Margaret Brandeau
Coleman F. Fung Professor in the School of Engineering and Professor, by courtesy, of Health Policy
Management Science and Engineering
Bio
Professor Brandeau is the Coleman F. Fung Professor in the School of Engineering and a Professor of Health Policy (by Courtesy). Her research focuses on the development of applied mathematical and economic models to support health policy decisions. Her recent work has focused on HIV prevention and treatment programs, programs to control the US opioid epidemic, and policies for minimizing the spread of infectious diseases, including COVID-19. She has served as Principal Investigator or Co-PI on a broad range of funded research projects.
She is a Fellow of the Institute for Operations Research and Management Science (INFORMS) and a member of the Omega Rho International Honor Society for Operations Research and Management Science. From INFORMS she has received the President’s Award (recognizing important contributions to the welfare of society), the Pierskalla Prize (in 2001 and 2017, for research excellence in health care management science), the Philip McCord Morse Lectureship Award, and the Award for the Advancement of Women in Operations Research and the Management Sciences. She has also received the Award for Excellence in Application of Pharmacoeconomics and Health Outcomes Research from the International Society for Pharmacoeconomics and Outcomes Research, and a Presidential Young Investigator Award from the National Science Foundation, among other awards. Professor Brandeau earned a BS in Mathematics and an MS in Operations Research from MIT, and a PhD in Engineering-Economic Systems from Stanford.
Academic Appointments
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Professor, Management Science and Engineering
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Professor (By courtesy), Health Policy
Honors & Awards
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CEA Registry Paper of the Year Award, Center for the Evaluation of Value and Risk in Health, Tufts University (2022)
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Stanford Medicine Integrated Strategic Plan Star Award, Stanford University (2020)
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Pierskalla Best Paper Award, INFORMS (Institute for Operations Research and Management Science) (2017)
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Honorary Professor, Universidad Nacional de Ingeniería (National Engineering University), Peru (2016)
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Award for the Advancement of Women in Operations Research and the Management Sciences, INFORMS (Institute for Operations Research and Management Science) (2015)
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Member, Omega Rho Honor Society for Operations Research and Management Science (2015)
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Omega Rho Distinguished Lecture on Operations Research and Management Science, INFORMS (Institute for Operations Research and Management Science) (2015)
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Philip McCord Morse Lecturership Award, INFORMS (Institute for Operations Research and Management Science) (2015)
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21st Annual E. Leonard Arnoff Memorial Lecture on the Practice of Management Science, University of Cincinnati (2012)
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Wasserstrom Family Distinguished Lecturer, Northwestern University (2012)
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Fellow, INFORMS (Institute for Operations Research and Management Science) (2009)
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Graduate Teaching Award, Department of Management Science and Engineering (2008-2009)
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Award for Excellence in Application of Pharmacoeconomics and Health Outcomes Research, ISPOR (International Society for Pharmacoeconomics and Outcomes Research) (2008)
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President's Award, INFORMS (Institute for Operations Research and Management Science) (2008)
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Pierskalla Best Paper Award, INFORMS (Institute for Operations Research and Management Science) (2001)
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Annual Outstanding Paper Award, Society for Computer Simulation (1996)
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Eugene L. Grant Teaching Award, Stanford School of Engineering (1990-1991)
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Presidential Young Investigator Award, National Science Foundation (1988-1993)
Boards, Advisory Committees, Professional Organizations
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Member, International Advisory Committee, Instituto Sistemas Complejos de Ingeniería, Santiago, Chile (2023 - Present)
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Member, Office of AIDS Research Advisory Council, National Institutes of Health (2018 - 2023)
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Diversity, Equity and Inclusion Ambassador, INFORMS (Institute for Operations Research and Management Science) (2020 - 2022)
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Member, Stanford-Lancet Commission on the North American Opioid Crisis (2020 - 2021)
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Member, Natl Acad Sci Eng and Med Committee on Equitable Allocation of Vaccine for the Novel Coronavirus (2020 - 2020)
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Member, Board of Scientific Counselors, CDC Office of Public Health Preparedness & Response (2012 - 2019)
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Editorial Board Member, Health Care Management Science (1997 - 2019)
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Member, Institute of Medicine Standing Committee for the CDC Division of the Strategic National Stockpile (2015 - 2017)
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Member, BSC/NBSB Working Group, Strategic National Stockpile (SNS) Review 20/20 (2012 - 2013)
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Member, Institute of Medicine Committee on Prepositioned Medical Countermeasures (2011 - 2011)
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Member, Institute of Medicine Committee on the Prevention and Control of Viral Hepatitis Infections in the US (2008 - 2009)
Professional Education
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PhD, Stanford University, Engineering-Economic Systems (1985)
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MS, Massachusetts Institute of Technology, Operations Research (1978)
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BS, Massachusetts Institute of Technology, Mathematics (1977)
Patents
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Corey A. Billington, Margaret L. Brandeau. "United States Patent 5,258,915 System and Method for Optimum Operation Assignments in Printed Circuit Board Manufacturing", Hewlett-Packard, Nov 2, 1993
2024-25 Courses
- Doctoral Research Seminar in Health Systems Modeling
HRP 390, MS&E 390 (Aut, Win, Spr) - Health Policy Modeling
HRP 293, MS&E 292 (Win) - The Ethical Analyst
MS&E 254 (Spr) - The Ethical Analyst
MS&E 254A (Spr) -
Independent Studies (4)
- Biomedical Informatics Teaching Methods
BIOMEDIN 290 (Aut, Win, Spr, Sum) - Directed Reading and Research
BIOMEDIN 299 (Aut, Win, Spr, Sum) - Directed Reading and Research
MS&E 408 (Aut, Win, Spr) - Medical Scholars Research
BIOMEDIN 370 (Aut, Win, Spr, Sum)
- Biomedical Informatics Teaching Methods
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Prior Year Courses
2023-24 Courses
- Doctoral Research Seminar in Health Systems Modeling
HRP 390, MS&E 390 (Aut, Win, Spr) - Health Policy Modeling
HRP 293, MS&E 292 (Win) - Part-Time Practical Training
MS&E 208E (Aut) - Practical Training
MS&E 208A (Aut) - Practical Training
MS&E 208B (Aut) - Practical Training
MS&E 208C (Aut) - Practical Training
MS&E 208D (Aut)
2022-23 Courses
- Doctoral Research Seminar in Health Systems Modeling
MS&E 390 (Aut, Win, Spr) - Health Policy Modeling
MS&E 292 (Win)
- Doctoral Research Seminar in Health Systems Modeling
Stanford Advisees
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Doctoral Dissertation Advisor (AC)
Paul Dupenloup, Grace Guan, Gary Qian -
Master's Program Advisor
Louisa Edwards, Loubaba El Ayoubi, Carolyn Ky, Chena Lee, Tiantian Meng, Amit Padaki, Ishan Sinha, Clara Wu, Yan Bo Zeng -
Doctoral (Program)
Yupeng Chen, Varun Gande, Yuewei Ling, Sean Tsung
All Publications
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Comparison of physiological and clinical reactions to COVID-19 and influenza vaccination
COMMUNICATIONS MEDICINE
2024; 4 (1): 169
Abstract
Public reluctance to receive COVID-19 vaccination is associated with safety concerns. By contrast, the seasonal influenza vaccine has been administered for decades with a solid safety record and a high level of public acceptance. We compare the safety profile of the BNT162b2 COVID-19 booster vaccine to that of the seasonal influenza vaccine.We study a prospective cohort of 5079 participants in Israel and a retrospective cohort of 250,000 members of MHS selected randomly. We examine reactions to BNT162b2 mRNA COVID-19 booster and to influenza vaccinations. All prospective cohort participants wore a smartwatch and completed a daily digital questionnaire. We compare pre-vaccination and post-vaccination smartwatch heart-rate data, and a stress measure based on heart-rate variability. We also examine adverse events from electronic health records.In the prospective cohort, 1905 participants receive the COVID-19 booster vaccine; 899 receive influenza vaccination. Focusing on those who receive both vaccines yields a total of 689 participants in the prospective cohort and 31,297 members in the retrospective cohort. Individuals reporting a more severe reaction after influenza vaccination tend to likewise report a more severe reaction after COVID-19 vaccination. In paired analysis, the increase in both heart rate and stress measure for each participant is higher for COVID-19 than for influenza in the first 2 days after vaccination. No elevated risk of hospitalization due to adverse events is found following either vaccine. Except for Bell's palsy after influenza vaccination, no elevated risk of adverse events is found.The more pronounced side effects after COVID-19 vaccination may explain the greater concern associated with it. Nevertheless, our comprehensive analysis supports the safety profile of both vaccines.
View details for DOI 10.1038/s43856-024-00588-7
View details for Web of Science ID 001297020900001
View details for PubMedID 39181950
View details for PubMedCentralID PMC11344792
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Changes in behavior and biomarkers during the diagnostic decision period for COVID-19, influenza, and group A streptococcus (GAS): a two-year prospective cohort study inIsrael.
The Lancet regional health. Europe
2024; 42: 100934
Abstract
Background: Limited knowledge exists regarding behavioral and biomarker shifts during the period from respiratory infection exposure to testing decisions (the diagnostic decision period), a key phase affecting transmission dynamics and public health strategy development. This study aims to examine the changes in behavior and biomarkers during the diagnostic decision period for COVID-19, influenza, and group A streptococcus (GAS).Methods: We analyzed data from a two-year prospective cohort study involving 4795 participants in Israel, incorporating smartwatch data, self-reported symptoms, and medical records. Our analysis focused on three critical phases: the digital incubation period (from exposure to physiological anomalies detected by smartwatches), the symptomatic incubation period (from exposure to onset of symptoms), and the diagnostic decision period for influenza, COVID-19, and GAS.Findings: The delay between initial symptom reporting and testing was 39 [95% confidence interval (CI): 34-45] hours for influenza, 53 [95% CI: 49-58] hours for COVID-19, and 38 [95% CI: 32-46] hours for GAS, with 73 [95% CI: 67-78] hours from anomalies in heart measures to symptom onset for influenza, 23 [95% CI: 18-27] hours for COVID-19, and 62 [95% CI: 54-68] hours for GAS. Analyzing the entire course of infection of each individual, the greatest changes in heart rates were detected 67.6 [95% CI: 62.8-72.5] hours prior to testing for influenza, 64.1 [95% CI: 61.4-66.7] hours prior for COVID-19, and 58.2 [95% CI: 52.1-64.2] hours prior for GAS. In contrast, the greatest reduction in physical activities and social contacts occurred after testing.Interpretation: These findings highlight the delayed response of patients in seeking medical attention and reducing social contacts and demonstrate the transformative potential of smartwatches for identifying infection and enabling timely public health interventions.Funding: This work was supported by the European Research Council, project #949850, the Israel Science Foundation (ISF), grant No. 3409/19, within the Israel Precision Medicine Partnership program, and a Koret Foundation gift for Smart Cities and Digital Living.
View details for DOI 10.1016/j.lanepe.2024.100934
View details for PubMedID 38800112
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Vaccination for communicable endemic diseases: optimal allocation of initial and booster vaccine doses.
Journal of mathematical biology
2024; 89 (2): 21
Abstract
For some communicable endemic diseases (e.g., influenza, COVID-19), vaccination is an effective means of preventing the spread of infection and reducing mortality, but must be augmented over time with vaccine booster doses. We consider the problem of optimally allocating a limited supply of vaccines over time between different subgroups of a population and between initial versus booster vaccine doses, allowing for multiple booster doses. We first consider an SIS model with interacting population groups and four different objectives: those of minimizing cumulative infections, deaths, life years lost, or quality-adjusted life years lost due to death. We solve the problem sequentially: for each time period, we approximate the system dynamics using Taylor series expansions, and reduce the problem to a piecewise linear convex optimization problem for which we derive intuitive closed-form solutions. We then extend the analysis to the case of an SEIS model. In both cases vaccines are allocated to groups based on their priority order until the vaccine supply is exhausted. Numerical simulations show that our analytical solutions achieve results that are close to optimal with objective function values significantly better than would be obtained using simple allocation rules such as allocation proportional to population group size. In addition to being accurate and interpretable, the solutions are easy to implement in practice. Interpretable models are particularly important in public health decision making.
View details for DOI 10.1007/s00285-024-02111-x
View details for PubMedID 38926228
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Prediction and detection of side effects severity following COVID-19 and influenza vaccinations: utilizing smartwatches and smartphones.
Scientific reports
2024; 14 (1): 6012
Abstract
Vaccines stand out as one of the most effective tools in our arsenal for reducing morbidity and mortality. Nonetheless, public hesitancy towards vaccination often stems from concerns about potential side effects, which can vary from person to person. As of now, there are no automated systems available to proactively warn against potential side effects or gauge their severity following vaccination. We have developed machine learning (ML) models designed to predict and detect the severity of post-vaccination side effects. Our study involved 2111 participants who had received at least one dose of either a COVID-19 or influenza vaccine. Each participant was equipped with a Garmin Vivosmart 4 smartwatch and was required to complete a daily self-reported questionnaire regarding local and systemic reactions through a dedicated mobile application. Our XGBoost models yielded an area under the receiver operating characteristic curve (AUROC) of 0.69 and 0.74 in predicting and detecting moderate to severe side effects, respectively. These predictions were primarily based on variables such as vaccine type (influenza vs. COVID-19), the individual's history of side effects from previous vaccines, and specific data collected from the smartwatches prior to vaccine administration, including resting heart rate, heart rate, and heart rate variability. In conclusion, our findings suggest that wearable devices can provide an objective and continuous method for predicting and monitoring moderate to severe vaccine side effects. This technology has the potential to improve clinical trials by automating the classification of vaccine severity.
View details for DOI 10.1038/s41598-024-56561-w
View details for PubMedID 38472345
View details for PubMedCentralID 8747859
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Estimated effectiveness and cost-effectiveness of opioid use disorder treatment under proposed U.S. regulatory relaxations: A model-based analysis.
Drug and alcohol dependence
2024; 256: 111112
Abstract
AIM: To assess the effectiveness and cost-effectiveness of buprenorphine and methadone treatment in the U.S. if exemptions expanding coverage for substance use disorder services via telehealth and allowing opioid treatment programs to supply a greater number of take-home doses of medications for opioid use disorder (OUD) continue (Notice of Proposed Rule Making, NPRM).DESIGN SETTING AND PARTICIPANTS: Model-based analysis of buprenorphine and methadone treatment for a cohort of 100,000 individuals with OUD, varying treatment retention and overdose risk among individuals receiving and not receiving methadone treatment compared to the status quo (no NPRM).INTERVENTION: Buprenorphine and methadone treatment under NPRM.MEASUREMENTS: Fatal and nonfatal overdoses and deaths over five years, discounted lifetime per person QALYs and costs.FINDINGS: For buprenorphine treatment under the status quo, 1.21 QALYs are gained at a cost of $19,200/QALY gained compared to no treatment; with 20% higher treatment retention, 1.28 QALYs are gained at a cost of $17,900/QALY gained compared to no treatment, and the strategy dominates the status quo. For methadone treatment under the status quo, 1.11 QALYs are gained at a cost of $17,900/QALY gained compared to no treatment. In all scenarios, methadone provision cost less than $20,000/QALY gained compared to no treatment, and less than $50,000/QALY gained compared to status quo methadone treatment.CONCLUSIONS: Buprenorphine and methadone OUD treatment under NPRM are likely to be effective and cost-effective. Increases in overdose risk with take-home methadone would reduce health benefits. Clinical and technological strategies could mitigate this risk.
View details for DOI 10.1016/j.drugalcdep.2024.111112
View details for PubMedID 38335797
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Predicting COVID-19 Outbreaks in Correctional Facilities Using Machine Learning.
MDM policy & practice
2024; 9 (1): 23814683231222469
Abstract
Introduction. The risk of infectious disease transmission, including COVID-19, is disproportionately high in correctional facilities due to close living conditions, relatively low levels of vaccination, and reduced access to testing and treatment. While much progress has been made on describing and mitigating COVID-19 and other infectious disease risk in jails and prisons, there are open questions about which data can best predict future outbreaks. Methods. We used facility data and demographic and health data collected from 24 prison facilities in the Pennsylvania Department of Corrections from March 2020 to May 2021 to determine which sources of data best predict a coming COVID-19 outbreak in a prison facility. We used machine learning methods to cluster the prisons into groups based on similar facility-level characteristics, including size, rurality, and demographics of incarcerated people. We developed logistic regression classification models to predict for each cluster, before and after vaccine availability, whether there would be no cases, an outbreak defined as 2 or more cases, or a large outbreak, defined as 10 or more cases in the next 1, 2, and 3 d. We compared these predictions to data on outbreaks that occurred. Results. Facilities were divided into 8 clusters of sizes varying from 1 to 7 facilities per cluster. We trained 60 logistic regressions; 20 had test sets with between 35% and 65% of days with outbreaks detected. Of these, 8 logistic regressions correctly predicted the occurrence of an outbreak more than 55% of the time. The most common predictive feature was incident cases among the incarcerated population from 2 to 32 d prior. Other predictive features included the number of tests administered from 1 to 33 d prior, total population, test positivity rate, and county deaths, hospitalizations, and incident cases. Cumulative cases, vaccination rates, and race, ethnicity, or age statistics for incarcerated populations were generally not predictive. Conclusions. County-level measures of COVID-19, facility population, and test positivity rate appear as potential promising predictors of COVID-19 outbreaks in correctional facilities, suggesting that correctional facilities should monitor community transmission in addition to facility transmission to inform future outbreak response decisions. These efforts should not be limited to COVID-19 but should include any large-scale infectious disease outbreak that may involve institution-community transmission.The risk of infectious disease transmission, including COVID-19, is disproportionately high in correctional facilities.We used machine learning methods with data collected from 24 prison facilities in the Pennsylvania Department of Corrections to determine which sources of data best predict a coming COVID-19 outbreak in a prison facility.Key predictors included county-level measures of COVID-19, facility population, and the test positivity rate in a facility.Fortifying correctional facilities with the ability to monitor local community rates of infection (e.g., though improved interagency collaboration and data sharing) along with continued testing of incarcerated people and staff can help correctional facilities better predict-and respond to-future infectious disease outbreaks.
View details for DOI 10.1177/23814683231222469
View details for PubMedID 38293655
View details for PubMedCentralID PMC10826393
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SCAN for Abuse: Electronic Health Record-Based Universal Child Abuse Screening.
Journal of pediatric surgery
2023
Abstract
Identification of physical abuse at the point of care without a systematic approach remains inherently subjective and prone to judgement error. This study examines the implementation of an electronic health record (EHR)-based universal child injury screen (CIS) to improve detection rates of child abuse.CIS was implemented in the EHR admission documentation for all patients age 5 or younger at a single medical center, with the following questions. 1) "Is this patient an injured/trauma patient?" 2) "If this is a trauma/injured patient, where did the injury occur?" A "Yes" response to Question 1 would alert a team of child abuse pediatricians and social workers to determine if a patient required formal child abuse clinical evaluation. Patients who received positive CIS responses, formal child abuse work-up, and/or reports to Child Protective Services (CPS) were reviewed for analysis. CPS rates from historical controls (2017-2018) were compared to post-implementation rates (2019-2021).Between 2019 and 2021, 14,150 patients were screened with CIS. 286 (2.0 %) patients screened received positive CIS responses. 166 (58.0 %) of these patients with positive CIS responses would not have otherwise been identified for child abuse evaluation by their treating teams. 18 (10.8 %) of the patients identified by the CIS and not by the treating team were later reported to CPS. Facility CPS reporting rates for physical abuse were 1.2 per 1000 admitted children age 5 or younger (pre-intervention) versus 4.2 per 1000 (post-intervention).Introduction of CIS led to increased detection suspected child abuse among children age 5 or younger.Level II.Study of Diagnostic Test.
View details for DOI 10.1016/j.jpedsurg.2023.10.025
View details for PubMedID 37953157
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Responding to the US opioid crisis: leveraging analytics to support decision making.
Health care management science
2023
Abstract
The US is experiencing a severe opioid epidemic with more than 80,000 opioid overdose deaths occurring in 2022. Beyond the tragic loss of life, opioid use disorder (OUD) has emerged as a major contributor to morbidity, lost productivity, mounting criminal justice system costs, and significant social disruption. This Current Opinion article highlights opportunities for analytics in supporting policy making for effective response to this crisis. We describe modeling opportunities in the following areas: understanding the opioid epidemic (e.g., the prevalence and incidence of OUD in different geographic regions, demographics of individuals with OUD, rates of overdose and overdose death, patterns of drug use and associated disease outbreaks, and access to and use of treatment for OUD); assessing policies for preventing and treating OUD, including mitigation of social conditions that increase the risk of OUD; and evaluating potential regulatory and criminal justice system reforms.
View details for DOI 10.1007/s10729-023-09657-0
View details for PubMedID 37804456
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Cost-effectiveness of office-based buprenorphine treatment for opioid use disorder.
Drug and alcohol dependence
2022; 243: 109762
Abstract
To assess the effectiveness and cost-effectiveness of office-based buprenorphine treatment (OBBT) in the U.S.We performed a model-based analysis of buprenorphine treatment provided in a primary care setting for the U.S. population with OUD.Buprenorphine treatment provided in a primary care setting.Fatal and nonfatal overdoses and deaths over five years, discounted lifetime quality-adjusted life years (QALYs), costs.For a cohort of 100,000 untreated individuals who enter OBBT, approximately 9350 overdoses would be averted over five years; of these, approximately 900 would have been fatal. OBBT compared to no treatment would yield 1.07 incremental lifetime QALYs per person at an incremental cost of $17,000 per QALY gained when using a healthcare perspective. If OBBT is half as effective and twice as expensive as assumed in the base case, the incremental cost when using a healthcare perspective is $25,500 per QALY gained. Using a limited societal perspective that additionally includes patient costs and criminal justice costs, OBBT is cost-saving compared to no treatment even under pessimistic assumptions about efficacy and cost.Expansion of OBBT would be highly cost-effective compared to no treatment when considered from a healthcare perspective, and cost-saving when reduced criminal justice costs are included. Given the continuing opioid crisis in the U.S., expansion of this care option should be a high priority.
View details for DOI 10.1016/j.drugalcdep.2022.109762
View details for PubMedID 36621198
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Higher sensitivity monitoring of reactions to COVID-19 vaccination using smartwatches.
NPJ digital medicine
2022; 5 (1): 140
Abstract
More than 12 billion COVID-19 vaccination shots have been administered as of August 2022, but information from active surveillance about vaccine safety is limited. Surveillance is generally based on self-reporting, making the monitoring process subjective. We study participants in Israel who received their second or third Pfizer BioNTech COVID-19 vaccination. All participants wore a Garmin Vivosmart 4 smartwatch and completed a daily questionnaire via smartphone. We compare post-vaccination smartwatch heart rate data and a Garmin-computed stress measure based on heart rate variability with data from the patient questionnaires. Using a mixed effects panel regression to remove participant-level fixed and random effects, we identify considerable changes in smartwatch measures in the 72 h post-vaccination even among participants who reported no side effects in the questionnaire. Wearable devices were more sensitive than questionnaires in determining when participants returned to baseline levels. We conclude that wearable devices can detect physiological responses following vaccination that may not be captured by patient self-reporting. More broadly, the ubiquity of smartwatches provides an opportunity to gather improved data on patient health, including active surveillance of vaccine safety.
View details for DOI 10.1038/s41746-022-00683-w
View details for PubMedID 36085312
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Sequential allocation of vaccine to control an infectious disease.
Mathematical biosciences
2022: 108879
Abstract
The problem of optimally allocating a limited supply of vaccine to control a communicable disease has broad applications in public health and has received renewed attention during the COVID-19 pandemic. This allocation problem is highly complex and nonlinear. Decision makers need a practical, accurate, and interpretable method to guide vaccine allocation. In this paper we develop simple analytical conditions that can guide the allocation of vaccines over time. We consider four objectives: minimize new infections, minimize deaths, minimize life years lost, or minimize quality-adjusted life years lost due to death. We consider an SIR model with interacting population groups. We approximate the model using Taylor series expansions, and develop simple analytical conditions characterizing the optimal solution to the resulting problem for a single time period. We develop a solution approach in which we allocate vaccines using the analytical conditions in each time period based on the state of the epidemic at the start of the time period. We illustrate our method with an example of COVID-19 vaccination, calibrated to epidemic data from New York State. Using numerical simulations, we show that our method achieves near-optimal results over a wide range of vaccination scenarios. Our method provides a practical, intuitive, and accurate tool for decision makers as they allocate limited vaccines over time, and highlights the need for more interpretable models over complicated black box models to aid in decision making.
View details for DOI 10.1016/j.mbs.2022.108879
View details for PubMedID 35843382
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Self-Reported and Physiologic Reactions to Third BNT162b2 mRNA COVID-19 (Booster) Vaccine Dose.
Emerging infectious diseases
2022; 28 (7): 1375-1383
Abstract
Despite extensive technological advances in recent years, objective and continuous assessment of physiologic measures after vaccination is rarely performed. We conducted a prospective observational study to evaluate short-term self-reported and physiologic reactions to the booster BNT162b2 mRNA (Pfizer-BioNTech, https://www.pfizer.com) vaccine dose. A total of 1,609 participants were equipped with smartwatches and completed daily questionnaires through a dedicated mobile application. The extent of systemic reactions reported after the booster dose was similar to that of the second dose and considerably greater than that of the first dose. Analyses of objective heart rate and heart rate variability measures recorded by smartwatches further supported this finding. Subjective and objective reactions after the booster dose were more apparent in younger participants and in participants who did not have underlying medical conditions. Our findings further support the safety of the booster dose from subjective and objective perspectives and underscore the need for integrating wearables in clinical trials.
View details for DOI 10.3201/eid2807.212330
View details for PubMedID 35654410
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Metamodeling for Policy Simulations with Multivariate Outcomes.
Medical decision making : an international journal of the Society for Medical Decision Making
2022: 272989X221105079
Abstract
PURPOSE: Metamodels are simplified approximations of more complex models that can be used as surrogates for the original models. Challenges in using metamodels for policy analysis arise when there are multiple correlated outputs of interest. We develop a framework for metamodeling with policy simulations to accommodate multivariate outcomes.METHODS: We combine 2 algorithm adaptation methods-multitarget stacking and regression chain with maximum correlation-with different base learners including linear regression (LR), elastic net (EE) with second-order terms, Gaussian process regression (GPR), random forests (RFs), and neural networks. We optimize integrated models using variable selection and hyperparameter tuning. We compare the accuracy, efficiency, and interpretability of different approaches. As an example application, we develop metamodels to emulate a microsimulation model of testing and treatment strategies for hepatitis C in correctional settings.RESULTS: Output variables from the simulation model were correlated (average rho = 0.58). Without multioutput algorithm adaptation methods, in-sample fit (measured by R2) ranged from 0.881 for LR to 0.987 for GPR. The multioutput algorithm adaptation method increased R2 by an average 0.002 across base learners. Variable selection and hyperparameter tuning increased R2 by 0.009. Simpler models such as LR, EE, and RF required minimal training and prediction time. LR and EE had advantages in model interpretability, and we considered methods for improving the interpretability of other models.CONCLUSIONS: In our example application, the choice of base learner had the largest impact on R2; multioutput algorithm adaptation and variable selection and hyperparameter tuning had a modest impact. Although advantages and disadvantages of specific learning algorithms may vary across different modeling applications, our framework for metamodeling in policy analyses with multivariate outcomes has broad applicability to decision analysis in health and medicine.
View details for DOI 10.1177/0272989X221105079
View details for PubMedID 35735216
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When Is Mass Prophylaxis Cost-Effective for Epidemic Control? A Comparison of Decision Approaches.
Medical decision making : an international journal of the Society for Medical Decision Making
2022: 272989X221098409
Abstract
BACKGROUND: For certain communicable disease outbreaks, mass prophylaxis of uninfected individuals can curtail new infections. When an outbreak emerges, decision makers could benefit from methods to quickly determine whether mass prophylaxis is cost-effective. We consider 2 approaches: a simple decision model and machine learning meta-models. The motivating example is plague in Madagascar.METHODS: We use a susceptible-exposed-infectious-removed (SEIR) epidemic model to derive a decision rule based on the fraction of the population infected, effective reproduction ratio, infection fatality rate, quality-adjusted life-year loss associated with death, prophylaxis effectiveness and cost, time horizon, and willingness-to-pay threshold. We also develop machine learning meta-models of a detailed model of plague in Madagascar using logistic regression, random forest, and neural network models. In numerical experiments, we compare results using the decision rule and the meta-models to results obtained using the simulation model. We vary the initial fraction of the population infected, the effective reproduction ratio, the intervention start date and duration, and the cost of prophylaxis.LIMITATIONS: We assume homogeneous mixing and no negative side effects due to antibiotic prophylaxis.RESULTS: The simple decision rule matched the SEIR model outcome in 85.4% of scenarios. Using data for a 2017 plague outbreak in Madagascar, the decision rule correctly indicated that mass prophylaxis was not cost-effective. The meta-models were significantly more accurate, with an accuracy of 92.8% for logistic regression, 95.8% for the neural network model, and 96.9% for the random forest model.CONCLUSIONS: A simple decision rule using minimal information about an outbreak can accurately evaluate the cost-effectiveness of mass prophylaxis for outbreak mitigation. Meta-models of a complex disease simulation can achieve higher accuracy but with greater computational and data requirements and less interpretability.HIGHLIGHTS: We use a susceptible-exposed-infectious-removed model and net monetary benefit to derive a simple decision rule to evaluate the cost-effectiveness of mass prophylaxis.We use the example of plague in Madagascar to compare the performance of the analytically derived decision rule to that of machine learning meta-models trained on a stochastic dynamic transmission model.We assess the accuracy of each approach for different combinations of disease dynamics and intervention scenarios.The machine learning meta-models are more accurate predictors of mass prophylaxis cost-effectiveness. However, the simple decision rule is also accurate and may be a preferred substitute in low-resource settings.
View details for DOI 10.1177/0272989X221098409
View details for PubMedID 35591754
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Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation.
Statistics in medicine
2022
Abstract
Outbreaks of an endemic infectious disease can occur when the disease is introduced into a highly susceptible subpopulation or when the disease enters a network of connected individuals. For example, significant HIV outbreaks among people who inject drugs have occurred in at least half a dozen US states in recent years. This motivates the current study: how can limited testing resources be allocated across geographic regions to rapidly detect outbreaks of an endemic infectious disease? We develop an adaptive sampling algorithm that uses profile likelihood to estimate the distribution of the number of positive tests that would occur for each location in a future time period if that location were sampled. Sampling is performed in the location with the highest estimated probability of triggering an outbreak alarm in the next time period. The alarm function is determined by a semiparametric likelihood ratio test. We compare the profile likelihood sampling (PLS) method numerically to uniform random sampling (URS) and Thompson sampling (TS). TS was worse than URS when the outbreak occurred in a location with lower initial prevalence than other locations. PLS had lower time to outbreak detection than TS in some but not all scenarios, but was always better than URS even when the outbreak occurred in a location with a lower initial prevalence than other locations. PLS provides an effective and reliable method for rapidly detecting endemic disease outbreaks that is robust to this uncertainty.
View details for DOI 10.1002/sim.9420
View details for PubMedID 35527474
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Responding to the opioid crisis in North America and beyond: recommendations of the Stanford-Lancet Commission.
Lancet (London, England)
2022; 399 (10324): 555-604
View details for DOI 10.1016/S0140-6736(21)02252-2
View details for PubMedID 35122753
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Prevention and control of dengue and Chikungunya in Colombia: A cost-effectiveness analysis.
PLoS neglected tropical diseases
1800; 15 (12): e0010086
Abstract
BACKGROUND: Chikungunya and dengue are emerging diseases that have caused large outbreaks in various regions of the world. Both are both spread by Aedes aegypti and Aedes albopictus mosquitos. We developed a dynamic transmission model of chikungunya and dengue, calibrated to data from Colombia (June 2014 -December 2017).METHODOLOGY/PRINCIPAL FINDINGS: We evaluated the health benefits and cost-effectiveness of residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup vaccination for individuals aged 10-19 or 10-29, and portfolios of these interventions. Model calibration resulted in 300 realistic transmission parameters sets that produced close matches to disease-specific incidence and deaths. Insecticide was the preferred intervention and was cost-effective. Insecticide averted an estimated 95 chikungunya cases and 114 dengue cases per 100,000 people, 61 deaths, and 4,523 disability-adjusted life years (DALYs). In sensitivity analysis, strategies that included dengue vaccination were cost-effective only when the vaccine cost was 14% of the current price.CONCLUSIONS/SIGNIFICANCE: Insecticide to prevent chikungunya and dengue in Columbia could generate significant health benefits and be cost-effective. Because of limits on diagnostic accuracy and vaccine efficacy, the cost of dengue testing and vaccination must decrease dramatically for such vaccination to be cost-effective in Colombia. The vectors for chikungunya and dengue have recently spread to new regions, highlighting the importance of understanding the effectiveness and cost-effectiveness of policies aimed at preventing these diseases.
View details for DOI 10.1371/journal.pntd.0010086
View details for PubMedID 34965277
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Quantile Markov Decision Processes
OPERATIONS RESEARCH
2021
View details for DOI 10.1287/opre.2021.2123
View details for Web of Science ID 000731911500001
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Quantile Markov Decision Processes.
Operations research
2021; 70 (3): 1428-1447
Abstract
The goal of a traditional Markov decision process (MDP) is to maximize expected cumulative reward over a defined horizon (possibly infinite). In many applications, however, a decision maker may be interested in optimizing a specific quantile of the cumulative reward instead of its expectation. In this paper we consider the problem of optimizing the quantiles of the cumulative rewards of a Markov decision process (MDP), which we refer to as a quantile Markov decision process (QMDP). We provide analytical results characterizing the optimal QMDP value function and present a dynamic programming-based algorithm to solve for the optimal policy. The algorithm also extends to the MDP problem with a conditional value-at-risk (CVaR) objective. We illustrate the practical relevance of our model by evaluating it on an HIV treatment initiation problem, where patients aim to balance the potential benefits and risks of the treatment.
View details for DOI 10.1287/opre.2021.2123
View details for PubMedID 36034163
View details for PubMedCentralID PMC9401554
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Effectiveness of Policies for Addressing the US Opioid Epidemic: A Model-Based Analysis from the Stanford-Lancet Commission on the North American Opioid Crisis.
Lancet Regional Health. Americas
2021; 3
Abstract
Background: The U.S. opioid crisis has been exacerbated by COVID-19 and the spread of synthetic opioids (e.g., fentanyl).Methods: We model the effectiveness of reduced prescribing, drug rescheduling, prescription monitoring programs (PMPs), tamper-resistant drug reformulation, excess opioid disposal, naloxone availability, syringe exchange, pharmacotherapy, and psychosocial treatment. We measure life years, quality-adjusted life years (QALYs), and opioid-related deaths over five and ten years.Findings: Under the status quo, our model predicts that approximately 547,000 opioid-related deaths will occur from 2020 to 2024 (range 441,000 - 613,000), rising to 1,220,000 (range 996,000 - 1,383,000) by 2029. Expanding naloxone availability by 30% had the largest effect, averting 25% of opioid deaths. Pharmacotherapy, syringe exchange, psychosocial treatment, and PMPs are uniformly beneficial, reducing opioid-related deaths while leading to gains in life years and QALYs. Reduced prescribing and increasing excess opioid disposal programs would reduce total deaths, but would lead to more heroin deaths in the short term. Drug rescheduling would increase total deaths over five years as some opioid users escalate to heroin, but decrease deaths over ten years. Combined interventions would lead to greater increases in life years, QALYs, and deaths averted, although in many cases the results are subadditive.Interpretation: Expanded health services for individuals with opioid use disorder combined with PMPs and reduced opioid prescribing would moderately lessen the severity of the opioid crisis over the next decade. Tragically, even with improved public policies, significant morbidity and mortality is inevitable.
View details for DOI 10.1016/j.lana.2021.100031
View details for PubMedID 34790907
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Who Are the Gatekeepers? An Examination of Diversity in INFORMS Journal Editorial Boards
SERVICE SCIENCE
2021; 13 (3): 109-132
View details for DOI 10.1287/serv.2021.0274
View details for Web of Science ID 000702739600001
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Personalization of Medical Treatment Decisions: Simplifying Complex Models while Maintaining Patient Health Outcomes.
Medical decision making : an international journal of the Society for Medical Decision Making
2021: 272989X211037921
Abstract
BACKGROUND: Personalizing medical treatments based on patient-specific risks and preferences can improve patient health. However, models to support personalized treatment decisions are often complex and difficult to interpret, limiting their clinical application.METHODS: We present a new method, using machine learning to create meta-models, for simplifying complex models for personalizing medical treatment decisions. We consider simple interpretable models, interpretable ensemble models, and noninterpretable ensemble models. We use variable selection with a penalty for patient-specific risks and/or preferences that are difficult, risky, or costly to obtain. We interpret the meta-models to the extent permitted by their model architectures. We illustrate our method by applying it to simplify a previously developed model for personalized selection of antipsychotic drugs for patients with schizophrenia.RESULTS: The best simplified interpretable, interpretable ensemble, and noninterpretable ensemble models contained at most half the number of patient-specific risks and preferences compared with the original model. The simplified models achieved 60.5% (95% credible interval [crI]: 55.2-65.4), 60.8% (95% crI: 55.5-65.7), and 83.8% (95% crI: 80.8-86.6), respectively, of the net health benefit of the original model (quality-adjusted life-years gained). Important variables in all models were similar and made intuitive sense. Computation time for the meta-models was orders of magnitude less than for the original model.LIMITATIONS: The simplified models share the limitations of the original model (e.g., potential biases).CONCLUSIONS: Our meta-modeling method is disease- and model- agnostic and can be used to simplify complex models for personalization, allowing for variable selection in addition to improved model interpretability and computational performance. Simplified models may be more likely to be adopted in clinical settings and can help improve equity in patient outcomes.
View details for DOI 10.1177/0272989X211037921
View details for PubMedID 34416832
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Assessing Interventions That Prevent Multiple Infectious Diseases: Simple Methods for Multidisease Modeling.
Medical decision making : an international journal of the Society for Medical Decision Making
2021: 272989X211033287
Abstract
BACKGROUND: Many cost-effectiveness analyses (CEAs) only consider outcomes for a single disease when comparing interventions that prevent or treat 1 disease (e.g., vaccination) to interventions that prevent or treat multiple diseases (e.g., vector control to prevent mosquito-borne diseases). An intervention targeted to a single disease may be preferred to a broader intervention in a single-disease model, but this conclusion might change if outcomes from the additional diseases were included. However, multidisease models are often complex and difficult to construct.METHODS: We present conditions for when multiple diseases should be considered in such a CEA. We propose methods for estimating health outcomes and costs associated with control of additional diseases using parallel single-disease models. Parallel modeling can incorporate competing mortality and coinfection from multiple diseases while maintaining model simplicity. We illustrate our approach with a CEA that compares a dengue vaccine, a chikungunya vaccine, and mosquito control via insecticide and mosquito nets, which can prevent dengue, chikungunya, Zika, and yellow fever.RESULTS: The parallel models and the multidisease model generated similar estimates of disease incidence and deaths with much less complexity. When using this method in our case study, considering only chikungunya and dengue, the preferred strategy was insecticide. A broader strategy-insecticide plus long-lasting insecticide-treated nets-was not preferred when Zika and yellow fever were included, suggesting the conclusion is robust even without the explicit inclusion of all affected diseases.LIMITATIONS: Parallel modeling assumes independent probabilities of infection for each disease.CONCLUSIONS: When multidisease effects are important, our parallel modeling method can be used to model multiple diseases accurately while avoiding additional complexity.
View details for DOI 10.1177/0272989X211033287
View details for PubMedID 34378462
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Modeling the Cost-Effectiveness of Interventions to Prevent Plague in Madagascar.
Tropical medicine and infectious disease
2021; 6 (2)
Abstract
Plague (Yersinia pestis) remains endemic in certain parts of the world. We assessed the cost-effectiveness of plague control interventions recommended by the World Health Organization with particular consideration to intervention coverage and timing. We developed a dynamic model of the spread of plague between interacting populations of humans, rats, and fleas and performed a cost-effectiveness analysis calibrated to a 2017 Madagascar outbreak. We assessed three interventions alone and in combination: expanded access to antibiotic treatment with doxycycline, mass distribution of doxycycline prophylaxis, and mass distribution of malathion. We varied intervention timing and coverage levels. We calculated costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios from a healthcare perspective. The preferred intervention, using a cost-effectiveness threshold of $1350/QALY (GDP per capita in Madagascar), was expanded access to antibiotic treatment with doxycycline with 100% coverage starting immediately after the first reported case, gaining 543 QALYs at an incremental cost of $1023/QALY gained. Sensitivity analyses support expanded access to antibiotic treatment and leave open the possibility that mass distribution of doxycycline prophylaxis or mass distribution of malathion could be cost-effective. Our analysis highlights the potential for rapid expansion of access to doxycycline upon recognition of plague outbreaks to cost-effectively prevent future large-scale plague outbreaks and highlights the importance of intervention timing.
View details for DOI 10.3390/tropicalmed6020101
View details for PubMedID 34208006
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Effectiveness of Face Masks in Reducing the Spread of COVID-19: A Model-Based Analysis.
Medical decision making : an international journal of the Society for Medical Decision Making
2021: 272989X211019029
Abstract
BACKGROUND: The World Health Organization and US Centers for Disease Control and Prevention recommend that both infected and susceptible people wear face masks to protect against COVID-19.METHODS: We develop a dynamic disease model to assess the effectiveness of face masks in reducing the spread of COVID-19, during an initial outbreak and a later resurgence, as a function of mask effectiveness, coverage, intervention timing, and time horizon. We instantiate the model for the COVID-19 outbreak in New York, with sensitivity analyses on key natural history parameters.RESULTS: During the initial epidemic outbreak, with no social distancing, only 100% coverage of masks with high effectiveness can reduce the effective reproductive number Re below 1. During a resurgence, with lowered transmission rates due to social distancing measures, masks with medium effectiveness at 80% coverage can reduce Re below 1 but cannot do so if individuals relax social distancing efforts. Full mask coverage could significantly improve outcomes during a resurgence: with social distancing, masks with at least medium effectiveness could reduce Re below 1 and avert almost all infections, even with intervention fatigue. For coverage levels below 100%, prioritizing masks that reduce the risk of an infected individual from spreading the infection rather than the risk of a susceptible individual from getting infected yields the greatest benefit.LIMITATIONS: Data regarding COVID-19 transmission are uncertain, and empirical evidence on mask effectiveness is limited. Our analyses assume homogeneous mixing, providing an upper bound on mask effectiveness.CONCLUSIONS: Even moderately effective face masks can play a role in reducing the spread of COVID-19, particularly with full coverage, but should be combined with social distancing measures to reduce Re below 1.[Box: see text].
View details for DOI 10.1177/0272989X211019029
View details for PubMedID 34041970
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Partial Personalization of Medical Treatment Decisions: Adverse Effects and Possible Solutions.
Medical decision making : an international journal of the Society for Medical Decision Making
2021: 272989X211013773
Abstract
BACKGROUND: Personalizing medical treatment decisions based on patient-specific risks and/or preferences can improve health outcomes. Decision makers frequently select treatments based on partial personalization (e.g., personalization based on risks but not preferences or vice versa) due to a lack of data about patient-specific risks and preferences. However, partially personalizing treatment decisions based on a subset of patient risks and/or preferences can result in worse population-level health outcomes than no personalization and can increase the variance of population-level health outcomes.METHODS: We develop a new method for partially personalizing treatment decisions that avoids these problems. Using a case study of antipsychotic treatment for schizophrenia, as well as 4 additional illustrative examples, we demonstrate the adverse effects and our method for avoiding them.RESULTS: For the schizophrenia treatment case study, using a previously proposed modeling approach for personalizing treatment decisions and using only a subset of patient preferences regarding treatment efficacy and side effects, mean population-level health outcomes decreased by 0.04 quality-adjusted life-years (QALYs; 95% credible interval [crI]: 0.02-0.06) per patient compared with no personalization. Using our new method and considering the same subset of patient preferences, mean population-level health outcomes increased by 0.01 QALYs (95% crI: 0.00-0.03) per patient as compared with no personalization, and the variance decreased.LIMITATIONS: We assumed a linear and additive utility function.CONCLUSIONS: Selecting personalized treatments for patients should be done in a way that does not decrease expected population-level health outcomes and does not increase their variance, thereby resulting in worse risk-adjusted, population-level health outcomes compared with treatment selection with no personalization. Our method can be used to ensure this, thereby helping patients realize the benefits of treatment personalization without the potential harms.
View details for DOI 10.1177/0272989X211013773
View details for PubMedID 34027738
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ASSESSING INTERVENTIONS THAT PREVENT MULTIPLE INFECTIOUS DISEASES: SIMPLE METHODS FOR MULTI-DISEASE MODELING
SAGE PUBLICATIONS INC. 2021: E335-E337
View details for Web of Science ID 000648637500258
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EFFECTIVENESS OF FACE MASKS IN REDUCING THE SPREAD OF COVID-19: A MODEL-BASED ANALYSIS
SAGE PUBLICATIONS INC. 2021: E20-E21
View details for Web of Science ID 000648637500029
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DEFER, TEST, OR MODIFY? IDENTIFYING THE OPTIMAL PORTFOLIO OF BLOOD SAFETY INTERVENTIONS
SAGE PUBLICATIONS INC. 2021: E16-E18
View details for Web of Science ID 000648637500027
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THE EFFECT OF INTERVENTIONS TO REDUCE COVID-19 IN A LARGE URBAN JAIL
SAGE PUBLICATIONS INC. 2021: E220-E221
View details for Web of Science ID 000648637500176
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OPTIMAL SURVEILLANCE OF HIV AMONG PEOPLE WHO INJECT DRUGS
SAGE PUBLICATIONS INC. 2021: E280-E282
View details for Web of Science ID 000648637500216
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Optimal allocation of limited vaccine to control an infectious disease: Simple analytical conditions.
Mathematical biosciences
2021: 108621
Abstract
When allocating limited vaccines to control an infectious disease, policy makers frequently have goals relating to individual health benefits (e.g., reduced morbidity and mortality) as well as population-level health benefits (e.g., reduced transmission and possible disease eradication). We consider the optimal allocation of a limited supply of a preventive vaccine to control an infectious disease, and four different allocation objectives: minimize new infections, deaths, life years lost, or quality-adjusted life years (QALYs) lost due to death. We consider an SIR model with n interacting populations, and a single allocation of vaccine at time 0. We approximate the model dynamics to develop simple analytical conditions characterizing the optimal vaccine allocation for each objective. We instantiate the model for an epidemic similar to COVID-19 and consider n=2 population groups: one group (individuals under age 65) with high transmission but low mortality and the other group (individuals age 65 or older) with low transmission but high mortality. We find that it is optimal to vaccinate younger individuals to minimize new infections, whereas it is optimal to vaccinate older individuals to minimize deaths, life years lost, or QALYs lost due to death. Numerical simulations show that the allocations resulting from our conditions match those found using much more computationally expensive algorithms such as exhaustive search. Sensitivity analysis on key parameters indicates that the optimal allocation is robust to changes in parameter values. The simple conditions we develop provide a useful means of informing vaccine allocation decisions for communicable diseases.
View details for DOI 10.1016/j.mbs.2021.108621
View details for PubMedID 33915160
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Predicting the Effectiveness of Endemic Infectious Disease Control Interventions: The Impact of Mass Action versus Network Model Structure.
Medical decision making : an international journal of the Society for Medical Decision Making
2021: 272989X211006025
Abstract
BACKGROUND: Analyses of the effectiveness of infectious disease control interventions often rely on dynamic transmission models to simulate intervention effects. We aim to understand how the choice of network or compartmental model can influence estimates of intervention effectiveness in the short and long term for an endemic disease with susceptible and infected states in which infection, once contracted, is lifelong.METHODS: We consider 4 disease models with different permutations of socially connected network versus unstructured contact (mass-action mixing) model and heterogeneous versus homogeneous disease risk. The models have susceptible and infected populations calibrated to the same long-term equilibrium disease prevalence. We consider a simple intervention with varying levels of coverage and efficacy that reduces transmission probabilities. We measure the rate of prevalence decline over the first 365 d after the intervention, long-term equilibrium prevalence, and long-term effective reproduction ratio at equilibrium.RESULTS: Prevalence declined up to 10% faster in homogeneous risk models than heterogeneous risk models. When the disease was not eradicated, the long-term equilibrium disease prevalence was higher in mass-action mixing models than in network models by 40% or more. This difference in long-term equilibrium prevalence between network versus mass-action mixing models was greater than that of heterogeneous versus homogeneous risk models (less than 30%); network models tended to have higher effective reproduction ratios than mass-action mixing models for given combinations of intervention coverage and efficacy.CONCLUSIONS: For interventions with high efficacy and coverage, mass-action mixing models could provide a sufficient estimate of effectiveness, whereas for interventions with low efficacy and coverage, or interventions in which outcomes are measured over short time horizons, predictions from network and mass-action models diverge, highlighting the importance of sensitivity analyses on model structure.HIGHLIGHTS: We calibrate 4 models-socially connected network versus unstructured contact (mass-action mixing) model and heterogeneous versus homogeneous disease risk-to 10% preintervention disease prevalence.We measure the short- and long-term intervention effectiveness of all models using the rate of prevalence decline, long-term equilibrium disease prevalence, and effective reproduction ratio.Generally, in the short term, prevalence declined faster in the homogeneous risk models than in the heterogeneous risk models.Generally, in the long term, equilibrium disease prevalence was higher in the mass-action mixing models than in the network models, and the effective reproduction ratio was higher in network models than in the mass-action mixing models.
View details for DOI 10.1177/0272989X211006025
View details for PubMedID 33899563
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Cost-effectiveness of Treatments for Opioid Use Disorder.
JAMA psychiatry
2021
Abstract
Importance: Opioid use disorder (OUD) is a significant cause of morbidity and mortality in the US, yet many individuals with OUD do not receive treatment.Objective: To assess the cost-effectiveness of OUD treatments and association of these treatments with outcomes in the US.Design and Setting: This model-based cost-effectiveness analysis included a US population with OUD.Interventions: Medication-assisted treatment (MAT) with buprenorphine, methadone, or injectable extended-release naltrexone; psychotherapy (beyond standard counseling); overdose education and naloxone distribution (OEND); and contingency management (CM).Main Outcomes and Measures: Fatal and nonfatal overdoses and deaths throughout 5 years, discounted lifetime quality-adjusted life-years (QALYs), and costs.Results: In the base case, in the absence of treatment, 42 717 overdoses (4132 fatal, 38 585 nonfatal) and 12 660 deaths were estimated to occur in a cohort of 100 000 patients over 5 years, and 11.58 discounted lifetime QALYs were estimated to be experienced per person. An estimated reduction in overdoses was associated with MAT with methadone (10.7%), MAT with buprenorphine or naltrexone (22.0%), and when combined with CM and psychotherapy (range, 21.0%-31.4%). Estimated deceased deaths were associated with MAT with methadone (6%), MAT with buprenorphine or naltrexone (13.9%), and when combined with CM, OEND, and psychotherapy (16.9%). MAT yielded discounted gains of 1.02 to 1.07 QALYs per person. Including only health care sector costs, methadone cost $16 000/QALY gained compared with no treatment, followed by methadone with OEND ($22 000/QALY gained), then by buprenorphine with OEND and CM ($42 000/QALY gained), and then by buprenorphine with OEND, CM, and psychotherapy ($250 000/QALY gained). MAT with naltrexone was dominated by other treatment alternatives. When criminal justice costs were included, all forms of MAT (with buprenorphine, methadone, and naltrexone) were associated with cost savings compared with no treatment, yielding savings of $25 000 to $105 000 in lifetime costs per person. The largest cost savings were associated with methadone plus CM. Results were qualitatively unchanged over a wide range of sensitivity analyses. An analysis using demographic and cost data for Veterans Health Administration patients yielded similar findings.Conclusions and Relevance: In this cost-effectiveness analysis, expanded access to MAT, combined with OEND and CM, was associated with cost-saving reductions in morbidity and mortality from OUD. Lack of widespread MAT availability limits access to a cost-saving medical intervention that reduces morbidity and mortality from OUD. Opioid overdoses in the US likely reached a record high in 2020 because of COVID-19 increasing substance use, exacerbating stress and social isolation, and interfering with opioid treatment. It is essential to understand the cost-effectiveness of alternative forms of MAT to treat OUD.
View details for DOI 10.1001/jamapsychiatry.2021.0247
View details for PubMedID 33787832
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Optimal portfolios of blood safety interventions: test, defer or modify?
Health care management science
2021
Abstract
A safe supply of blood for transfusion is a critical component of the healthcare system in all countries. Most health systems manage the risk of transfusion-transmissible infections (TTIs) through a portfolio of blood safety interventions. These portfolios must be updated periodically to reflect shifting epidemiological conditions, emerging infectious diseases, and new technologies. However, the number of available blood safety portfolios grows exponentially with the number of available interventions, making it impossible for policymakers to evaluate all feasible portfolios without the assistance of a computer model. We develop a novel optimization model for evaluating blood safety portfolios that enables systematic comparison of all feasible portfolios of deferral, testing, and modification interventions to identify the portfolio that is preferred from a cost-utility perspective. We present structural properties that reduce the state space and required computation time in certain cases, and we develop a linear approximation of the model. We apply the model to retrospectively evaluate U.S. blood safety policies for Zika and West Nile virus for the years 2017, 2018, and 2019, defining donor groups based on season and geography. We leverage structural properties to efficiently find an optimal solution. We find that the optimal portfolio varies geographically, seasonally, and over time. Additionally, we show that for this problem the approximated model yields the same optimal solution as the exact model. Our method enables systematic identification of the optimal blood safety portfolio in any setting and any time period, thereby supporting decision makers in efforts to ensure the safety of the blood supply.
View details for DOI 10.1007/s10729-021-09557-1
View details for PubMedID 33666808
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Effectiveness of interventions to reduce COVID-19 transmission in a large urban jail: a model-based analysis.
BMJ open
2021; 11 (2): e042898
Abstract
OBJECTIVES: We aim to estimate the impact of various mitigation strategies on COVID-19 transmission in a US jail beyond those offered in national guidelines.DESIGN: We developed a stochastic dynamic transmission model of COVID-19.SETTING: One anonymous large urban US jail.PARTICIPANTS: Several thousand staff and incarcerated individuals.INTERVENTIONS: There were four intervention phases during the outbreak: the start of the outbreak, depopulation of the jail, increased proportion of people in single cells and asymptomatic testing. These interventions were implemented incrementally and in concert with one another.PRIMARY AND SECONDARY OUTCOME MEASURES: The basic reproduction ratio, R 0 , in each phase, as estimated using the next generation method. The fraction of new cases, hospitalisations and deaths averted by these interventions (along with the standard measures of sanitisation, masking and social distancing interventions).RESULTS: For the first outbreak phase, the estimated R 0 was 8.44 (95% credible interval (CrI): 5.00 to 13.10), and for the subsequent phases, R 0,phase 2 =3.64 (95% CrI: 2.43 to 5.11), R 0,phase 3 =1.72 (95% CrI: 1.40 to 2.12) and R 0,phase 4 =0.58 (95% CrI: 0.43 to 0.75). In total, the jail's interventions prevented approximately 83% of projected cases, hospitalisations and deaths over 83 days.CONCLUSIONS: Depopulation, single celling and asymptomatic testing within jails can be effective strategies to mitigate COVID-19 transmission in addition to standard public health measures. Decision makers should prioritise reductions in the jail population, single celling and testing asymptomatic populations as additional measures to manage COVID-19 within correctional settings.
View details for DOI 10.1136/bmjopen-2020-042898
View details for PubMedID 33597139
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Optimal allocation of limited vaccine to minimize the effective reproduction number.
Mathematical biosciences
2021: 108654
Abstract
We examine the problem of allocating a limited supply of vaccine for controlling an infectious disease with the goal of minimizing the effective reproduction number Re. We consider an SIR model with two interacting populations and develop an analytical expression that the optimal vaccine allocation must satisfy. With limited vaccine supplies, we find that an all-or-nothing approach is optimal. For certain special cases, we determine the conditions under which the optimal Re is below 1. We present an example of vaccine allocation for COVID-19 and show that it is optimal to vaccinate younger individuals before older individuals to minimize Re if less than 59% of the population can be vaccinated. The analytical conditions we develop provide a simple means of determining the optimal allocation of vaccine between two population groups to minimize Re.
View details for DOI 10.1016/j.mbs.2021.108654
View details for PubMedID 34216636
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Early detection of COVID-19 outbreaks using human mobility data.
PloS one
2021; 16 (7): e0253865
Abstract
Contact mixing plays a key role in the spread of COVID-19. Thus, mobility restrictions of varying degrees up to and including nationwide lockdowns have been implemented in over 200 countries. To appropriately target the timing, location, and severity of measures intended to encourage social distancing at a country level, it is essential to predict when and where outbreaks will occur, and how widespread they will be.We analyze aggregated, anonymized health data and cell phone mobility data from Israel. We develop predictive models for daily new cases and the test positivity rate over the next 7 days for different geographic regions in Israel. We evaluate model goodness of fit using root mean squared error (RMSE). We use these predictions in a five-tier categorization scheme to predict the severity of COVID-19 in each region over the next week. We measure magnitude accuracy (MA), the extent to which the correct severity tier is predicted.Models using mobility data outperformed models that did not use mobility data, reducing RMSE by 17.3% when predicting new cases and by 10.2% when predicting the test positivity rate. The best set of predictors for new cases consisted of 1-day lag of past 7-day average new cases, along with a measure of internal movement within a region. The best set of predictors for the test positivity rate consisted of 3-days lag of past 7-day average test positivity rate, along with the same measure of internal movement. Using these predictors, RMSE was 4.812 cases per 100,000 people when predicting new cases and 0.79% when predicting the test positivity rate. MA in predicting new cases was 0.775, and accuracy of prediction to within one tier was 1.0. MA in predicting the test positivity rate was 0.820, and accuracy to within one tier was 0.998.Using anonymized, macro-level data human mobility data along with health data aids predictions of when and where COVID-19 outbreaks are likely to occur. Our method provides a useful tool for government decision makers, particularly in the post-vaccination era, when focused interventions are needed to contain COVID-19 outbreaks while mitigating the collateral damage from more global restrictions.
View details for DOI 10.1371/journal.pone.0253865
View details for PubMedID 34283839
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Health outcomes and cost-effectiveness of diversion programs for low-level drug offenders: A model-based analysis.
PLoS medicine
2020; 17 (10): e1003239
Abstract
BACKGROUND: Cycles of incarceration, drug abuse, and poverty undermine ongoing public health efforts to reduce overdose deaths and the spread of infectious disease in vulnerable populations. Jail diversion programs aim to divert low-level drug offenders toward community care resources, avoiding criminal justice costs and disruptions in treatment for HIV, hepatitis C virus (HCV), and drug abuse. We sought to assess the health benefits and cost-effectiveness of a jail diversion program for low-level drug offenders.METHODS AND FINDINGS: We developed a microsimulation model, calibrated to King County, Washington, that captured the spread of HIV and HCV infections and incarceration and treatment systems as well as preexisting interventions such as needle and syringe programs and opiate agonist therapy. We considered an adult population of people who inject drugs (PWID), people who use drugs but do not inject (PWUD), men who have sex with men, and lower-risk heterosexuals. We projected discounted lifetime costs and quality-adjusted life years (QALYs) over a 10-year time horizon with and without a jail diversion program and calculated resulting incremental cost-effectiveness ratios (ICERs) from the health system and societal perspectives. We also tracked HIV and HCV infections, overdose deaths, and jail population size. Over 10 years, the program was estimated to reduce HIV and HCV incidence by 3.4% (95% CI 2.7%-4.0%) and 3.3% (95% CI 3.1%-3.4%), respectively, overdose deaths among PWID by 10.0% (95% CI 9.8%-10.8%), and jail population size by 6.3% (95% CI 5.9%-6.7%). When considering healthcare costs only, the program cost $25,500/QALY gained (95% CI $12,600-$48,600). Including savings from reduced incarceration (societal perspective) improved the ICER to $6,200/QALY gained (95% CI, cost-saving $24,300). Sensitivity analysis indicated that cost-effectiveness depends on diversion program participants accessing community programs such as needle and syringe programs, treatment for substance use disorder, and HIV and HCV treatment, as well as diversion program cost. A limitation of the analysis is data availability, as fewer data are available for diversion programs than for more established interventions aimed at people with substance use disorder. Additionally, like any model of a complex system, our model relies on simplifying assumptions: For example, we simplified pathways in the healthcare and criminal justice systems, modeled an average efficacy for substance use disorder treatment, and did not include costs associated with homelessness, unemployment, and breakdown in family structure.CONCLUSIONS: We found that diversion programs for low-level drug offenders are likely to be cost-effective, generating savings in the criminal justice system while only moderately increasing healthcare costs. Such programs can reduce incarceration and its associated costs, and also avert overdose deaths and improve quality of life for PWID, PWUD, and the broader population (through reduced HIV and HCV transmission).
View details for DOI 10.1371/journal.pmed.1003239
View details for PubMedID 33048929
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Optimizing interventions across the HIV care continuum: A case study using process improvement analysis
OPERATIONS RESEARCH FOR HEALTH CARE
2020; 25
View details for DOI 10.1016/j.orhc.2020.100258
View details for Web of Science ID 000550215300001
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Optimizing Interventions Across the HIV Care Continuum: A Case Study Using Process Improvement Analysis.
Operations research for health care
2020; 25
Abstract
UNAIDS' 90-90-90 goal for 2020 is for 90% of HIV-infected people to know their status, 90% of infected individuals to receive antiretroviral therapy (ART), and 90% of those on ART to achieve viral suppression. To achieve these ambitious goals, effective care delivery programs are needed. In this paper we present a case study showing how HIV care can be improved by viewing the patient care process as a production process and applying methods of process improvement analysis. We examine the continuum of HIV care at a hospital-based HIV clinic in Kingston, Jamaica. We perform qualitative analysis to identify key programmatic, personnel, and clinical areas for process improvement. We then perform quantitative analysis. We develop a stochastic model of the care process which we use to evaluate the effects of potential process improvements on the number of patients who receive ART and the number who achieve viral suppression. We also develop a model for optimal investment of a fixed budget among interventions aimed at improving the care cascade and we use the model to determine the optimal investment among three interventions that the clinic could invest in. By viewing the patient care process as a production process and applying qualitative and quantitative process improvement analysis, our case study illustrates how clinics can identify the best ways to maximize clinical outcomes. Our methods are generalizable to other HIV care clinics as well as to clinics that provide care for other chronic conditions (e.g., diabetes, hepatitis B, or opioid use disorder).
View details for DOI 10.1016/j.orhc.2020.100258
View details for PubMedID 33014699
View details for PubMedCentralID PMC7528976
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Implementing Analytics Projects in a Hospital: Successes, Failures, and Opportunities
INTERFACES
2020; 50 (3): 176–89
View details for DOI 10.1287/inte.2020.1036
View details for Web of Science ID 000574663800003
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PREVENTION AND CONTROL OF DENGUE AND CHIKUNGUNYA IN COLOMBIA: A COST-EFFECTIVENESS ANALYSIS
SAGE PUBLICATIONS INC. 2020: E85–E87
View details for Web of Science ID 000509275600080
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Estimation of COVID-19 Basic Reproduction Ratio in a Large Urban Jail in the United States.
Annals of epidemiology
2020
View details for DOI 10.1016/j.annepidem.2020.09.002
View details for PubMedID 32919033
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Predicting and improving patient-level antibiotic adherence.
Health care management science
2020
Abstract
Low adherence to prescribed medications causes substantial health and economic burden. We analyzed primary data from electronic medical records of 250,000 random patients from Israel's Maccabi Healthcare services from 2007 to 2017 to predict whether a patient will purchase a prescribed antibiotic. We developed a decision model to evaluate whether an intervention to improve purchasing adherence is warranted for the patient, considering the cost of the intervention and the cost of non-adherence. The best performing prediction model achieved an average area under the receiver operating characteristic curve (AUC) of 0.684, with 82% accuracy in detecting individuals who had less than 50% chance of purchasing a prescribed drug. Using the decision model, an adherence intervention targeted to patients whose predicted purchasing probability is below a specified threshold can increase the number of prescriptions filled while generating significant savings compared to no intervention - on the order of 6.4% savings and 4.0% more prescriptions filled for our dataset. We conclude that analysis of large-scale patient data from electronic medical records can help predict the probability that a patient will purchase a prescribed antibiotic and can provide real-time predictions to physicians, who can then counsel the patient about medication importance. More broadly, in-depth analysis of patient-level data can help shape the next generation of personalized interventions.
View details for DOI 10.1007/s10729-020-09523-3
View details for PubMedID 33017035
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Public Health Interventions with Harms and Benefits: A Graphical Framework for Evaluating Tradeoffs.
Medical decision making : an international journal of the Society for Medical Decision Making
2020: 272989X20960458
Abstract
Evaluations of public health interventions typically report benefits and harms aggregated over the population. However, benefits and harms are not always evenly distributed. Examining disaggregated outcomes enables decision makers to consider health benefits and harms accruing to both intended intervention recipients and others in the population.We provide a graphical framework for categorizing and comparing public health interventions that examines the distribution of benefit and harm between and within population subgroups for a single intervention and compares distributions of harm and benefit for multiple interventions. We demonstrate the framework through a case study of a hypothetical increase in the price of meat (5%, 10%, 25%, or 50%) that, via elasticity of demand, reduces consumption and consequently reduces body mass index. We examine how inequalities in benefits and harms (measured by quality-adjusted life-years) are distributed across a population of white and black males and females.A 50% meat price increase would yield the greatest net benefit to the population. However, because of reduced consumption among low-weight individuals, black males would bear disproportionate harm relative to the benefit they receive. With increasing meat price, the distribution of harm relative to benefit becomes less "internal" to those receiving benefit and more "distributed" to those not receiving commensurate benefit. When we segment the population by sex only, this result does not hold.Disaggregating harms and benefits to understand their differential impact on subgroups can strongly affect which decision alternative is deemed optimal, as can the approach to segmenting the population. Our framework provides a useful tool for illuminating key tradeoffs relevant to harm-averse decision makers and those concerned with both equity and efficiency.
View details for DOI 10.1177/0272989X20960458
View details for PubMedID 32996356
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Health outcomes and cost-effectiveness of treating depression in people with HIV in Sub-Saharan Africa: a model-based analysis.
AIDS care
2020: 1–7
Abstract
High prevalence of depression among people living with HIV (PLHIV) impedes antiretroviral therapy (ART) adherence and viral suppression. We estimate the effectiveness and cost-effectiveness of strategies to treat depression among PLHIV in Sub-Saharan Africa (SSA). We developed a microsimulation model of HIV disease and care in Uganda which captured individuals' depression status and the relationship between depression and HIV behaviors. We consider a strategy of screening for depression and providing antidepressant therapy with fluoxetine at ART initiation or re-initiation (if a patient has dropped out). We estimate that over 10 years this strategy would reduce prevalence of depression among PLHIV by 16.0% [95% uncertainty bounds 15.8%, 16.1%] from a baseline prevalence of 28%, increase adherence to ART by 1.0% [1.0%, 1.0%], and decrease rates of loss to followup by 3.7% [3.4%, 4.1%]. This would decrease first-line ART failure rates by 2.5% [2.3%, 2.8%] and increase viral suppression rates by 1.0% [1.0%, 1.0%]. This strategy costs $15/QALY compared to the status quo, and was highly cost-effective over a broad range of sensitivity analyses. We conclude that screening for and treating depression among PLHIV in SSA with fluoxetine would be effective in improving HIV treatment outcomes and would be highly cost-effective.
View details for DOI 10.1080/09540121.2020.1719966
View details for PubMedID 31986900
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PREDICTING THE EFFECTIVENESS OF INTERVENTIONS FOR INFECTIOUS DISEASE CONTROL: THE ROLE OF MODEL STRUCTURE
SAGE PUBLICATIONS INC. 2020: E377
View details for Web of Science ID 000509275600314
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DIVERSION PROGRAMS FOR LOW-LEVEL DRUG OFFENDERS: HEALTH OUTCOMES AND COST-EFFECTIVENESS
SAGE PUBLICATIONS INC. 2020: E374
View details for Web of Science ID 000509275600311
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PREDICTING THE EFFECTIVENESS OF INTERVENTIONS FOR INFECTIOUS DISEASE CONTROL: THE ROLE OF MODEL STRUCTURE
SAGE PUBLICATIONS INC. 2020: E118
View details for Web of Science ID 000509275600105
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META-MODELLING FOR POLICY SIMULATIONS WITH MULTIVARIATE OUTCOMES
SAGE PUBLICATIONS INC. 2020: E69–E70
View details for Web of Science ID 000509275600068
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PREDICTING PATIENT-LEVEL ANTIBIOTIC ADHERENCE
SAGE PUBLICATIONS INC. 2020: E45–E46
View details for Web of Science ID 000509275600049
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COST-EFFECTIVENESS OF INTERVENTIONS TO PREVENT PLAGUE IN MADAGASCAR
SAGE PUBLICATIONS INC. 2020: E116–E117
View details for Web of Science ID 000509275600104
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Improving the efficiency of the operating room environment with an optimization and machine learning model
HEALTH CARE MANAGEMENT SCIENCE
2019; 22 (4): 756–67
View details for DOI 10.1007/s10729-018-9457-3
View details for Web of Science ID 000495243200010
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Personalizing Medical Treatment Decisions: Integrating Meta-Analytic Treatment Comparisons with Patient-Specific Risks and Preferences.
Medical decision making : an international journal of the Society for Medical Decision Making
2019: 272989X19884927
Abstract
Background. Network meta-analyses (NMAs) that compare treatments for a given condition allow physicians to identify which treatments have higher or lower probabilities of reducing the risks of disease complications or increasing the risks of treatment side effects. Translating these data into personalized treatment plans requires integration of NMA data with patient-specific pretreatment risk estimates and preferences regarding treatment objectives and acceptable risks. Methods. We introduce a modeling framework to integrate data probabilistically from NMAs with data on individualized patient risk estimates for disease outcomes, treatment preferences (such as willingness to incur greater side effects for increased life expectancy), and risk preferences. We illustrate the modeling framework by creating personalized plans for antipsychotic drug treatment and evaluating their effectiveness and cost-effectiveness. Results. Compared with treating all patients with the drug that yields the greatest quality-adjusted life-years (QALYs) on average (amisulpride), personalizing the selection of antipsychotic drugs for schizophrenia patients over the next 5 years would be expected to yield 0.33 QALYs (95% credible interval [crI]: 0.30-0.37) per patient at an incremental cost of $4849/QALY gained (95% crI: dominant-$12,357), versus 0.29 and 0.04 QALYs per patient when accounting for only risks or preferences, respectively, but not both. Limitations. The analysis uses a linear, additive utility function to reflect patient treatment preferences and does not consider potential variations in patient time discounting. Conclusions. Our modeling framework rigorously computes what physicians normally have to do mentally. By integrating 3 key components of personalized medicine-evidence on efficacy, patient risks, and patient preferences-the modeling framework can provide personalized treatment decisions to improve patient health outcomes.
View details for DOI 10.1177/0272989X19884927
View details for PubMedID 31707910
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Quantifying Positive Health Externalities of Disease Control Interventions: Modeling Chikungunya and Dengue.
Medical decision making : an international journal of the Society for Medical Decision Making
2019: 272989X19880554
Abstract
Purpose. Health interventions can generate positive externalities not captured in traditional, single-disease cost-effectiveness analyses (CEAs), potentially biasing results. We illustrate this with the example of mosquito-borne diseases. When a particular mosquito species can transmit multiple diseases, a single-disease CEA comparing disease-specific interventions (e.g., vaccination) with interventions targeting the mosquito population (e.g., insecticide) would underestimate the insecticide's full benefits (i.e., preventing other diseases). Methods. We developed three dynamic transmission models: chikungunya, dengue, and combined chikungunya and dengue, each calibrated to disease-specific incidence and deaths in Colombia (June 2014 to December 2017). We compared the models' predictions of the incremental benefits and cost-effectiveness of an insecticide (10% efficacy), hypothetical chikungunya and dengue vaccines (40% coverage, 95% efficacy), and combinations of these interventions. Results. Model calibration yielded realistic parameters that produced close matches to disease-specific incidence and deaths. The chikungunya model predicted that vaccine would decrease the incidence of chikungunya and avert more total deaths than insecticide. The dengue model predicted that insecticide and the dengue vaccine would reduce dengue incidence and deaths, with no effect for the chikungunya vaccine. In the combined model, insecticide was more effective than either vaccine in reducing the incidence of and deaths from both diseases. In all models, the combined strategy was at least as effective as the most effective single strategy. In an illustrative CEA, the most frequently preferred strategy was vaccine in the chikungunya model, the status quo in the dengue model, and insecticide in the combined model. Limitations. There is uncertainty in the target calibration data. Conclusions. Failure to capture positive externalities can bias CEA results, especially when evaluating interventions that affect multiple diseases. Multidisease modeling is a reasonable alternative for addressing such biases.
View details for DOI 10.1177/0272989X19880554
View details for PubMedID 31642362
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A modified HIV continuum of care: A six-year evaluation of a viral load cascade at a hospital-based clinic in Kingston, Jamaica
INTERNATIONAL JOURNAL OF STD & AIDS
2019; 30 (8): 748–55
View details for DOI 10.1177/0956462419839514
View details for Web of Science ID 000476522800003
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OR Forum-Public Health Preparedness: Answering (Largely Unanswerable) Questions with Operations Research-The 2016-2017 Philip McCord Morse Lecture
OPERATIONS RESEARCH
2019; 67 (3): 700–710
View details for DOI 10.1287/opre.2019.1844
View details for Web of Science ID 000470860200005
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A modified HIV continuum of care: A six-year evaluation of a viral load cascade at a hospital-based clinic in Kingston, Jamaica.
International journal of STD & AIDS
2019: 956462419839514
Abstract
To achieve the goal of HIV viral suppression, provision of medication alone is not sufficient. Concomitant frameworks to evaluate HIV care delivery programmes are needed. This study examined the care continuum at a hospital-based HIV clinic in Kingston, Jamaica using a modified HIV continuum of care, with an increased focus on viral load indicators (viral load samples taken, results returned and viral suppression). A statistical analysis of patient flow through the care continuum to identify gaps in programme delivery was performed. Key programmatic areas for process improvement and the utility of this approach for viral load suppression interpretation were identified. Between 2010 and 2015, more than 1600 patients had been registered for care and more than 1000 had accessed antiretroviral therapy at this location. Consistent trends in programme performance were seen from 2010 to 2012. Although declines in the proportion of viral load samples taken and results returned occurred because of laboratory failures in 2013, the trend of increasing numbers and proportions of virally suppressed patients continued. Statistical analysis indicated that improvements in laboratory quality (fraction of viral load samples returned with accurate test results) could increase viral load suppression among patients at the clinic by up to 17%. Refining care delivery processes can significantly improve HIV viral load suppression rates. Expanding monitoring frameworks to include all of the essential processes that affect final outcome indicators can provide valuable insight into trends of outcome indicators and programme performance.
View details for PubMedID 31072281
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Optimal timing of drug sensitivity testing for patients on first-line tuberculosis treatment
HEALTH CARE MANAGEMENT SCIENCE
2018; 21 (4): 632–46
Abstract
Effective treatment for tuberculosis (TB) patients on first-line treatment involves triaging those with drug-resistant (DR) TB to appropriate treatment alternatives. Patients likely to have DR TB are identified using results from repeated inexpensive sputum-smear (SS) tests and expensive but definitive drug sensitivity tests (DST). Early DST may lead to high costs and unnecessary testing; late DST may lead to poor health outcomes and disease transmission. We use a partially observable Markov decision process (POMDP) framework to determine optimal DST timing. We develop policy-relevant structural properties of the POMDP model. We apply our model to TB in India to identify the patterns of SS test results that should prompt DST if transmission costs remain at status-quo levels. Unlike previous analyses of personalized treatment policies, we take a societal perspective and consider the effects of disease transmission. The inclusion of such effects can significantly alter the optimal policy. We find that an optimal DST policy could save India approximately $1.9 billion annually.
View details for PubMedID 28861650
View details for PubMedCentralID PMC5832607
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Improving the efficiency of the operating room environment with an optimization and machine learning model.
Health care management science
2018
Abstract
The operating room is a major cost and revenue center for most hospitals. Thus, more effective operating room management and scheduling can provide significant benefits. In many hospitals, the post-anesthesia care unit (PACU), where patients recover after their surgical procedures, is a bottleneck. If the PACU reaches capacity, patients must wait in the operating room until the PACU has available space, leading to delays and possible cancellations for subsequent operating room procedures. We develop a generalizable optimization and machine learning approach to sequence operating room procedures to minimize delays caused by PACU unavailability. Specifically, we use machine learning to estimate the required PACU time for each type of surgical procedure, we develop and solve two integer programming models to schedule procedures in the operating rooms to minimize maximum PACU occupancy, and we use discrete event simulation to compare our optimized schedule to the existing schedule. Using data from Lucile Packard Children's Hospital Stanford, we show that the scheduling system can significantly reduce operating room delays caused by PACU congestion while still keeping operating room utilization high: simulation of the second half of 2016 shows that our model could have reduced total PACU holds by 76% without decreasing operating room utilization. We are currently working on implementing the scheduling system at the hospital.
View details for PubMedID 30387040
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Modeling Health Benefis and Harms of Public Policy Responses to the US Opioid Epidemic
AMERICAN JOURNAL OF PUBLIC HEALTH
2018; 108 (10): 1394-1400
View details for DOI 10.2105/AJPH.2018.304590
View details for Web of Science ID 000444410800048
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Modeling Health Benefits and Harms of Public Policy Responses to the US Opioid Epidemic.
American journal of public health
2018: e1–e7
Abstract
OBJECTIVES: To estimate health outcomes of policies to mitigate the opioid epidemic.METHODS: We used dynamic compartmental modeling of US adults, in various pain, opioid use, and opioid addiction health states, to project addiction-related deaths, life years, and quality-adjusted life years from 2016 to 2025 for 11 policy responses to the opioid epidemic.RESULTS: Over 5 years, increasing naloxone availability, promoting needle exchange, expanding medication-assisted addiction treatment, and increasing psychosocial treatment increased life years and quality-adjusted life years and reduced deaths. Other policies reduced opioid prescription supply and related deaths but led some addicted prescription users to switch to heroin use, which increased heroin-related deaths. Over a longer horizon, some such policies may avert enough new addiction to outweigh the harms. No single policy is likely to substantially reduce deaths over 5 to 10 years.CONCLUSIONS: Policies focused on services for addicted people improve population health without harming any groups. Policies that reduce the prescription opioid supply may increase heroin use and reduce quality of life in the short term, but in the long term could generate positive health benefits. A portfolio of interventions will be needed for eventual mitigation. (Am J Public Health. Published online ahead of print August 23, 2018: e1-e7. doi:10.2105/AJPH.2018.304590).
View details for PubMedID 30138057
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Dynamic Learning of Patient Response Types: An Application to Treating Chronic Diseases
MANAGEMENT SCIENCE
2018; 64 (8): 3469–88
View details for DOI 10.1287/mnsc.2017.2793
View details for Web of Science ID 000440922200001
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Dynamic Learning of Patient Response Types: An Application to Treating Chronic Diseases.
Management science
2018; 64 (8): 3469-3970
Abstract
Currently available medication for treating many chronic diseases is often effective only for a subgroup of patients, and biomarkers accurately assessing whether an individual belongs to this subgroup typically do not exist. In such settings, physicians learn about the effectiveness of a drug primarily through experimentation, i.e., by initiating treatment and monitoring the patient's response. Precise guidelines for discontinuing treatment are often lacking or left entirely to the physician's discretion. We introduce a framework for developing adaptive, personalized treatments for such chronic diseases. Our model is based on a continuous-time, multi-armed bandit setting where drug effectiveness is assessed by aggregating information from several channels: by continuously monitoring the state of the patient, but also by (not) observing the occurrence of particular infrequent health events, such as relapses or disease flare-ups. Recognizing that the timing and severity of such events provides critical information for treatment decisions is a key point of departure in our framework compared with typical (bandit) models used in healthcare. We show that the model can be analyzed in closed form for several settings of interest, resulting in optimal policies that are intuitive and may have practical appeal. We illustrate the effectiveness of the methodology by developing a set of efficient treatment policies for multiple sclerosis, which we then use to benchmark several existing treatment guidelines.
View details for DOI 10.1287/mnsc.2017.2793
View details for PubMedID 30344343
View details for PubMedCentralID PMC6193506
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Anticipated burden and mitigation of carbon-dioxide-induced nutritional deficiencies and related diseases: A simulation modeling study.
PLoS medicine
2018; 15 (7): e1002586
Abstract
BACKGROUND: Rising atmospheric carbon dioxide concentrations are anticipated to decrease the zinc and iron concentrations of crops. The associated disease burden and optimal mitigation strategies remain unknown. We sought to understand where and to what extent increasing carbon dioxide concentrations may increase the global burden of nutritional deficiencies through changes in crop nutrient concentrations, and the effects of potential mitigation strategies.METHODS AND FINDINGS: For each of 137 countries, we incorporated estimates of climate change, crop nutrient concentrations, dietary patterns, and disease risk into a microsimulation model of zinc and iron deficiency. These estimates were obtained from the Intergovernmental Panel on Climate Change, US Department of Agriculture, Statistics Division of the Food and Agriculture Organization of the United Nations, and Global Burden of Disease Project, respectively. In the absence of increasing carbon dioxide concentrations, we estimated that zinc and iron deficiencies would induce 1,072.9 million disability-adjusted life years (DALYs) globally over the period 2015 to 2050 (95% credible interval [CrI]: 971.1-1,167.7). In the presence of increasing carbon dioxide concentrations, we estimated that decreasing zinc and iron concentrations of crops would induce an additional 125.8 million DALYs globally over the same period (95% CrI: 113.6-138.9). This carbon-dioxide-induced disease burden is projected to disproportionately affect nations in the World Health Organization's South-East Asia and African Regions (44.0 and 28.5 million DALYs, respectively), which already have high existing disease burdens from zinc and iron deficiencies (364.3 and 299.5 million DALYs, respectively), increasing global nutritional inequalities. A climate mitigation strategy such as the Paris Agreement (an international agreement to keep global temperatures within 2°C of pre-industrial levels) would be expected to avert 48.2% of this burden (95% CrI: 47.8%-48.5%), while traditional public health interventions including nutrient supplementation and disease control programs would be expected to avert 26.6% of the burden (95% CrI: 23.8%-29.6%). Of the traditional public health interventions, zinc supplementation would be expected to avert 5.5%, iron supplementation 15.7%, malaria mitigation 3.2%, pneumonia mitigation 1.6%, and diarrhea mitigation 0.5%. The primary limitations of the analysis include uncertainty regarding how food consumption patterns may change with climate, how disease mortality rates will change over time, and how crop zinc and iron concentrations will decline from those at present to those in 2050.CONCLUSIONS: Effects of increased carbon dioxide on crop nutrient concentrations are anticipated to exacerbate inequalities in zinc and iron deficiencies by 2050. Proposed Paris Agreement strategies are expected to be more effective than traditional public health measures to avert the increased inequality.
View details for PubMedID 29969442
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Anticipated burden and mitigation of carbondioxide-induced nutritional deficiencies and related diseases: A simulation modeling study
PLOS MEDICINE
2018; 15 (7)
View details for DOI 10.1371/journal.pmed.1002586
View details for Web of Science ID 000440339700001
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Cost-effectiveness of alternative strategies for provision of HIV preexposure prophylaxis for people who inject drugs
AIDS
2018; 32 (5): 663–72
Abstract
Oral HIV preexposure prophylaxis (PrEP) has been recommended as a means of HIV prevention among people who inject drugs (PWIDs) but, at current prices, is unlikely to be cost-effective for all PWID.To determine the cost-effectiveness of alternative strategies for enrolling PWID in PrEP.Dynamic network model that captures HIV transmission and progression among PWID in a representative US urban center.HIV infections averted, discounted costs and quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios.We assume 25% PrEP coverage and investigate four strategies: first, random PWID are enrolled (Unselected Enrollment); second, individuals are randomly selected and enrolled together with their partners (Enroll Partners); third, individuals with the highest number of sexual and needle-sharing partnerships are enrolled (Most Partners); fourth, individuals with the greatest number of infected partners are enrolled (Most Positive Partners).PrEP can achieve significant health benefits: compared with the status quo of no PrEP, the strategies gain 1114 QALYs (Unselected Enrollment), 2194 QALYs (Enroll Partners), 2481 QALYs (Most Partners), and 3046 QALYs (Most Positive Partners) over 20 years in a population of approximately 8500 people. The incremental cost-effectiveness ratio of each strategy compared with the status quo (cost per QALY gained) is $272 000 (Unselected Enrollment), $158 000 (Enroll Partners), $124 000 (Most Partners), and $101 000 (Most Positive Partners). All strategies except Unselected Enrollment are cost-effective according to WHO criteria.Selection of high-risk PWID for PrEP can improve the cost-effectiveness of PrEP for PWID.
View details for PubMedID 29334549
View details for PubMedCentralID PMC5906044
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Dynamic treatment selection and modification for personalised blood pressure therapy using a Markov decision process model: a cost-effectiveness analysis
BMJ OPEN
2017; 7 (11)
View details for DOI 10.1136/bmjopen-2017-018374
View details for Web of Science ID 000422898800200
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Structural Sensitivity in HIV Modeling: A Case Study of Vaccination.
Infectious Disease Modelling
2017; 2 (4): 399–411
Abstract
Structural assumptions in infectious disease models, such as the choice of network or compartmental model type or the inclusion of different types of heterogeneity across individuals, might affect model predictions as much as or more than the choice of input parameters. We explore the potential implications of structural assumptions on HIV model predictions and policy conclusions. We illustrate the value of inference robustness assessment through a case study of the effects of a hypothetical HIV vaccine in multiple population subgroups over eight related transmission models, which we sequentially modify to vary over two dimensions: parameter complexity (e.g., the inclusion of age and HCV comorbidity) and contact/simulation complexity (e.g., aggregated compartmental vs. individual/disaggregated compartmental vs. network models). We find that estimates of HIV incidence reductions from network models and individual compartmental models vary, but those differences are overwhelmed by the differences in HIV incidence between such models and the aggregated compartmental models (which aggregate groups of individuals into compartments). Complexities such as age structure appear to buffer the effects of aggregation and increase the threshold of net vaccine effectiveness at which aggregated models begin to overestimate reductions. The differences introduced by parameter complexity in estimated incidence reduction also translate into substantial differences in cost-effectiveness estimates. Parameter complexity does not appear to play a consistent role in differentiating the projections of network models.
View details for PubMedID 29532039
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Estimation of the cost-effectiveness of HIV prevention portfolios for people who inject drugs in the United States: A model-based analysis.
PLoS medicine
2017; 14 (5)
Abstract
The risks of HIV transmission associated with the opioid epidemic make cost-effective programs for people who inject drugs (PWID) a public health priority. Some of these programs have benefits beyond prevention of HIV-a critical consideration given that injection drug use is increasing across most United States demographic groups. To identify high-value HIV prevention program portfolios for US PWID, we consider combinations of four interventions with demonstrated efficacy: opioid agonist therapy (OAT), needle and syringe programs (NSPs), HIV testing and treatment (Test & Treat), and oral HIV pre-exposure prophylaxis (PrEP).We adapted an empirically calibrated dynamic compartmental model and used it to assess the discounted costs (in 2015 US dollars), health outcomes (HIV infections averted, change in HIV prevalence, and discounted quality-adjusted life years [QALYs]), and incremental cost-effectiveness ratios (ICERs) of the four prevention programs, considered singly and in combination over a 20-y time horizon. We obtained epidemiologic, economic, and health utility parameter estimates from the literature, previously published models, and expert opinion. We estimate that expansions of OAT, NSPs, and Test & Treat implemented singly up to 50% coverage levels can be cost-effective relative to the next highest coverage level (low, medium, and high at 40%, 45%, and 50%, respectively) and that OAT, which we assume to have immediate and direct health benefits for the individual, has the potential to be the highest value investment, even under scenarios where it prevents fewer infections than other programs. Although a model-based analysis can provide only estimates of health outcomes, we project that, over 20 y, 50% coverage with OAT could avert up to 22,000 (95% CI: 5,200, 46,000) infections and cost US$18,000 (95% CI: US$14,000, US$24,000) per QALY gained, 50% NSP coverage could avert up to 35,000 (95% CI: 8,900, 43,000) infections and cost US$25,000 (95% CI: US$7,000, US$76,000) per QALY gained, 50% Test & Treat coverage could avert up to 6,700 (95% CI: 1,200, 16,000) infections and cost US$27,000 (95% CI: US$15,000, US$48,000) per QALY gained, and 50% PrEP coverage could avert up to 37,000 (22,000, 58,000) infections and cost US$300,000 (95% CI: US$162,000, US$667,000) per QALY gained. When coverage expansions are allowed to include combined investment with other programs and are compared to the next best intervention, the model projects that scaling OAT coverage up to 50%, then scaling NSP coverage to 50%, then scaling Test & Treat coverage to 50% can be cost-effective, with each coverage expansion having the potential to cost less than US$50,000 per QALY gained relative to the next best portfolio. In probabilistic sensitivity analyses, 59% of portfolios prioritized the addition of OAT and 41% prioritized the addition of NSPs, while PrEP was not likely to be a priority nor a cost-effective addition. Our findings are intended to be illustrative, as data on achievable coverage are limited and, in practice, the expansion scenarios considered may exceed feasible levels. We assumed independence of interventions and constant returns to scale. Extensive sensitivity analyses allowed us to assess parameter sensitivity, but the use of a dynamic compartmental model limited the exploration of structural sensitivities.We estimate that OAT, NSPs, and Test & Treat, implemented singly or in combination, have the potential to effectively and cost-effectively prevent HIV in US PWID. PrEP is not likely to be cost-effective in this population, based on the scenarios we evaluated. While local budgets or policy may constrain feasible coverage levels for the various interventions, our findings suggest that investments in combined prevention programs can substantially reduce HIV transmission and improve health outcomes among PWID.
View details for DOI 10.1371/journal.pmed.1002312
View details for PubMedID 28542184
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Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment
HEALTH CARE MANAGEMENT SCIENCE
2017; 20 (1): 16-32
Abstract
How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient's quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3-4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment-despite expectations for future treatment improvement-for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population.
View details for DOI 10.1007/s10729-015-9330-6
View details for Web of Science ID 000398100100002
View details for PubMedCentralID PMC4718905
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Dynamic treatment selection and modification for personalised blood pressure therapy using a Markov decision process model: a cost-effectiveness analysis.
BMJ open
2017; 7 (11): e018374
Abstract
Personalised medicine seeks to select and modify treatments based on individual patient characteristics and preferences. We sought to develop an automated strategy to select and modify blood pressure treatments, incorporating the likelihood that patients with different characteristics would benefit from different types of medications and dosages and the potential severity and impact of different side effects among patients with different characteristics.We developed a Markov decision process (MDP) model to incorporate meta-analytic data and estimate the optimal treatment for maximising discounted lifetime quality-adjusted life-years (QALYs) based on individual patient characteristics, incorporating medication adjustment choices when a patient incurs side effects. We compared the MDP to current US blood pressure treatment guidelines (the Eighth Joint National Committee, JNC8) and a variant of current guidelines that incorporates results of a major recent trial of intensive treatment (Intensive JNC8). We used a microsimulation model of patient demographics, cardiovascular disease risk factors and side effect probabilities, sampling from the National Health and Nutrition Examination Survey (2003-2014), to compare the expected population outcomes from adopting the MDP versus guideline-based strategies.Costs and QALYs for the MDP-based treatment (MDPT), JNC8 and Intensive JNC8 strategies.Compared with the JNC8 guideline, the MDPT strategy would be cost-saving from a societal perspective with discounted savings of US$1187 per capita (95% CI 1178 to 1209) and an estimated discounted gain of 0.06 QALYs per capita (95% CI 0.04 to 0.08) among the US adult population. QALY gains would largely accrue from reductions in severe side effects associated with higher treatment doses later in life. The Intensive JNC8 strategy was dominated by the MDPT strategy.An MDP-based approach can aid decision-making by incorporating meta-analytic evidence to personalise blood pressure treatment and improve overall population health compared with current blood pressure treatment guidelines.
View details for PubMedID 29146652
View details for PubMedCentralID PMC5695480
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Analytical Approaches to Operating Room Management Projects at Lucile Packard Children's Hospital Stanford
SPRINGER. 2017: 17-26
View details for DOI 10.1007/978-3-319-66146-9_2
View details for Web of Science ID 000476922200002
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Risk stratification in compartmental epidemic models: Where to draw the line?
Journal of theoretical biology
2017; 428: 1–17
Abstract
Economic evaluations of infectious disease control interventions frequently use dynamic compartmental epidemic models. Such models capture heterogeneity in risk of infection by stratifying the population into discrete risk groups, thus approximating what is typically continuous variation in risk. An important open question is whether and how different risk stratification choices influence model predictions of intervention effects. We develop equivalent Susceptible-Infected-Susceptible (SIS) dynamic transmission models: an unstratified model, a model stratified into a high-risk and low-risk group, and a model with an arbitrary number of risk groups. Absent intervention, the models produce the same overall prevalence of infected individuals in steady state. We consider an intervention that either reduces the contact rate or increases the disease clearance rate. We develop analytical and numerical results characterizing the models and the effects of the intervention. We find that there exist multiple feasible choices of risk stratification, contact distribution, and within- and between-group contact rates for models that stratify risk. We show analytically and empirically that these choices can generate different estimates of intervention effectiveness, and that these differences can be significant enough to alter conclusions from cost-effectiveness analyses and change policy recommendations. We conclude that the choice of how to discretize risk in compartmental epidemic models can influence predicted effectiveness of interventions. Therefore, analysts should examine multiple alternatives and report the range of results.
View details for PubMedID 28606751
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Cost-effectiveness of malaria preventive treatment for HIV-infected pregnant women in sub-Saharan Africa.
Malaria journal
2017; 16 (1): 403
Abstract
Malaria is a leading cause of morbidity and mortality among HIV-infected pregnant women in sub-Saharan Africa: at least 1 million pregnancies among HIV-infected women are complicated by co-infection with malaria annually, leading to increased risk of premature delivery, severe anaemia, delivery of low birth weight infants, and maternal death. Current guidelines recommend either daily cotrimoxazole (CTX) or intermittent preventive treatment with sulfadoxine-pyrimethamine (IPTp-SP) for HIV-infected pregnant women to prevent malaria and its complications. The cost-effectiveness of CTX compared to IPTp-SP among HIV-infected pregnant women was assessed.A microsimulation model of malaria and HIV among pregnant women in five malaria-endemic countries in sub-Saharan Africa was constructed. Four strategies were compared: (1) 2-dose IPTp-SP at current IPTp-SP coverage of the country ("2-IPT Low"); (2) 3-dose IPTp-SP at current coverage ("3-IPT Low"); (3) 3-dose IPTp-SP at the same coverage as antiretroviral therapy (ART) in the country ("3-IPT High"); and (4) daily CTX at ART coverage. Outcomes measured include maternal malaria, anaemia, low birth weight (LBW), and disability-adjusted life years (DALYs). Sensitivity analyses assessed the effect of adherence to CTX.Compared with the 2-IPT Low Strategy, women receiving CTX had 22.5% fewer LBW infants (95% CI 22.3-22.7), 13.5% fewer anaemia cases (95% CI 13.4-13.5), and 13.6% fewer maternal malaria cases (95% CI 13.6-13.7). In all simulated countries, CTX was the preferred strategy, with incremental cost-effectiveness ratios ranging from cost-saving to $3.9 per DALY averted from a societal perspective. CTX was less effective than the 3-IPT High Strategy when more than 18% of women stopped taking CTX during the pregnancy.In malarious regions of sub-Saharan Africa, daily CTX for HIV-infected pregnant women regardless of CD4 cell count is cost-effective compared with 3-dose IPTp-SP as long as more than 82% of women adhere to daily dosing.
View details for PubMedID 28985732
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Creating impact with operations research in health: making room for practice in academia
HEALTH CARE MANAGEMENT SCIENCE
2016; 19 (4): 305-312
Abstract
Operations research (OR)-based analyses have the potential to improve decision making for many important, real-world health care problems. However, junior scholars often avoid working on practical applications in health because promotion and tenure processes tend to value theoretical studies more highly than applied studies. This paper discusses the author's experiences in using OR to inform and influence decisions in health and provides a blueprint for junior researchers who wish to find success by taking a similar path. This involves selecting good problems to study, forming productive collaborations with domain experts, developing appropriate models, identifying the most salient results from an analysis, and effectively disseminating findings to decision makers. The paper then suggests how journals, funding agencies, and senior academics can encourage such work by taking a broader and more informed view of the potential role and contributions of OR to solving health care problems. Making room in academia for the application of OR in health follows in the tradition begun by the founders of operations research: to work on important real-world problems where operations research can contribute to better decision making.
View details for DOI 10.1007/s10729-015-9328-0
View details for Web of Science ID 000387088500001
View details for PubMedID 26003321
View details for PubMedCentralID PMC4658326
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Cost-Effectiveness of HIV Preexposure Prophylaxis for People Who Inject Drugs in the United States
ANNALS OF INTERNAL MEDICINE
2016; 165 (1): 10-?
View details for DOI 10.7326/M15-2634
View details for Web of Science ID 000379215800003
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Modeling a dynamic bi-layer contact network of injection drug users and the spread of blood-borne infections
MATHEMATICAL BIOSCIENCES
2016; 273: 102-113
Abstract
Injection drug users (IDUs) are at high risk of acquiring and spreading various blood-borne infections including human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV) and a number of sexually transmitted infections. These infections can spread among IDUs via risky sexual and needle-sharing contacts. To accurately model the spread of such contagions among IDUs, we build a bi-layer network that captures both types of risky contacts. We present methodology for inferring important model parameters, such as those governing network structure and dynamics, from readily available data sources (e.g., epidemiological surveys). Such a model can be used to evaluate the efficacy of various programs that aim to combat drug addiction and contain blood-borne diseases among IDUs. The model is especially useful for evaluating interventions that exploit the structure of the contact network. To illustrate, we instantiate a network model with data collected by a needle and syringe program in Chicago. We model sexual and needle-sharing contacts and the consequent spread of HIV and HCV. We use the model to evaluate the potential effects of a peer education (PE) program under different targeting strategies. We show that a targeted PE program would avert significantly more HIV and HCV infections than an untargeted program, highlighting the importance of reaching individuals who are centrally located in contact networks when instituting prevention programs.
View details for DOI 10.1016/j.mbs.2016.01.003
View details for Web of Science ID 000370908500009
View details for PubMedID 26775738
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HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment
MEDICAL DECISION MAKING
2016; 36 (3): 391-409
Abstract
To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention.A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted.Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model.Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP.
View details for DOI 10.1177/0272989X15598528
View details for Web of Science ID 000371697100011
View details for PubMedID 26369347
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Expansion of the National Salt Reduction Initiative: A Mathematical Model of Benefits and Risks of Population-Level Sodium Reduction
MEDICAL DECISION MAKING
2016; 36 (1): 72-85
Abstract
. The National Salt Reduction Initiative, in which food producers agree to lower sodium to levels deemed feasible for different foods, is expected to significantly reduce sodium intake if expanded to a large sector of food manufacturers.. Given recent data on the relationship between sodium intake, hypertension, and associated cardiovascular disease at a population level, we sought to examine risks and benefits of the program.. To estimate the impact of further expanding the initiative on hypertension, myocardial infarction (MI) and stroke incidence, and related mortality, given food consumption patterns across the United States, we developed and validated a stochastic microsimulation model of hypertension, MI, and stroke morbidity and mortality, using data from food producers on sodium reduction among foods, linked to 24-hour dietary recalls, blood pressure, and cardiovascular histories from the National Health and Nutrition Examination Survey.. Expansion of the initiative to ensure all restaurants and manufacturers reach agreed-upon sodium targets would be expected to avert from 0.9 to 3.0 MIs (a 1.6%-5.4% reduction) and 0.5 to 2.8 strokes (a 1.1%-6.2% reduction) per 10,000 Americans per year over the next decade, after incorporating consumption patterns and variations in the effect of sodium reduction on blood pressure among different demographic groups. Even high levels of consumer addition of table salt or substitution among food categories would be unlikely to neutralize this benefit. However, if recent epidemiological associations between very low sodium and increased mortality are causal, then older women may be at risk of increased mortality from excessively low sodium intake.An expanded National Salt Reduction Initiative is likely to significantly reduce hypertension and hypertension-related cardiovascular morbidity but may be accompanied by potential risks to older women.
View details for DOI 10.1177/0272989X15583846
View details for Web of Science ID 000366910300008
View details for PubMedID 25926284
View details for PubMedCentralID PMC4626435
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Evaluating Cost-effectiveness of Interventions That Affect Fertility and Childbearing: How Health Effects Are Measured Matters.
Medical decision making
2015; 35 (7): 818-846
Abstract
Current guidelines for economic evaluations of health interventions define relevant outcomes as those accruing to individuals receiving interventions. Little consensus exists on counting health impacts on current and future fertility and childbearing. Our objective was to characterize current practices for counting such health outcomes.We developed a framework characterizing health interventions with direct and/or indirect effects on fertility and childbearing and how such outcomes are reported. We identified interventions spanning the framework and performed a targeted literature review for economic evaluations of these interventions. For each article, we characterized how the potential health outcomes from each intervention were considered, focusing on quality-adjusted life-years (QALYs) associated with fertility and childbearing.We reviewed 108 studies, identifying 7 themes: 1) Studies were heterogeneous in reporting outcomes. 2) Studies often selected outcomes for inclusion that tend to bias toward finding the intervention to be cost-effective. 3) Studies often avoided the challenges of assigning QALYs for pregnancy and fertility by instead considering cost per intermediate outcome. 4) Even for the same intervention, studies took heterogeneous approaches to outcome evaluation. 5) Studies used multiple, competing rationales for whether and how to include fertility-related QALYs and whose QALYs to include. 6) Studies examining interventions with indirect effects on fertility typically ignored such QALYs. 7) Even recent studies had these shortcomings. Limitations include that the review was targeted rather than systematic.Economic evaluations inconsistently consider QALYs from current and future fertility and childbearing in ways that frequently appear biased toward the interventions considered. As the Panel on Cost-Effectiveness in Health and Medicine updates its guidelines, making the practice of cost-effectiveness analysis more consistent is a priority. Our study contributes to harmonizing methods in this respect.
View details for DOI 10.1177/0272989X15583845
View details for PubMedID 25926281
View details for PubMedCentralID PMC4418217
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Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment.
Health care management science
2015: -?
Abstract
How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient's quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3-4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment-despite expectations for future treatment improvement-for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population.
View details for PubMedID 26188961
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Link removal for the control of stochastically evolving epidemics over networks: A comparison of approaches
JOURNAL OF THEORETICAL BIOLOGY
2015; 371: 154-165
Abstract
For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two "preventive" approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two "reactive" approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdös-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdös-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing which nodes are initially infected by comparing the performance improvement achieved by reactive over preventive strategies. We find that such information is most valuable for moderate budget levels, with increasing value as disease spread becomes more likely (due to either increased connectedness of the network or increased infectiousness of the disease).
View details for DOI 10.1016/j.jtbi.2015.02.005
View details for Web of Science ID 000353011200014
View details for PubMedID 25698229
View details for PubMedCentralID PMC4372451
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Modeling and calibration for exposure to time-varying, modifiable risk factors: the example of smoking behavior in India.
Medical decision making
2015; 35 (2): 196-210
Abstract
Risk factors increase the incidence and severity of chronic disease. To examine future trends and develop policies addressing chronic diseases, it is important to capture the relationship between exposure and disease development, which is challenging given limited data.To develop parsimonious risk factor models embeddable in chronic disease models, which are useful when longitudinal data are unavailable.The model structures encode relevant features of risk factors (e.g., time-varying, modifiable) and can be embedded in chronic disease models. Calibration captures time-varying exposures for the risk factor models using available cross-sectional data. We illustrate feasibility with the policy-relevant example of smoking in India.The model is calibrated to the prevalence of male smoking in 12 Indian regions estimated from the 2009-2010 Indian Global Adult Tobacco Survey. Nelder-Mead searches (250,000 starting locations) identify distributions of starting, quitting, and restarting rates that minimize the difference between modeled and observed age-specific prevalence. We compare modeled life expectancies to estimates in the absence of time-varying risk exposures and consider gains from hypothetical smoking cessation programs delivered for 1 to 30 years.Calibration achieves concordance between modeled and observed outcomes. Probabilities of starting to smoke rise and fall with age, while quitting and restarting probabilities fall with age. Accounting for time-varying smoking exposures is important, as not doing so produces smaller estimates of life expectancy losses. Estimated impacts of smoking cessation programs delivered for different periods depend on the fact that people who have been induced to abstain from smoking longer are less likely to restart.The approach described is feasible for important risk factors for numerous chronic diseases. Incorporating exposure-change rates can improve modeled estimates of chronic disease outcomes and of the long-term effects of interventions targeting risk factors.
View details for DOI 10.1177/0272989X13518272
View details for PubMedID 24477078
View details for PubMedCentralID PMC4115057
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HIV epidemic control-a model for optimal allocation of prevention and treatment resources
HEALTH CARE MANAGEMENT SCIENCE
2014; 17 (2): 162-181
Abstract
With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.
View details for DOI 10.1007/s10729-013-9240-4
View details for Web of Science ID 000341086500006
View details for PubMedID 23793895
View details for PubMedCentralID PMC3839258
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Expanded HIV Testing in Low-Prevalence, High-Income Countries: A Cost-Effectiveness Analysis for the United Kingdom
PLOS ONE
2014; 9 (4)
Abstract
In many high-income countries with low HIV prevalence, significant numbers of persons living with HIV (PLHIV) remain undiagnosed. Identification of PLHIV via HIV testing offers timely access to lifesaving antiretroviral therapy (ART) and decreases HIV transmission. We estimated the effectiveness and cost-effectiveness of HIV testing in the United Kingdom (UK), where 25% of PLHIV are estimated to be undiagnosed.We developed a dynamic compartmental model to analyze strategies to expand HIV testing and treatment in the UK, with particular focus on men who have sex with men (MSM), people who inject drugs (PWID), and individuals from HIV-endemic countries.We estimated HIV prevalence, incidence, quality-adjusted life years (QALYs), and health care costs over 10 years, and cost-effectiveness.Annual HIV testing of all adults could avert 5% of new infections, even with no behavior change following HIV diagnosis because of earlier ART initiation, or up to 18% if risky behavior is halved. This strategy costs £67,000-£106,000/QALY gained. Providing annual testing only to MSM, PWID, and people from HIV-endemic countries, and one-time testing for all other adults, prevents 4-15% of infections, requires one-fourth as many tests to diagnose each PLHIV, and costs £17,500/QALY gained. Augmenting this program with increased ART access could add 145,000 QALYs to the population over 10 years, at £26,800/QALY gained.Annual HIV testing of key populations in the UK is very cost-effective. Additional one-time testing of all other adults could identify the majority of undiagnosed PLHIV. These findings are potentially relevant to other low-prevalence, high-income countries.
View details for DOI 10.1371/journal.pone.0095735
View details for Web of Science ID 000335505000031
View details for PubMedID 24763373
View details for PubMedCentralID PMC3998955
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Effectiveness and Cost Effectiveness of Oral Pre-Exposure Prophylaxis in a Portfolio of Prevention Programs for Injection Drug Users in Mixed HIV Epidemics.
PloS one
2014; 9 (1)
Abstract
Pre-exposure prophylaxis with oral antiretroviral treatment (oral PrEP) for HIV-uninfected injection drug users (IDUs) is potentially useful in controlling HIV epidemics with a significant injection drug use component. We estimated the effectiveness and cost effectiveness of strategies for using oral PrEP in various combinations with methadone maintenance treatment (MMT) and antiretroviral treatment (ART) in Ukraine, a representative case for mixed HIV epidemics.We developed a dynamic compartmental model of the HIV epidemic in a population of non-IDUs, IDUs who inject opiates, and IDUs in MMT, adding an oral PrEP program (tenofovir/emtricitabine, 49% susceptibility reduction) for uninfected IDUs. We analyzed intervention portfolios consisting of oral PrEP (25% or 50% of uninfected IDUs), MMT (25% of IDUs), and ART (80% of all eligible patients). We measured health care costs, quality-adjusted life years (QALYs), HIV prevalence, HIV infections averted, and incremental cost effectiveness. A combination of PrEP for 50% of IDUs and MMT lowered HIV prevalence the most in both IDUs and the general population. ART combined with MMT and PrEP (50% access) averted the most infections (14,267). For a PrEP cost of $950, the most cost-effective strategy was MMT, at $520/QALY gained versus no intervention. The next most cost-effective strategy consisted of MMT and ART, costing $1,000/QALY gained compared to MMT alone. Further adding PrEP (25% access) was also cost effective by World Health Organization standards, at $1,700/QALY gained. PrEP alone became as cost effective as MMT at a cost of $650, and cost saving at $370 or less.Oral PrEP for IDUs can be part of an effective and cost-effective strategy to control HIV in regions where injection drug use is a significant driver of the epidemic. Where budgets are limited, focusing on MMT and ART access should be the priority, unless PrEP has low cost.
View details for DOI 10.1371/journal.pone.0086584
View details for PubMedID 24489747
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Too Much of a Good Thing? When to Stop Catch-Up Vaccination
MEDICAL DECISION MAKING
2013; 33 (7): 920-936
Abstract
During the 20th century, deaths from a range of serious infectious diseases decreased dramatically due to the development of safe and effective vaccines. However, infant immunization coverage has increased only marginally since the 1960s, and many people remain susceptible to vaccine-preventable diseases. "Catch-up vaccination" for age groups beyond infancy can be an attractive and effective means of immunizing people who were missed earlier. However, as newborn vaccination rates increase, catch-up vaccination becomes less attractive: the number of susceptible people decreases, so the cost to find and vaccinate each unvaccinated person may increase; in addition, the number of infected individuals decreases, so each unvaccinated person faces a lower risk of infection. This article presents a general framework for determining the optimal time to discontinue a catch-up vaccination program. We use a cost-effectiveness framework: we consider the cost per quality-adjusted life year gained of catch-up vaccination efforts as a function of newborn immunization rates over time and consequent disease prevalence and incidence. We illustrate our results with the example of hepatitis B catch-up vaccination in China. We contrast results from a dynamic modeling approach with an approach that ignores the impact of vaccination on future disease incidence. The latter approach is likely to be simpler for decision makers to understand and implement because of lower data requirements.
View details for DOI 10.1177/0272989X13493142
View details for Web of Science ID 000324535200004
View details for PubMedID 23858015
View details for PubMedCentralID PMC4247340
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Are organic foods safer or healthier?
Annals of internal medicine
2013; 158 (4): 297-300
View details for DOI 10.7326/0003-4819-158-4-201302190-00019
View details for PubMedID 23420246
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Are Organic Foods Safer or Healthier?
ANNALS OF INTERNAL MEDICINE
2013; 158 (4): 297
View details for DOI 10.7326/0003-4819-158-4-201302190-00018
View details for Web of Science ID 000315580300026
View details for PubMedID 23420245
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Are Organic Foods Safer or Healthier? RESPONSE
ANNALS OF INTERNAL MEDICINE
2013; 158 (4): 297-300
View details for Web of Science ID 000315580300027
- National Biodefense Science Board/Board of Scientific Counselors Strategic National Stockpile 2020 Joint Working Group. Anticipated Responsibilities of the Strategic National Stockpile (SNS) in the Year 2020 – An Examination with Recommendations. Washington, DC 2013
- Too much of a good thing? When to stop catch-up vaccination. Medical Decision Making 2013; 7 (33): 920-936.
- REACH: A practical HIV resource allocation tool for decision makers. In Operations Research and Health Care Policy edited by Zaric, G., S. Springer Publishers, New York. 2013: 201–224.
- Are organic foods safer or healthier? [Letter]. [Letter]. Annals of Internal Medicine. 2013; 4 (158): 297-300.
- OR in public health: A little help can go a long way. In Operations Research and Health Care Policy edited by Zaric, G., S. Springer Publishers, New York. 2013: 17–38.
- HIV epidemic control: A model for optimal allocation of prevention and treatment resources. Health Care Management Science, Epub ahead of print. 2013
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Balancing Immunological Benefits and Cardiovascular Risks of Antiretroviral Therapy: When Is Immediate Treatment Optimal?
CLINICAL INFECTIOUS DISEASES
2012; 55 (10): 1392-1399
Abstract
We developed a mathematical model to identify the timing of antiretroviral therapy (ART) initiation that optimizes patient outcomes as a function of patient CD4 count, age, cardiac mortality risk, sex, and personal preferences. Our goal was to find the conditions that maximize patient quality-adjusted life expectancy (QALE) in the context of our model. Under the assumption that ART confers disease progression and mortality benefits at any CD4 count, immediate treatment initiation yields the greatest remaining QALE for young patients under most circumstances. The timing of ART initiation depends on the magnitude of benefit from ART at high CD4 counts, the magnitude of increases in cardiac risk, and patients' preferences. If ART reduces HIV progression at high CD4 counts, immediate ART is preferable for most newly infected individuals <35 years even if ART doubles age- and sex-specific cardiac risk.
View details for DOI 10.1093/cid/cis731
View details for PubMedID 22942203
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Cost Effectiveness of Screening Strategies for Early Identification of HIV and HCV Infection in Injection Drug Users
PLOS ONE
2012; 7 (9)
Abstract
To estimate the cost, effectiveness, and cost effectiveness of HIV and HCV screening of injection drug users (IDUs) in opioid replacement therapy (ORT).Dynamic compartmental model of HIV and HCV in a population of IDUs and non-IDUs for a representative U.S. urban center with 2.5 million adults (age 15-59).We considered strategies of screening individuals in ORT for HIV, HCV, or both infections by antibody or antibody and viral RNA testing. We evaluated one-time and repeat screening at intervals from annually to once every 3 months. We calculated the number of HIV and HCV infections, quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs).Adding HIV and HCV viral RNA testing to antibody testing averts 14.8-30.3 HIV and 3.7-7.7 HCV infections in a screened population of 26,100 IDUs entering ORT over 20 years, depending on screening frequency. Screening for HIV antibodies every 6 months costs $30,700/QALY gained. Screening for HIV antibodies and viral RNA every 6 months has an ICER of $65,900/QALY gained. Strategies including HCV testing have ICERs exceeding $100,000/QALY gained unless awareness of HCV-infection status results in a substantial reduction in needle-sharing behavior.Although annual screening for antibodies to HIV and HCV is modestly cost effective compared to no screening, more frequent screening for HIV provides additional benefit at less cost. Screening individuals in ORT every 3-6 months for HIV infection using both antibody and viral RNA technologies and initiating ART for acute HIV infection appears cost effective.
View details for DOI 10.1371/journal.pone.0045176
View details for PubMedID 23028828
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Are organic foods safer or healthier than conventional alternatives?: a systematic review.
Annals of internal medicine
2012; 157 (5): 348-366
Abstract
The health benefits of organic foods are unclear.To review evidence comparing the health effects of organic and conventional foods.MEDLINE (January 1966 to May 2011), EMBASE, CAB Direct, Agricola, TOXNET, Cochrane Library (January 1966 to May 2009), and bibliographies of retrieved articles.English-language reports of comparisons of organically and conventionally grown food or of populations consuming these foods.2 independent investigators extracted data on methods, health outcomes, and nutrient and contaminant levels.17 studies in humans and 223 studies of nutrient and contaminant levels in foods met inclusion criteria. Only 3 of the human studies examined clinical outcomes, finding no significant differences between populations by food type for allergic outcomes (eczema, wheeze, atopic sensitization) or symptomatic Campylobacter infection. Two studies reported significantly lower urinary pesticide levels among children consuming organic versus conventional diets, but studies of biomarker and nutrient levels in serum, urine, breast milk, and semen in adults did not identify clinically meaningful differences. All estimates of differences in nutrient and contaminant levels in foods were highly heterogeneous except for the estimate for phosphorus; phosphorus levels were significantly higher than in conventional produce, although this difference is not clinically significant. The risk for contamination with detectable pesticide residues was lower among organic than conventional produce (risk difference, 30% [CI, -37% to -23%]), but differences in risk for exceeding maximum allowed limits were small. Escherichia coli contamination risk did not differ between organic and conventional produce. Bacterial contamination of retail chicken and pork was common but unrelated to farming method. However, the risk for isolating bacteria resistant to 3 or more antibiotics was higher in conventional than in organic chicken and pork (risk difference, 33% [CI, 21% to 45%]).Studies were heterogeneous and limited in number, and publication bias may be present.The published literature lacks strong evidence that organic foods are significantly more nutritious than conventional foods. Consumption of organic foods may reduce exposure to pesticide residues and antibiotic-resistant bacteria.None.
View details for DOI 10.7326/0003-4819-157-5-201209040-00007
View details for PubMedID 22944875
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Are Organic Foods Safer or Healthier Than Conventional Alternatives?
ANNALS OF INTERNAL MEDICINE
2012; 157 (5): 348-U112
Abstract
The health benefits of organic foods are unclear.To review evidence comparing the health effects of organic and conventional foods.MEDLINE (January 1966 to May 2011), EMBASE, CAB Direct, Agricola, TOXNET, Cochrane Library (January 1966 to May 2009), and bibliographies of retrieved articles.English-language reports of comparisons of organically and conventionally grown food or of populations consuming these foods.2 independent investigators extracted data on methods, health outcomes, and nutrient and contaminant levels.17 studies in humans and 223 studies of nutrient and contaminant levels in foods met inclusion criteria. Only 3 of the human studies examined clinical outcomes, finding no significant differences between populations by food type for allergic outcomes (eczema, wheeze, atopic sensitization) or symptomatic Campylobacter infection. Two studies reported significantly lower urinary pesticide levels among children consuming organic versus conventional diets, but studies of biomarker and nutrient levels in serum, urine, breast milk, and semen in adults did not identify clinically meaningful differences. All estimates of differences in nutrient and contaminant levels in foods were highly heterogeneous except for the estimate for phosphorus; phosphorus levels were significantly higher than in conventional produce, although this difference is not clinically significant. The risk for contamination with detectable pesticide residues was lower among organic than conventional produce (risk difference, 30% [CI, -37% to -23%]), but differences in risk for exceeding maximum allowed limits were small. Escherichia coli contamination risk did not differ between organic and conventional produce. Bacterial contamination of retail chicken and pork was common but unrelated to farming method. However, the risk for isolating bacteria resistant to 3 or more antibiotics was higher in conventional than in organic chicken and pork (risk difference, 33% [CI, 21% to 45%]).Studies were heterogeneous and limited in number, and publication bias may be present.The published literature lacks strong evidence that organic foods are significantly more nutritious than conventional foods. Consumption of organic foods may reduce exposure to pesticide residues and antibiotic-resistant bacteria.None.
View details for Web of Science ID 000308361500005
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The Cost-Effectiveness of Preexposure Prophylaxis for HIV Prevention in the United States in Men Who Have Sex With Men
ANNALS OF INTERNAL MEDICINE
2012; 156 (8): 541-U144
Abstract
A recent randomized, controlled trial showed that daily oral preexposure chemoprophylaxis (PrEP) was effective for HIV prevention in men who have sex with men (MSM). The Centers for Disease Control and Prevention recently provided interim guidance for PrEP in MSM at high risk for HIV. Previous studies did not reach a consistent estimate of its cost-effectiveness.To estimate the effectiveness and cost-effectiveness of PrEP in MSM in the United States.Dynamic model of HIV transmission and progression combined with a detailed economic analysis.Published literature.MSM aged 13 to 64 years in the United States.Lifetime.Societal.PrEP was evaluated in both the general MSM population and in high-risk MSM and was assumed to reduce infection risk by 44% on the basis of clinical trial results.New HIV infections, discounted quality-adjusted life-years (QALYs) and costs, and incremental cost-effectiveness ratios.Initiating PrEP in 20% of MSM in the United States would reduce new HIV infections by an estimated 13% and result in a gain of 550,166 QALYs over 20 years at a cost of $172,091 per QALY gained. Initiating PrEP in a larger proportion of MSM would prevent more infections but at an increasing cost per QALY gained (up to $216,480 if all MSM receive PrEP). Preexposure chemoprophylaxis in only high-risk MSM can improve cost-effectiveness. For MSM with an average of 5 partners per year, PrEP costs approximately $50,000 per QALY gained. Providing PrEP to all high-risk MSM for 20 years would cost $75 billion more in health care-related costs than the status quo and $600,000 per HIV infection prevented, compared with incremental costs of $95 billion and $2 million per infection prevented for 20% coverage of all MSM.PrEP in the general MSM population would cost less than $100,000 per QALY gained if the daily cost of antiretroviral drugs for PrEP was less than $15 or if PrEP efficacy was greater than 75%.When examining PrEP in high-risk MSM, the investigators did not model a mix of low- and high-risk MSM because of lack of data on mixing patterns.PrEP in the general MSM population could prevent a substantial number of HIV infections, but it is expensive. Use in high-risk MSM compares favorably with other interventions that are considered cost-effective but could result in annual PrEP expenditures of more than $4 billion.National Institute on Drug Abuse, Department of Veterans Affairs, and National Institute of Allergy and Infectious Diseases.
View details for DOI 10.1059/0003-4819-156-8-201204170-00001
View details for PubMedID 22508731
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Optimal link removal for epidemic mitigation: A two-way partitioning approach
MATHEMATICAL BIOSCIENCES
2012; 235 (2): 138-147
Abstract
The structure of the contact network through which a disease spreads may influence the optimal use of resources for epidemic control. In this work, we explore how to minimize the spread of infection via quarantining with limited resources. In particular, we examine which links should be removed from the contact network, given a constraint on the number of removable links, such that the number of nodes which are no longer at risk for infection is maximized. We show how this problem can be posed as a non-convex quadratically constrained quadratic program (QCQP), and we use this formulation to derive a link removal algorithm. The performance of our QCQP-based algorithm is validated on small Erdős-Renyi and small-world random graphs, and then tested on larger, more realistic networks, including a real-world network of injection drug use. We show that our approach achieves near optimal performance and out-performs other intuitive link removal algorithms, such as removing links in order of edge centrality.
View details for DOI 10.1016/j.mbs.2011.11.006
View details for Web of Science ID 000301020300003
View details for PubMedID 22115862
View details for PubMedCentralID PMC3434711
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Decision Making for HIV Prevention and Treatment Scale up: Bridging the Gap between Theory and Practice
MEDICAL DECISION MAKING
2012; 32 (1): 105-117
Abstract
Effectively controlling the HIV epidemic will require efficient use of limited resources. Despite ambitious global goals for HIV prevention and treatment scale up, few comprehensive practical tools exist to inform such decisions.We briefly summarize modeling approaches for resource allocation for epidemic control, and discuss the practical limitations of these models. We describe typical challenges of HIV resource allocation in practice and some of the tools used by decision makers. We identify the characteristics needed in a model that can effectively support planners in decision making about HIV prevention and treatment scale up.An effective model to support HIV scale-up decisions will be flexible, with capability for parameter customization and incorporation of uncertainty. Such a model needs certain key technical features: it must capture epidemic effects; account for how intervention effectiveness depends on the target population and the level of scale up; capture benefit and cost differentials for packages of interventions versus single interventions, including both treatment and prevention interventions; incorporate key constraints on potential funding allocations; identify optimal or near-optimal solutions; and estimate the impact of HIV interventions on the health care system and the resulting resource needs. Additionally, an effective model needs a user-friendly design and structure, ease of calibration and validation, and accessibility to decision makers in all settings.Resource allocation theory can make a significant contribution to decision making about HIV prevention and treatment scale up. What remains now is to develop models that can bridge the gap between theory and practice.
View details for DOI 10.1177/0272989X10391808
View details for Web of Science ID 000299701100014
View details for PubMedID 21191118
View details for PubMedCentralID PMC3271126
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Assessing effectiveness and cost-effectiveness of concurrency reduction for HIV prevention
INTERNATIONAL JOURNAL OF STD & AIDS
2011; 22 (10): 558-567
Abstract
We estimated the effectiveness and cost-effectiveness of changes in concurrent sexual partnerships in reducing the spread of HIV in sub-Saharan Africa. Using data from Swaziland, Tanzania, Uganda and Zambia, we estimated country-specific concurrency behaviour from sexual behaviour survey data on the number of partners in the past 12 months, and we developed a network model to compare the impact of three behaviour changes on the HIV epidemic: (1) changes in concurrent partnership patterns to strict monogamy; (2) partnership reduction among those with the greatest number of partners; and (3) partnership reduction among all individuals. We estimated the number of new HIV infections over 10 years and the cost per infection averted. Given our assumptions and model structure, we find that reducing concurrency among high-risk individuals averts the most infections and increasing monogamy the least (11.7% versus 8.7% reduction in new infections, on average, for a 10% reduction in concurrent partnerships). A campaign that costs US$1 per person annually is likely cost-saving if it reduces concurrency by 9% on average, given our baseline estimates of concurrency. In sensitivity analysis, the rank ordering of behaviour change scenarios was unaffected by potential over-estimation of concurrency, though the number of infections averted decreased and the cost per HIV infection averted increased. Concurrency reduction programmes may be effective and cost-effective in reducing HIV incidence in sub-Saharan Africa if they can achieve even modest impacts at similar costs to past mass media campaigns in the region. Reduced concurrency among high-risk individuals appears to be most effective in reducing HIV incidence, but concurrency reduction in other risk groups may yield nearly as much benefit.
View details for DOI 10.1258/ijsa.2011.010322
View details for Web of Science ID 000296991200004
View details for PubMedID 21998175
View details for PubMedCentralID PMC3230224
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The cost-effectiveness of symptom-based testing and routine screening for acute HIV infection in men who have sex with men in the USA
AIDS
2011; 25 (14): 1779-1787
Abstract
Acute HIV infection often causes influenza-like illness (ILI) and is associated with high infectivity. We estimated the effectiveness and cost-effectiveness of strategies to identify and treat acute HIV infection in men who have sex with men (MSM) in the USA.Dynamic model of HIV transmission and progression.We evaluated three testing approaches: viral load testing for individuals with ILI, expanded screening with antibody testing, and expanded screening with antibody and viral load testing. We included treatment with antiretroviral therapy for individuals identified as acutely infected.New HIV infections, discounted quality-adjusted life years (QALYs) and costs, and incremental cost-effectiveness ratios.At the present rate of HIV-antibody testing, we estimated that 538,000 new infections will occur among MSM over the next 20 years. Expanding antibody screening coverage to 90% of MSM annually reduces new infections by 2.8% and costs US$ 12,582 per QALY gained. Symptom-based viral load testing with ILI is more expensive than expanded antibody screening, but is more effective and costs US$ 22,786 per QALY gained. Combining expanded antibody screening with symptom-based viral load testing prevents twice as many infections compared to expanded antibody screening alone, and costs US$ 29,923 per QALY gained. Adding viral load testing to all annual HIV tests costs more than US$ 100,000 per QALY gained.Use of HIV viral load testing in MSM with ILI prevents more infections than does expanded annual antibody screening alone and is inexpensive relative to other screening interventions. Clinicians should consider symptom-based viral load testing in MSM, in addition to encouraging annual antibody screening.
View details for DOI 10.1097/QAD.0b013e328349f067
View details for PubMedID 21716076
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Efficient stockpiling and shipping policies for humanitarian relief: UNHCR's inventory challenge
OR SPECTRUM
2011; 33 (3): 673-698
View details for DOI 10.1007/s00291-011-0237-4
View details for Web of Science ID 000292213700011
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Inferring model parameters in network-based disease simulation
HEALTH CARE MANAGEMENT SCIENCE
2011; 14 (2): 174-188
Abstract
Many models of infectious disease ignore the underlying contact structure through which the disease spreads. However, in order to evaluate the efficacy of certain disease control interventions, it may be important to include this network structure. We present a network modeling framework of the spread of disease and a methodology for inferring important model parameters, such as those governing network structure and network dynamics, from readily available data sources. This is a general and flexible framework with wide applicability to modeling the spread of disease through sexual or close contact networks. To illustrate, we apply this modeling framework to evaluate HIV control programs in sub-Saharan Africa, including programs aimed at concurrent partnership reduction, reductions in risky sexual behavior, and scale up of HIV treatment.
View details for DOI 10.1007/s10729-011-9150-2
View details for Web of Science ID 000290039400005
View details for PubMedID 21373984
View details for PubMedCentralID PMC3108362
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Doing Good with Good OR: Supporting Cost-Effective Hepatitis B Interventions
INTERFACES
2011; 41 (3): 289-300
Abstract
In an era of limited healthcare budgets, mathematical models can be useful tools to identify cost-effective programs and to support policymakers in informed decision making. This paper reports results of our work carried out over several years with the Asian Liver Center at Stanford University, a nonprofit outreach and advocacy organization that is an international leader in the fight against hepatitis B and liver cancer. Hepatitis B is a vaccine-preventable viral disease that, if untreated, can lead to death from cirrhosis and liver cancer. Infection with hepatitis B is a major public health problem, particularly in Asian populations. We used new combinations of decision analysis and Markov models to analyze the cost-effectiveness of several interventions to combat hepatitis B in the United States and China. The results of our OR-based analyses have helped change United States public health policy on hepatitis B screening for millions of people and have helped encourage policymakers in China to enact legislation to provide free catch-up vaccination for hundreds of millions of children. These policies are an important step in eliminating health disparities, reducing discrimination, and ensuring that millions of people who need it can now receive hepatitis B vaccination or lifesaving treatment.
View details for DOI 10.1287/inte.1100.0511
View details for Web of Science ID 000292246700007
View details for PubMedCentralID PMC3134280
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Doing Good with Good OR: Supporting Cost-effective Hepatitis B Interventions.
Interfaces
2011; 41 (3): 289-300
Abstract
In an era of limited healthcare budgets, mathematical models can be useful tools to identify cost-effective programs and to support policymakers in informed decision making. This paper reports results of our work carried out over several years with the Asian Liver Center at Stanford University, a nonprofit outreach and advocacy organization that is an international leader in the fight against hepatitis B and liver cancer. Hepatitis B is a vaccine-preventable viral disease that, if untreated, can lead to death from cirrhosis and liver cancer. Infection with hepatitis B is a major public health problem, particularly in Asian populations. We used new combinations of decision analysis and Markov models to analyze the cost-effectiveness of several interventions to combat hepatitis B in the United States and China. The results of our OR-based analyses have helped change United States public health policy on hepatitis B screening for millions of people and have helped encourage policymakers in China to enact legislation to provide free catch-up vaccination for hundreds of millions of children. These policies are an important step in eliminating health disparities, reducing discrimination, and ensuring that millions of people who need it can now receive hepatitis B vaccination or lifesaving treatment.
View details for DOI 10.1287/inte.1100.0511
View details for PubMedID 21760650
View details for PubMedCentralID PMC3134280
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Effectiveness and Cost Effectiveness of Expanding Harm Reduction and Antiretroviral Therapy in a Mixed HIV Epidemic: A Modeling Analysis for Ukraine
PLOS MEDICINE
2011; 8 (3)
Abstract
Injection drug use (IDU) and heterosexual virus transmission both contribute to the growing mixed HIV epidemics in Eastern Europe and Central Asia. In Ukraine-chosen in this study as a representative country-IDU-related risk behaviors cause half of new infections, but few injection drug users (IDUs) receive methadone substitution therapy. Only 10% of eligible individuals receive antiretroviral therapy (ART). The appropriate resource allocation between these programs has not been studied. We estimated the effectiveness and cost-effectiveness of strategies for expanding methadone substitution therapy programs and ART in mixed HIV epidemics, using Ukraine as a case study.We developed a dynamic compartmental model of the HIV epidemic in a population of non-IDUs, IDUs using opiates, and IDUs on methadone substitution therapy, stratified by HIV status, and populated it with data from the Ukraine. We considered interventions expanding methadone substitution therapy, increasing access to ART, or both. We measured health care costs, quality-adjusted life years (QALYs), HIV prevalence, infections averted, and incremental cost-effectiveness. Without incremental interventions, HIV prevalence reached 67.2% (IDUs) and 0.88% (non-IDUs) after 20 years. Offering methadone substitution therapy to 25% of IDUs reduced prevalence most effectively (to 53.1% IDUs, 0.80% non-IDUs), and was most cost-effective, averting 4,700 infections and adding 76,000 QALYs compared with no intervention at US$530/QALY gained. Expanding both ART (80% coverage of those eligible for ART according to WHO criteria) and methadone substitution therapy (25% coverage) was the next most cost-effective strategy, adding 105,000 QALYs at US$1,120/QALY gained versus the methadone substitution therapy-only strategy and averting 8,300 infections versus no intervention. Expanding only ART (80% coverage) added 38,000 QALYs at US$2,240/QALY gained versus the methadone substitution therapy-only strategy, and averted 4,080 infections versus no intervention. Offering ART to 80% of non-IDUs eligible for treatment by WHO criteria, but only 10% of IDUs, averted only 1,800 infections versus no intervention and was not cost effective.Methadone substitution therapy is a highly cost-effective option for the growing mixed HIV epidemic in Ukraine. A strategy that expands both methadone substitution therapy and ART to high levels is the most effective intervention, and is very cost effective by WHO criteria. When expanding ART, access to methadone substitution therapy provides additional benefit in infections averted. Our findings are potentially relevant to other settings with mixed HIV epidemics. Please see later in the article for the Editors' Summary.
View details for DOI 10.1371/journal.pmed.1000423
View details for PubMedID 21390264
- Institute of Medicine Committee on Prepositioned Medical Countermeasures. Prepositioning Antibiotics for Anthrax. 2011
- Efficient stockpiling and shipping strategies for humanitarian relief: UNHCR’s inventory challenge. OR Spectrum 2011; 3 (33): 673-698.
- Inferring model parameters in network-based disease simulation. Health Care Management Science 2011; 2 (14): 174-188.
- The cost-effectiveness of symptom-based testing and routine screening for acute HIV infection in men who have sex with men in the United States. AIDS 2011; 14 (25): 1779-1787.
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The Cost-Effectiveness and Population Outcomes of Expanded HIV Screening and Antiretroviral Treatment in the United States
ANNALS OF INTERNAL MEDICINE
2010; 153 (12): 778-?
Abstract
Although recent guidelines call for expanded routine screening for HIV, resources for antiretroviral therapy (ART) are limited, and all eligible persons are not currently receiving treatment.To evaluate the effects on the U.S. HIV epidemic of expanded ART, HIV screening, or interventions to reduce risk behavior.Dynamic mathematical model of HIV transmission and disease progression and cost-effectiveness analysis.Published literature.High-risk (injection drug users and men who have sex with men) and low-risk persons aged 15 to 64 years in the United States.Twenty years and lifetime (costs and quality-adjusted life-years [QALYs]).Societal.Expanded HIV screening and counseling, treatment with ART, or both.New HIV infections, discounted costs and QALYs, and incremental cost-effectiveness ratios.One-time HIV screening of low-risk persons coupled with annual screening of high-risk persons could prevent 6.7% of a projected 1.23 million new infections and cost $22,382 per QALY gained, assuming a 20% reduction in sexual activity after screening. Expanding ART utilization to 75% of eligible persons prevents 10.3% of infections and costs $20,300 per QALY gained. A combination strategy prevents 17.3% of infections and costs $21,580 per QALY gained.With no reduction in sexual activity, expanded screening prevents 3.7% of infections. Earlier ART initiation when a CD4 count is greater than 0.350 × 10(9) cells/L prevents 20% to 28% of infections. Additional efforts to halve high-risk behavior could reduce infections by 65%.The model of disease progression and treatment was simplified, and acute HIV screening was excluded.Expanding HIV screening and treatment simultaneously offers the greatest health benefit and is cost-effective. However, even substantial expansion of HIV screening and treatment programs is not sufficient to markedly reduce the U.S. HIV epidemic without substantial reductions in risk behavior.National Institute on Drug Abuse, National Institutes of Health, and Department of Veterans Affairs.
View details for Web of Science ID 000285453700027
View details for PubMedID 21173412
View details for PubMedCentralID PMC3173812
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Cost-Effectiveness of Strategies for Diagnosing Pulmonary Embolism Among Emergency Department Patients Presenting With Undifferentiated Symptoms
ANNALS OF EMERGENCY MEDICINE
2010; 56 (4): 321-332
Abstract
Symptoms associated with pulmonary embolism can be nonspecific and similar to many competing diagnoses, leading to excessive costly testing and treatment, as well as missed diagnoses. Objective studies are essential for diagnosis. This study evaluates the cost-effectiveness of different diagnostic strategies in an emergency department (ED) for patients presenting with undifferentiated symptoms suggestive of pulmonary embolism.Using a probabilistic decision model, we evaluated the incremental costs and effectiveness (quality-adjusted life-years gained) of 60 testing strategies for 5 patient pretest categories (distinguished by Wells score [high, moderate, or low] and whether deep venous thrombosis is clinically suspected). We performed deterministic and probabilistic sensitivity analyses.In the base case, for all patient pretest categories, the most cost-effective diagnostic strategy is to use an initial enzyme-linked immunosorbent assay D-dimer test, followed by compression ultrasonography of the lower extremities if the D-dimer is above a specified cutoff. The level of the preferred cutoff varies with the Wells pretest category and whether a deep venous thrombosis is clinically suspected. D-dimer cutoffs higher than the current recommended cutoff were often preferred for patients with even moderate and high Wells categories. Compression ultrasonography accuracy had to decrease below commonly cited levels in the literature before it was not part of a preferred strategy.When pulmonary embolism is suspected in the ED, use of an enzyme-linked immunosorbent assay D-dimer assay, often at cutoffs higher than those currently in use (for patients in whom deep venous thrombosis is not clinically suspected), followed by compression ultrasonography as appropriate, can reduce costs and improve outcomes.
View details for DOI 10.1016/j.annemergmed.2010.03.029
View details for Web of Science ID 000282854500004
View details for PubMedID 20605261
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Comparative Effectiveness of HIV Testing and Treatment in Highly Endemic Regions
ARCHIVES OF INTERNAL MEDICINE
2010; 170 (15): 1347-1354
Abstract
Universal testing and treatment holds promise for reducing the burden of human immunodeficiency virus (HIV) in sub-Saharan Africa, but linkage from testing to treatment sites and retention in care are inadequate.We developed a simulation of the HIV epidemic and HIV disease progression in South Africa to compare the outcomes of the present HIV treatment campaign (status quo) with 4 HIV testing and treating strategies that increase access to antiretroviral therapy: (1) universal testing and treatment without changes in linkage to care and loss to follow-up; (2) universal testing and treatment with improved linkage to care; (3) universal testing and treatment with reduced loss to follow-up; and (4) comprehensive HIV care with universal testing and treatment, improved linkage to care, and reduced loss to follow-up. The main outcome measures were survival benefits, new HIV infections, and HIV prevalence.Compared with the status quo strategy, universal testing and treatment (1) was associated with a mean (95% uncertainty bounds) life expectancy gain of 12.0 months (11.3-12.2 months), and 35.3% (32.7%-37.5%) fewer HIV infections over a 10-year time horizon. Improved linkage to care (2), prevention of loss to follow-up (3), and comprehensive HIV care (4) provided substantial additional benefits: life expectancy gains compared with the status quo strategy were 16.1, 18.6, and 22.2 months, and new infections were 55.5%, 51.4%, and 73.2% lower, respectively. In sensitivity analysis, comprehensive HIV care reduced new infections by 69.7% to 76.7% under a broad set of assumptions.Universal testing and treatment with current levels of linkage to care and loss to follow-up could substantially reduce the HIV death toll and new HIV infections. However, increasing linkage to care and preventing loss to follow-up provides nearly twice the benefits of universal testing and treatment alone.
View details for PubMedID 20696960
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Cost-effective control of chronic viral diseases: Finding the optimal level of screening and contact tracing
MATHEMATICAL BIOSCIENCES
2010; 224 (1): 35-42
Abstract
Chronic viral diseases such as human immunodeficiency virus (HIV) and hepatitis B virus (HBV) afflict millions of people worldwide. A key public health challenge in managing such diseases is identifying infected, asymptomatic individuals so that they can receive antiviral treatment. Such treatment can benefit both the treated individual (by improving quality and length of life) and the population as a whole (through reduced transmission). We develop a compartmental model of a chronic, treatable infectious disease and use it to evaluate the cost and effectiveness of different levels of screening and contact tracing. We show that: (1) the optimal strategy is to get infected individuals into treatment at the maximal rate until the incremental health benefits balance the incremental cost of controlling the disease; (2) as one reduces the disease prevalence by moving people into treatment (which decreases the chance that they will infect others), one should increase the level of contact tracing to compensate for the decreased effectiveness of screening; (3) as the disease becomes less prevalent, it is optimal to spend more per case identified; and (4) the relative mix of screening and contact tracing at any level of disease prevalence is such that the marginal efficiency of contact tracing (cost per infected person found) equals that of screening if possible (e.g., when capacity limitations are not binding). We also show how to determine the cost-effective equilibrium level of disease prevalence (among untreated individuals), and we develop an approximation of the path of the optimal prevalence over time. Using this, one can obtain a close approximation of the optimal solution without having to solve an optimal control problem. We apply our methods to an example of hepatitis B virus.
View details for DOI 10.1016/j.mbs.2009.12.006
View details for Web of Science ID 000275310300005
View details for PubMedID 20043926
View details for PubMedCentralID PMC3235175
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Cost-Effectiveness of Nationwide Hepatitis B Catch-up Vaccination Among Children and Adolescents in China
HEPATOLOGY
2010; 51 (2): 405-414
Abstract
Liver disease and liver cancer associated with childhood-acquired chronic hepatitis B are leading causes of death among adults in China. Despite expanded newborn hepatitis B vaccination programs, approximately 20% of children under age 5 years and 40% of children aged 5 to 19 years remain unprotected from hepatitis B. Although immunizing them will be beneficial, no studies have examined the cost-effectiveness of hepatitis B catch-up vaccination in an endemic country like China. We examined the cost-effectiveness of a hypothetical nationwide free hepatitis B catch-up vaccination program in China for unvaccinated children and adolescents aged 1 to 19 years. We used a Markov model for disease progression and infections. Cost variables were based on data published by the Chinese Ministry of Health, peer-reviewed Chinese and English publications, and the GAVI Alliance. We measured costs (2008 U.S. dollars and Chinese renminbi), quality-adjusted life years, and incremental cost-effectiveness from a societal perspective. Our results show that hepatitis B catch-up vaccination for children and adolescents in China is cost-saving across a range of parameters, even for adolescents aged 15 to 19 years old. We estimate that if all 150 million susceptible children under 19 were vaccinated, more than 8 million infections and 65,000 deaths due to hepatitis B would be prevented.The adoption of a nationwide free catch-up hepatitis B vaccination program for unvaccinated children and adolescents in China, in addition to ongoing efforts to improve birth dose and newborn vaccination coverage, will be cost-saving and can generate significant population-wide health benefits. The success of such a program in China could serve as a model for other endemic countries.
View details for DOI 10.1002/hep.23310
View details for Web of Science ID 000274131200009
View details for PubMedID 19839061
View details for PubMedCentralID PMC3245734
- Cost-effective control of chronic viral diseases: Finding the optimal level of screening and contact tracing. Mathematical Biosciences 2010; 1 (224): 35-42.
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HEPATITIS AND LIVER CANCER A National Strategy for Prevention and Control of Hepatitis B and C Summary
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 1–17
View details for Web of Science ID 000352025500001
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HEPATITIS AND LIVER CANCER A National Strategy for Prevention and Control of Hepatitis B and C Introduction
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 19–40
View details for Web of Science ID 000352025500002
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Surveillance
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 41–78
View details for Web of Science ID 000352025500003
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Knowledge and Awareness About Chronic Hepatitis B and Hepatitis C
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 79–107
View details for Web of Science ID 000352025500004
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Immunization
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 109–45
View details for Web of Science ID 000352025500005
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Viral Hepatitis Services
HEPATITIS AND LIVER CANCER: A NATIONAL STRATEGY FOR PREVENTION AND CONTROL OF HEPATITIS B AND C
2010: 147–207
View details for Web of Science ID 000352025500006
- Cost-effectiveness of strategies for diagnosing pulmonary embolism among emergency department patients presenting with undifferentiated symptoms. Annals of Emergency Medicine 2010; 4 (56): 321-332.
- Comparative effectiveness of HIV testing and treatment in highly endemic regions. Archives of Internal Medicine 2010; 15 (17): 1347-1354.
- The cost effectiveness and population outcomes of expanded HIV screening and antiretroviral treatment in the United States. Annals of Internal Medicine 2010; 12 (153): 778-789.
- Institute of Medicine Committee on the Prevention and Control of Viral Hepatitis Infections. Hepatitis and Liver Cancer: A National Strategy for Prevention andControl of Hepatitis B and C. 2010
- Cost effectiveness of nationwide hepatitis B catchup vaccination among children and adolescents in China. Hepatology 2010; 2 (51): 405-414.
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Potential population health outcomes and expenditures of HIV vaccination strategies in the United States
VACCINE
2009; 27 (39): 5402-5410
Abstract
Estimating the potential health benefits and expenditures of a partially effective HIV vaccine is an important consideration in the debate about whether HIV vaccine research should continue. We developed an epidemic model to estimate HIV prevalence, new infections, and the cost-effectiveness of vaccination strategies in the U.S. Vaccines with modest efficacy could prevent 300,000-700,000 HIV infections and save $30 billion in healthcare expenditures over 20 years. Targeted vaccination of high-risk individuals is economically efficient, but difficulty in reaching these groups may mitigate these benefits. Universal vaccination is cost-effective for vaccines with 50% efficacy and price similar to other infectious disease vaccines.
View details for DOI 10.1016/j.vaccine.2009.06.063
View details for Web of Science ID 000269629800018
View details for PubMedID 19591796
View details for PubMedCentralID PMC2757634
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Recommendations for Modeling Disaster Responses in Public Health and Medicine: A Position Paper of the Society for Medical Decision Making
MEDICAL DECISION MAKING
2009; 29 (4): 438-460
Abstract
Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models.. The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making.. The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models.. Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.
View details for DOI 10.1177/0272989X09340346
View details for Web of Science ID 000268291200005
View details for PubMedID 19605887
View details for PubMedCentralID PMC3699691
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Optimal investment in HIV prevention programs: more is not always better
HEALTH CARE MANAGEMENT SCIENCE
2009; 12 (1): 27-37
Abstract
This paper develops a mathematical/economic framework to address the following question: Given a particular population, a specific HIV prevention program, and a fixed amount of funds that could be invested in the program, how much money should be invested? We consider the impact of investment in a prevention program on the HIV sufficient contact rate (defined via production functions that describe the change in the sufficient contact rate as a function of expenditure on a prevention program), and the impact of changes in the sufficient contact rate on the spread of HIV (via an epidemic model). In general, the cost per HIV infection averted is not constant as the level of investment changes, so the fact that some investment in a program is cost effective does not mean that more investment in the program is cost effective. Our framework provides a formal means for determining how the cost per infection averted changes with the level of expenditure. We can use this information as follows: When the program has decreasing marginal cost per infection averted (which occurs, for example, with a growing epidemic and a prevention program with increasing returns to scale), it is optimal either to spend nothing on the program or to spend the entire budget. When the program has increasing marginal cost per infection averted (which occurs, for example, with a shrinking epidemic and a prevention program with decreasing returns to scale), it may be optimal to spend some but not all of the budget. The amount that should be spent depends on both the rate of disease spread and the production function for the prevention program. We illustrate our ideas with two examples: that of a needle exchange program, and that of a methadone maintenance program.
View details for DOI 10.1007/s10729-008-9074-7
View details for Web of Science ID 000281584100003
View details for PubMedID 19938440
View details for PubMedCentralID PMC2786080
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Cost-effectiveness of voluntary HIV screening in Russia
INTERNATIONAL JOURNAL OF STD & AIDS
2009; 20 (1): 46-51
Abstract
Russia has one of the world's fastest growing HIV epidemics, and HIV screening has been widespread. Whether such screening is an effective use of resources is unclear. We used epidemiologic and economic data from Russia to develop a Markov model to estimate costs, quality of life and survival associated with a voluntary HIV screening programme compared with no screening in Russia. We measured discounted lifetime health-care costs and quality-adjusted life years (QALYs) gained. We varied our inputs in sensitivity analysis. Early identification of HIV through screening provided a substantial benefit to persons with HIV, increasing life expectancy by 2.1 years and 1.7 QALYs. At a base-case prevalence of 1.2%, once-per-lifetime screening cost $13,396 per QALY gained, exclusive of benefit from reduced transmission. Cost-effectiveness of screening remained favourable until prevalence dropped below 0.04%. When HIV-transmission-related costs and benefits were included, once-per-lifetime screening cost $6910 per QALY gained and screening every two years cost $27,696 per QALY gained. An important determinant of the cost-effectiveness of screening was effectiveness of counselling about risk reduction. Early identification of HIV infection through screening in Russia is effective and cost-effective in all but the lowest prevalence groups.
View details for DOI 10.1258/ijsa.2008.008128
View details for PubMedID 19103893
- OR’s next top model: Decision models for infectious disease control. In TutORials in Operations Research Institute for Operations Research and the Management Sciences (INFORMS). 2009: 123–138.
- Recommendations for modeling crisis response in public health and medicine: A position paper of the Society for Medical Decision Making. Medical Decision Making 2009; 4 (29): 438-460.
- Optimal investment in HIV prevention programs: More is not always better. Health Care Management Science 2009; 1 (12): 27-37.
- Cost-effectiveness of voluntary HIV screening in Russia. International Journal of STD and AIDS 2009; 1 (20): 46-51.
- Potential population health outcomes and expenditures of HIV vaccination strategies in the United States. Vaccine 2009; 39 (27): 5402-5410.
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Controlling Co-Epidemics: Analysis of HIV and Tuberculosis Infection Dynamics
OPERATIONS RESEARCH
2008; 56 (6): 1366-1381
Abstract
A co-epidemic arises when the spread of one infectious disease stimulates the spread of another infectious disease. Recently, this has happened with human immunodeficiency virus (HIV) and tuberculosis (TB). We develop two variants of a co-epidemic model of two diseases. We calculate the basic reproduction number (R(0)), the disease-free equilibrium, and the quasi-disease-free equilibria, which we define as the existence of one disease along with the complete eradication of the other disease, and the co-infection equilibria for specific conditions. We determine stability criteria for the disease-free and quasi-disease-free equilibria. We present an illustrative numerical analysis of the HIV-TB co-epidemics in India that we use to explore the effects of hypothetical prevention and treatment scenarios. Our numerical analysis demonstrates that exclusively treating HIV or TB may reduce the targeted epidemic, but can subsequently exacerbate the other epidemic. Our analyses suggest that coordinated treatment efforts that include highly active antiretroviral therapy for HIV, latent TB prophylaxis, and active TB treatment may be necessary to slow the HIV-TB co-epidemic. However, treatment alone may not be sufficient to eradicate both diseases. Increased disease prevention efforts (for example, those that promote condom use) may also be needed to extinguish this co-epidemic. Our simple model of two synergistic infectious disease epidemics illustrates the importance of including the effects of each disease on the transmission and progression of the other disease.
View details for DOI 10.1287/opre.1080.0571
View details for Web of Science ID 000263565300004
View details for PubMedCentralID PMC2675172
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Modeling the logistics of response to anthrax bioterrorism
MEDICAL DECISION MAKING
2008; 28 (3): 332-350
Abstract
A bioterrorism attack with an agent such as anthrax will require rapid deployment of medical and pharmaceutical supplies to exposed individuals. How should such a logistical system be organized? How much capacity should be built into each element of the bioterrorism response supply chain?The authors developed a compartmental model to evaluate the costs and benefits of various strategies for preattack stockpiling and postattack distribution and dispensing of medical and pharmaceutical supplies, as well as the benefits of rapid attack detection.The authors show how the model can be used to address a broad range of logistical questions as well as related, nonlogistical questions (e.g., the cost-effectiveness of strategies to improve patient adherence to antibiotic regimens). They generate several key insights about appropriate strategies for local communities. First, stockpiling large local inventories of medical and pharmaceutical supplies is unlikely to be the most effective means of reducing mortality from an attack, given the availability of national and regional supplies. Instead, communities should create sufficient capacity for dispensing prophylactic antibiotics in the event of a large-scale bioterror attack. Second, improved surveillance systems can significantly reduce deaths from such an attack but only if the local community has sufficient antibiotic-dispensing capacity. Third, mortality from such an attack is significantly affected by the number of unexposed individuals seeking prophylaxis and treatment. Fourth, full adherence to treatment regimens is critical for reducing expected mortality.Effective preparation for response to potential bioterror attacks can avert deaths in the event of an attack. Models such as this one can help communities more effectively prepare for response to potential bioterror attacks.
View details for DOI 10.1177/0272989X07312721
View details for Web of Science ID 000256264500006
View details for PubMedID 18349432
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An ounce of prevention is worth a pound of cure: improving communication to reduce mortality during bioterrorism responses.
American journal of disaster medicine
2008; 3 (2): 65-78
Abstract
To identify communication needs and evaluate the effectiveness of alternative communication strategies for bioterrorism responses.We provide a framework for evaluating communication needs during a bioterrorism response. Then, using a simulation model of a hypothetical response to anthrax bioterrorism in a large metropolitan area, we evaluate the costs and benefits of alternative strategies for communication during a response.Expected mortality increases significantly with increases in the time for attack detection and announcement; decreases in the rate at which exposed individuals seek and receive prophylaxis; increases in the number of unexposed people seeking prophylaxis; and increases in workload imbalances at dispensing centers. Thus, the timeliness, accuracy, and precision of communications about the mechanisms of exposure and instructions for obtaining prophylaxis and treatment are critical. Investment in strategies that improve adherence to prophylaxis is likely to be highly cost effective, even if the improvement in adherence is modest, and even if such strategies reduce the prophylaxis dispensing rate.Communication during the response to a bioterror attack must involve the right information delivered at the appropriate time in an effective manner from trusted sources. Because the response system for bioterror communication is only fully operationalized once an attack has occurred, tabletop planning and simulation exercises, and other up-front investments in the design of an effective communication strategy, are critical for effective response planning.
View details for PubMedID 18522248
- An ounce of prevention is worth a pound of cure: Improving communication to reduce mortality during bioterrorism responses. American Journal of Disaster Medicine 2008; 2 (3): 65-78.
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INFECTIOUS DISEASE CONTROL POLICY: A ROLE FOR SIMULATION
2008 WINTER SIMULATION CONFERENCE, VOLS 1-5
2008: 1578-1582
View details for Web of Science ID 000274496200191
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Optimal Spending on HIV Prevention and Treatment: A Framework for Evaluating Cost-Effectiveness with Example Application to the India AIDS Initiative
OPTIMIZATION IN MEDICINE AND BIOLOGY
2008: 147–75
View details for Web of Science ID 000268012400005
- Optimal spending on HIV prevention and treatment: A framework for evaluating the cost-effectiveness of HIV prevention and treatment programs with example application to The India AIDS Initiative. In Optimization in Medicine and Biology Taylor and Francis Publishers, Boca Raton, Florida. 2008: 147–175.
- Modeling the logistics of response to anthrax bioterrorism. Medical Decision Making 2008; 3 (28): 332-350.
- Infectious disease control policy: A role for simulation. 2008
- The cost effectiveness of counseling strategies to improve adherence to highly active antiretroviral therapy among men who have sex with men. Medical Decision Making 2008; 3 (28): 359-376.
- Controlling co-epidemics: Analysis of HIV and tuberculosis infection dynamics. Operations Research 2008; 6 (56): 1366-1381.
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Contact tracing to control infectious disease: when enough is enough.
Health care management science
2007; 10 (4): 341-355
Abstract
Contact tracing (also known as partner notification) is a primary means of controlling infectious diseases such as tuberculosis (TB), human immunodeficiency virus (HIV), and sexually transmitted diseases (STDs). However, little work has been done to determine the optimal level of investment in contact tracing. In this paper, we present a methodology for evaluating the appropriate level of investment in contact tracing. We develop and apply a simulation model of contact tracing and the spread of an infectious disease among a network of individuals in order to evaluate the cost and effectiveness of different levels of contact tracing. We show that contact tracing is likely to have diminishing returns to scale in investment: incremental investments in contact tracing yield diminishing reductions in disease prevalence. In conjunction with a cost-effectiveness threshold, we then determine the optimal amount that should be invested in contact tracing. We first assume that the only incremental disease control is contact tracing. We then extend the analysis to consider the optimal allocation of a budget between contact tracing and screening for exogenous infection, and between contact tracing and screening for endogenous infection. We discuss how a simulation model of this type, appropriately tailored, could be used as a policy tool for determining the appropriate level of investment in contact tracing for a specific disease in a specific population. We present an example application to contact tracing for chlamydia control.
View details for PubMedID 18074967
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Cost-effectiveness of screening and vaccinating Asian and pacific islander adults for hepatitis B
ANNALS OF INTERNAL MEDICINE
2007; 147 (7): 460-469
Abstract
As many as 10% of Asian and Pacific Islander adults in the United States are chronically infected with hepatitis B virus (HBV), and up to two thirds are unaware that they are infected. Without proper medical management and antiviral therapy, up to 25% of Asian and Pacific Islander persons with chronic HBV infection will die of liver disease.To assess the cost-effectiveness of 4 HBV screening and vaccination programs for Asian and Pacific Islander adults in the United States.Markov model with costs and benefits discounted at 3%.Published literature and expert opinion.Asian and Pacific Islander adults (base-case age, 40 years; sensitivity analysis conducted on ages 20 to 60 years).Lifetime.U.S. societal.A universal vaccination strategy in which all individuals are given a 3-dose vaccination series; a screen-and-treat strategy, in which individuals are given blood tests to determine whether they are chronically infected, and infected persons are monitored and treated; a screen, treat, and ring vaccinate strategy, in which all individuals are tested for chronic HBV infection and close contacts of infected persons are screened and vaccinated if needed; and a screen, treat, and vaccinate strategy, in which all individuals are tested and then vaccinated with a 3-dose series if needed. In all cases, persons found to be chronically infected are monitored and treated if indicated.Costs (2006 U.S. dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness.Compared with the status quo, the screen-and-treat strategy has an incremental cost-effectiveness ratio of $36,088 per QALY gained. The screen, treat, and ring vaccinate strategy gains more QALYs than the screen and treat strategy and incurs modest incremental costs, leading to incremental cost-effectiveness of $39,903 per QALY gained compared with the screen and treat strategy. The universal vaccination and screen, treat, and vaccinate strategies were weakly dominated by the other 2 strategies.Over a wide range of variables, the incremental cost-effectiveness ratios of the screen and treat and screen, treat, and ring vaccinate strategies were less than $50,000 per QALY gained.Results depend on the accuracy of the underlying data and assumptions. The long-term effectiveness of new and future HBV treatments is uncertain.Screening programs for HBV among Asian and Pacific Islander adults are likely to be cost effective. Clinically significant benefits accrue from identifying chronically infected persons for medical management and vaccinating their close contacts. Such efforts can greatly reduce the burden of HBV-associated liver cancer and chronic liver disease in the Asian and Pacific Islander population.
View details for Web of Science ID 000250214700003
View details for PubMedID 17909207
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Optimal mix of screening and contact tracing for endemic diseases
MATHEMATICAL BIOSCIENCES
2007; 209 (2): 386-402
Abstract
Two common means of controlling infectious diseases are screening and contact tracing. Which should be used, and when? We consider the problem of determining the cheapest mix of screening and contact tracing necessary to achieve a desired endemic prevalence of a disease or to identify a specified number of cases. We perform a partial equilibrium analysis of small-scale interventions, assuming that prevalence is unaffected by the intervention; we develop a full equilibrium analysis where we compare the long-term cost of various combinations of screening and contact tracing needed to achieve a given equilibrium prevalence; and we solve the problem of minimizing the total costs of identifying and treating disease cases plus the cost of untreated disease cases. Our analysis provides several insights. First, contact tracing is only cost effective when prevalence is below a threshold value. This threshold depends on the relative cost per case found by screening versus contact tracing. Second, for a given contact tracing policy, the screening rate needed to achieve a given prevalence or identify a specified number of cases is a decreasing function of disease prevalence. As prevalence increases above the threshold (and contact tracing is discontinued), the screening rate jumps discontinuously to a higher level. Third, these qualitative results hold when we consider unchanged or changed prevalence, and short-term or long-term costs.
View details for DOI 10.1016/j.mbs.2007.02.007
View details for Web of Science ID 000250330600004
View details for PubMedID 17428503
View details for PubMedCentralID PMC3089719
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Planning the bioterrorism response supply chain: learn and live.
American journal of disaster medicine
2007; 2 (5): 231-247
Abstract
Responses to bioterrorism require rapid procurement and distribution of medical and pharmaceutical supplies, trained personnel, and information. Thus, they present significant logistical challenges. On the basis of a review of the manufacturing and service supply chain literature, the authors identified five supply chain strategies that can potentially increase the speed of response to a bioterrorism attack, reduce inventories, and save money: effective supply chain network design; effective inventory management; postponement of product customization and modularization of component parts; coordination of supply chain stakeholders and appropriate use of incentives; and effective information management. The authors describe how concepts learned from published evaluations of manufacturing and service supply chains, as well as lessons learned from responses to natural disasters, naturally occurring outbreaks, and the 2001 US anthrax attacks, can be applied to design, evaluate, and improve the bioterrorism response supply chain. Such lessons could also be applied to the response supply chains for disease outbreaks and natural and manmade disasters.
View details for PubMedID 18491839
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A knowledge representation of local pandemic influenza planning models.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
2007: 988-?
Abstract
Planning for pandemic flu outbreak at the small-government level can be aided through the use of mathematical policy models. Formulating and analyzing policy models, however, can be a time- and expertise-expensive process. We believe that a knowledge-based system for facilitating the instantiation of locale- and problem-specific policy models can reduce some of these costs. In this work, we present the ontology we have developed for pandemic influenza policy models.
View details for PubMedID 18694088
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A little planning goes a long way: Multilevel allocation of HIV prevention resources
MEDICAL DECISION MAKING
2007; 27 (1): 71-81
Abstract
HIV prevention funds are often allocated by decision makers at multiple levels. High-level decision makers may allocate funds to regions, and regional decision makers then allocate those funds to specific programs. Often, funds are allocated proportionally (e.g., in proportion to HIV incidence) rather than efficiently (i.e., to maximize HIV infections averted). The authors investigate the impact of efficient and proportional allocation methods at 2 different decision levels.The authors developed an optimization model of resource allocation at 2 levels-an aggregate upper level and multiple local levels-and considered efficient allocation and allocation proportional to HIV incidence. Using data from 40 U.S. states, they compared 4 strategies for allocating HIV prevention funds.The greatest health benefit (HIV infections averted) occurred when efficient allocations were made at both levels. When funds were allocated proportionally at the higher level and efficiently at the lower level, the health benefit was about 5% less than when efficient allocations were made at both levels. When funds were allocated efficiently at the higher level and proportionally at the lower level, the health benefit was 15% less than when efficient allocations were made at both levels. The least health benefit (23% less than when efficient allocations were made at both levels) occurred with proportional allocation at both levels.Efficient allocation only at the higher level cannot overcome poor allocations at lower levels. Moreover, efficient allocation at the lower level is likely to yield greater gains than efficient allocation at the higher level. Thus, upper-level decision makers, such as donor organizations, should develop incentives to promote efficient allocation by lower-level decision makers.
View details for DOI 10.1177/0272989X06297395
View details for Web of Science ID 000243911200008
View details for PubMedID 17237455
- Planning the bioterrorism responsesupply chain: Learn and live. American Journal of Disaster edicine 2007; 5 (2): 231-247.
- Who do you know? A simulation study of infectious disease control through contact tracing. 2007
- From Venn diagrams to bioterrorism: An OR journey. The Operations Research Center at MIT. INFORMS Topics in Operations Research Series 2007: 41-46.
- Cost effectiveness of screening and vaccinating Asian and Pacific Islander adults for hepatitis B. Annals of Internal Medicine 2007; 7 (14): 460-469.
- A little planning goes a long way: Multi-level allocation of HIV prevention resources. Medical Decision Making 2007; 1 (27): 71-81.
- Contact tracing to control infectious disease: When enough is enough. Health Care Management Science 2007; 4 (10): 341-355.
- Optimal mix of screening and contact tracing for endemic diseases. Mathematical Biosciences 2007; 2 (209): 386-402.
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Effectiveness and cost-effectiveness of strategies to expand antiretroviral therapy in St. Petersburg, Russia
AIDS
2006; 20 (17): 2207-2215
Abstract
To assess the effectiveness and cost-effectiveness of treating HIV-infected injection drug users (IDUs) and non-IDUs in Russia with highly active antiretroviral therapy HAART.A dynamic HIV epidemic model was developed for a population of IDUs and non-IDUs. The location for the study was St. Petersburg, Russia. The adult population aged 15 to 49 years was subdivided on the basis of injection drug use and HIV status. HIV treatment targeted to IDUs and non-IDUs, and untargeted treatment interventions were considered. Health care costs and quality-adjusted life years (QALYs) experienced in the population were measured, and HIV prevalence, HIV infections averted, and incremental cost-effectiveness ratios of different HAART strategies were calculated.With no incremental HAART programs, HIV prevalence reached 64% among IDUs and 1.7% among non-IDUs after 20 years. If treatment were targeted to IDUs, over 40 000 infections would be prevented (75% among non-IDUs), adding 650 000 QALYs at a cost of USD 1501 per QALY gained. If treatment were targeted to non-IDUs, fewer than 10 000 infections would be prevented, adding 400 000 QALYs at a cost of USD 2572 per QALY gained. Untargeted strategies prevented the most infections, adding 950 000 QALYs at a cost of USD 1827 per QALY gained. Our results were sensitive to HIV transmission parameters.Expanded use of antiretroviral therapy in St. Petersburg, Russia would generate enormous population-wide health benefits and be economically efficient. Exclusively treating non-IDUs provided the least health benefit, and was the least economically efficient. Our findings highlight the urgency of initiating HAART for both IDUs and non-IDUs in Russia.
View details for PubMedID 17086061
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Value of quantitative D-dimer assays in identifying pulmonary embolism: Implications from a sequential decision model
ACADEMIC EMERGENCY MEDICINE
2006; 13 (7): 755-766
Abstract
To examine the cost-effectiveness of a quantitative D-dimer assay for the evaluation of patients with suspected pulmonary embolism (PE) in an urban emergency department (ED).The authors analyzed different diagnostic strategies over pretest risk categories on the basis of Wells criteria by using the performance profile of the ELISA D-dimer assay (over five cutoff values) and imaging strategies used in the ED for PE: compression ultrasound (CUS), ventilation-perfusion (VQ) scan (over three cutoff values), CUS with VQ (over three cutoff values), computed tomography (CT) angiogram (CTA) with pulmonary portion (CTP) and lower-extremity venous portion, and CUS with CTP. Data used in the analysis were based on literature review. Incremental costs and quality-adjusted-life-years were the outcomes measured.Computed tomography angiogram with pulmonary portion and lower-extremity venous portion without D-dimer was the preferred strategy. CUS-VQ scanning always was dominated by CT-based strategies. When CTA was infeasible, the dominant strategy was D-dimer with CUS-VQ in moderate- and high-Wells patients and was D-dimer with CUS for low-Wells patients. When CTP specificity falls below 80%, or if its overall performance is markedly degraded, preferred strategies include D-dimer testing. Sensitivity analyses suggest that pessimistic assessments of CTP accuracy alter the results only at extremes of parameter settings.In patients in whom PE is suspected, when CTA is available, even the most sensitive quantitative D-dimer assay is not likely to be cost-effective. When CTA is not available or if its performance is markedly degraded, use of the D-dimer assay has value in combination with CUS and a pulmonary imaging study. These conclusions may not hold for the larger domain of patients presenting to the ED with chest pain or shortness of breath in whom PE is one of many competing diagnoses.
View details for DOI 10.1197/j.aem.2006.02.011
View details for Web of Science ID 000239051800008
View details for PubMedID 16723725
- Reducing mortality from anthrax bioterrorism: Strategies for stockpiling and dispensing medical and pharmaceutical supplies. Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science 2006; 3 (4): 244-262.
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Reducing mortality from anthrax bioterrorism: Strategies for stockpiling and dispensing medical and pharmaceutical supplies
BIOSECURITY AND BIOTERRORISM-BIODEFENSE STRATEGY PRACTICE AND SCIENCE
2006; 4 (3): 244-262
Abstract
A critical question in planning a response to bioterrorism is how antibiotics and medical supplies should be stockpiled and dispensed. The objective of this work was to evaluate the costs and benefits of alternative strategies for maintaining and dispensing local and regional inventories of antibiotics and medical supplies for responses to anthrax bioterrorism. We modeled the regional and local supply chain for antibiotics and medical supplies as well as local dispensing capacity. We found that mortality was highly dependent on the local dispensing capacity, the number of individuals requiring prophylaxis, adherence to prophylactic antibiotics, and delays in attack detection. For an attack exposing 250,000 people and requiring the prophylaxis of 5 million people, expected mortality fell from 243,000 to 145,000 as the dispensing capacity increased from 14,000 to 420,000 individuals per day. At low dispensing capacities (<14,000 individuals per day), nearly all exposed individuals died, regardless of the rate of adherence to prophylaxis, delays in attack detection, or availability of local inventories. No benefit was achieved by doubling local inventories at low dispensing capacities; however, at higher dispensing capacities, the cost-effectiveness of doubling local inventories fell from 100,000 US dollars to 20,000 US dollars/life year gained as the annual probability of an attack increased from 0.0002 to 0.001. We conclude that because of the reportedly rapid availability of regional inventories, the critical determinant of mortality following anthrax bioterrorism is local dispensing capacity. Bioterrorism preparedness efforts directed at improving local dispensing capacity are required before benefits can be reaped from enhancing local inventories.
View details for PubMedID 16999586
- Value of quantitative D-dimer assays in identifying pulmonary embolism: Implications from a sequential decision model. Academic Emergency Medicine 2006; 7 (13): 755-766.
- Effectiveness and cost-effectiveness of strategies to expand antiretroviral therapy in St.Petersburg, Russia. AIDS 2006; 17 (20): 2207-2215.
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Modeling complex medical decision problems with the Archimedes model
ANNALS OF INTERNAL MEDICINE
2005; 143 (4): 303-304
View details for DOI 10.7326/0003-4819-143-4-200508160-00012
View details for Web of Science ID 000231237100008
View details for PubMedID 16103475
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Improved allocation of HIV prevention resources: using information about prevention program production functions.
Health care management science
2005; 8 (1): 19-28
Abstract
To allocate HIV prevention resources effectively, it is important to have information about the effectiveness of alternative prevention programs as a function of expenditure. We refer to this relationship as the "production function" for a prevention program. Few studies of HIV prevention programs have reported this relationship. This paper demonstrates the value of such information. We present a simple model for allocating HIV prevention resources, and apply the model to an illustrative HIV prevention resource allocation problem. We show that, without sufficient information about prevention program production functions, suboptimal decisions may be made. We show that epidemiologic data, such as estimates of HIV prevalence or incidence, may not provide enough information to support optimal allocation of HIV prevention resources. Our results suggest that good allocations can be obtained based on fairly basic information about prevention program production functions: an estimate of fixed cost plus a single estimate of cost and resulting risk reduction. We find that knowledge of production functions is most important when fixed cost is high and/or when the budget is a significantly constraining factor. We suggest that, at the minimum, future data collection on prevention program effectiveness should include fixed and variable cost estimates for the intervention when implemented at a "typical" level, along with a detailed description of the intervention and detailed description of costs by category.
View details for PubMedID 15782509
- Evaluating the cost effectiveness of the India AIDS Initiative: A blueprint. White Paper, Gates Foundation Policy Research Network 2005
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ALLOCATING RESOURCES TO CONTROL INFECTIOUS DISEASES
OPERATIONS RESEARCH AND HEALTH CARE: A HANDBOOK OF METHODS AND APPLICATIONS
2005; 70: 443-464
View details for DOI 10.1007/1-4020-8066-2_17
View details for Web of Science ID 000270672800017
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HEALTH CARE DELIVERY: CURRENT PROBLEMS AND FUTURE CHALLENGES
OPERATIONS RESEARCH AND HEALTH CARE: A HANDBOOK OF METHODS AND APPLICATIONS
2005; 70: 1-14
View details for DOI 10.1007/1-4020-8066-2_1
View details for Web of Science ID 000270672800001
- Global HIV prevention and treatment: Planning for the future. White Paper, Gates Foundation Policy Research Network 2005
- Modeling complex medical decision problems with the Archimedes model [Editorial]. Annals of Internal Medicine 2005; 4 (143): 303-304.
- Improved allocation of HIV prevention resources: Using information about prevention program production functions. Health Care Management Science 2005; 1 (8): 19-28.
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Regionalization of bioterrorism preparedness and response.
Evidence report/technology assessment (Summary)
2004: 1-7
View details for PubMedID 15133889
- Regionalization of bioterrorism preparedness and response [Summary]. Evidence Report/Technology Assessment 2004: 96, 1-7.
- Allocating resources to control infectious diseases. In Operations Research and Health Care: A Handbook of Methods and Applications Kluwer Academic Publishers. 2004: 443–464.
- Operations Research and Health Care: A Handbook of Methods and Applications. edited by Brandeau, M., L., Sainfort, F., Pierskalla, W., P. Kluwer Academic Publishers, Norwell, MA. 2004
- Health care delivery: Current problems and future challenges. In Operations Research and Health Care: A Handbook of Methods and Applications Kluwer Academic Publishers. 2004: 1–14.
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Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis
JOURNAL OF HEALTH ECONOMICS
2003; 22 (4): 575-598
Abstract
Traditional cost-effectiveness analysis (CEA) assumes that program costs and benefits scale linearly with investment-an unrealistic assumption for epidemic control programs. This paper combines epidemic modeling with optimization techniques to determine the optimal allocation of a limited resource for epidemic control among multiple noninteracting populations. We show that the optimal resource allocation depends on many factors including the size of each population, the state of the epidemic in each population before resources are allocated (e.g. infection prevalence and incidence), the length of the time horizon, and prevention program characteristics. We establish conditions that characterize the optimal solution in certain cases.
View details for DOI 10.1016/S0167-6296(03)00043-2
View details for Web of Science ID 000184078500004
View details for PubMedID 12842316
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The cost effectiveness of improved adherence to antiretroviral treatment
ELSEVIER SCIENCE INC. 2003: 266–66
View details for Web of Science ID 000183419000219
- Resource allocation for control of infectious diseases in multiple independent populations: Beyond cost-effectiveness analysis. Journal of Health Economics 2003; 4 (22): 575-598.
- Regionalization of Bioterrorism Preparedness and Response Evidence Report/Technology Assessment) Agency for Healthcare Research and Quality, Rockville, MD 2003
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Dynamic resource allocation for epidemic control in multiple populations
IMA JOURNAL OF MATHEMATICS APPLIED IN MEDICINE AND BIOLOGY
2002; 19 (4): 235-255
Abstract
We develop a dynamic resource allocation model in which a limited budget for epidemic control is allocated over multiple time periods to interventions that affect multiple populations. For certain special cases with two time periods, multiple independent populations, and a linear relationship between investment in a prevention programme and the resulting change in risky behaviour, we demonstrate that the optimal solution involves investing in each period as much as possible in some of the populations and nothing in all the other populations. We present heuristic algorithms for solving the general problem, and present numerical results. Our computational analyses suggest that good allocations can be made based on some fairly simple heuristics. Our analyses also suggest that allowing for some reallocation of resources over the time horizon of the problem, rather than allocating resources just once at the beginning of the time horizon, can lead to significant increases in health benefits. Allowing for reallocation of funds may generate more health benefits than use of a sophisticated model for one-time allocation of resources.
View details for Web of Science ID 000183092500001
View details for PubMedID 12828363
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Optimal pricing for service facilities with self-optimizing customers
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
2002; 141 (1): 39-57
View details for Web of Science ID 000176278000004
- Optimal pricing for service facilities with self-optimizing customers. European Journal of Operational Research 2002; 1 (141): 39-57.
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Difficult choices, urgent needs: Optimal investment in HIV prevention programs
14th Conference on Quantitative Evaluation of HIV Prvention Programs
YALE UNIV PRESS. 2002: 97–117
View details for Web of Science ID 000180918400005
- Dynamic resource allocation for epidemic control in multiple populations. IMA Journal of Mathematics Applied to Medicine and Biology 2002; 4 (19): 235-255.
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Optimal investment in a portfolio of HIV prevention programs
MEDICAL DECISION MAKING
2001; 21 (5): 391-408
Abstract
In this article, the authors determine the optimal allocation of HIV prevention funds and investigate the impact of different allocation methods on health outcomes.The authors present a resource allocation model that can be used to determine the allocation of HIV prevention funds that maximizes quality-adjusted life years (or life years) gained or HIV infections averted in a population over a specified time horizon. They apply the model to determine the allocation of a limited budget among 3 types of HIV prevention programs in a population of injection drug users and nonusers: needle exchange programs, methadone maintenance treatment, and condom availability programs. For each prevention program, the authors estimate a production function that relates the amount invested to the associated change in risky behavior.The authors determine the optimal allocation of funds for both objective functions for a high-prevalence population and a low-prevalence population. They also consider the allocation of funds under several common rules of thumb that are used to allocate HIV prevention resources. It is shown that simpler allocation methods (e.g., allocation based on HIV incidence or notions of equity among population groups) may lead to alloctions that do not yield the maximum health benefit.The optimal allocation of HIV prevention funds in a population depends on HIV prevalence and incidence, the objective function, the production functions for the prevention programs, and other factors. Consideration of cost, equity, and social and political norms may be important when allocating HIV prevention funds. The model presented in this article can help decision makers determine the health consequences of different allocations of funds.
View details for Web of Science ID 000170925300006
View details for PubMedID 11575489
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The cost-effectiveness of buprenorphine maintenance therapy for opiate addiction in the United States
ADDICTION
2001; 96 (9): 1267-1278
Abstract
To determine the cost-effectiveness of buprenorphine maintenance therapy for opiate addiction in the United States, particularly its effect on the HIV epidemic.We developed a dynamic model to capture the effects of adding buprenorphine maintenance to the current opiate dependence treatment system. We evaluated incremental costs, including all health-care costs, and incremental effectiveness, measured as quality-adjusted life years (QALYs) of survival. We considered communities with HIV prevalence among injection drug users of 5% and 40%. Because no price has been set in the United States for a dose of buprenorphine, we considered three prices per dose: $5, $15, and $30.If buprenorphine increases the number of individuals in maintenance treatment by 10%, but does not affect the number of individuals receiving methadone maintenance, the cost-effectiveness ratios for buprenorphine maintenance therapy are less than $45 000 per QALY gained for all prices, in both the low-prevalence and high-prevalence communities. If the same number of individuals enter buprenorphine maintenance (10% of the number currently in methadone), but half are injection drug users newly entering maintenance and half are individuals who switched from methadone to buprenorphine, the cost-effectiveness ratios in both communities are less than $45 000 per QALY gained for the $5 and $15 prices, and greater than $65 000 per QALY gained for the $30 price.At a price of $5 or less per dose, buprenorphine maintenance is cost-effective under all scenarios we considered. At $15 per dose, it is cost-effective if its adoption does not lead to a net decline in methadone use, or if a medium to high value is assigned to the years of life lived by injection drug users and those in maintenance therapy. At $30 per dose, buprenorphine will be cost-effective only under the most optimistic modeling assumptions.
View details for Web of Science ID 000171019400006
View details for PubMedID 11672491
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Cost minimization and workload balancing in printed circuit board assembly
IIE TRANSACTIONS
2001; 33 (7): 547-557
View details for Web of Science ID 000168539900002
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Resource allocation for epidemic control over short time horizons
MATHEMATICAL BIOSCIENCES
2001; 171 (1): 33-58
Abstract
We present a model for allocation of epidemic control resources among a set of interventions. We assume that the epidemic is modeled by a general compartmental epidemic model, and that interventions change one or more of the parameters that describe the epidemic. Associated with each intervention is a 'production function' that relates the amount invested in the intervention to values of parameters in the epidemic model. The goal is to maximize quality-adjusted life years gained or the number of new infections averted over a fixed time horizon, subject to a budget constraint. Unlike previous models, our model allows for interacting populations and non-linear interacting production functions and does not require a long time horizon. We show that an analytical solution to the model may be difficult or impossible to derive, even for simple cases. Therefore, we derive a method of approximating the objective functions. We use the approximations to gain insight into the optimal resource allocation for three problem instances. We also develop heuristics for solving the general resource allocation problem. We present results of numerical studies using our approximations and heuristics. Finally, we discuss implications and applications of this work.
View details for Web of Science ID 000168504800003
View details for PubMedID 11325383
- Cost minimization and workload balancing in printed circuit board assembly. IIE Transactions 2001; 7 (33): 547-557.
- The cost-effectiveness of buprenorphine maintenance therapy for opiate addiction in the United States. Addiction 2001; 9 (96): 1267-1278.
- AIDS policy modeling for the 21st century: An overview of key issues. Health Care Management Science 2001; 3 (4): 165-180.
- Optimal investment in a portfolio of HIV prevention programs. Medical Decision Making 2001; 5 (21): 391-408.
- Resource allocation for epidemic control over short time horizons. Mathematical Biosciences 2001; 1 (171): 33-58.
- Difficult choices, urgent needs: Optimal investment in HIV prevention programs. In Quantitative Evaluation of HIV Prevention Programs Yale University Press, New Haven. 2001: 128–153.
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The cost effectiveness of voluntary prenatal and routine newborn HIV screening in the United States
JOURNAL OF ACQUIRED IMMUNE DEFICIENCY SYNDROMES
2000; 25 (5): 403-416
Abstract
To evaluate the cost effectiveness of voluntary prenatal and routine postnatal HIV screening in the cohort of pregnant women and newborns in the United States.Cost-effectiveness analysis. We developed a decision model to analyze the cost effectiveness of enhanced prenatal screening and routine newborn screening for HIV. We also analyzed the incremental cost effectiveness of routine newborn screening when improved voluntary prenatal screening is already in place.Analysis of the cohort of pregnant women and newborns in the United States.Enhanced prenatal screening, or routine newborn screening for HIV.Infections averted, life expectancy, costs, and incremental cost effectiveness.Improved participation in voluntary prenatal HIV screening would result in an additional 1.1 million women being screened annually, would identify an additional 527 HIV-infected mothers annually, would avert 150 infections in newborns, and would cost $8,900 U.S. per life-year gained. Routine newborn HIV screening would test 3.9 million infants annually, would identify 1061 HIV-infected mothers, would avert 266 infections in newborns, and would cost $7,000 U.S. per life-year gained. If improved voluntary prenatal screening is already in place, routine newborn screening would avert an additional 135 infections in newborns, at an incremental cost of $10, 600 U.S. per life-year gained. The screening programs are likely to be cost effective over a wide range of assumptions regarding key factors in the analysis.Improved voluntary prenatal HIV screening of women and routine screening of newborns are cost effective. Routine newborn screening becomes less attractive as the rate of voluntary prenatal screening increases. Improved participation in voluntary prenatal screening has the added benefit that mothers maintain their right to determine whether they are tested for HIV.
View details for Web of Science ID 000166017000004
View details for PubMedID 11141240
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Methadone maintenance and HIV prevention: A cost-effectiveness analysis
MANAGEMENT SCIENCE
2000; 46 (8): 1013-1031
View details for Web of Science ID 000088961000001
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HIV transmission and the cost-effectiveness of methadone maintenance
AMERICAN JOURNAL OF PUBLIC HEALTH
2000; 90 (7): 1100-1111
Abstract
This study determined the cost-effectiveness of expanding methadone maintenance treatment for heroin addiction, particularly its effect on the HIV epidemic.We developed a dynamic epidemic model to study the effects of increased methadone maintenance capacity on health care costs and survival, measured as quality-adjusted life-years (QALYs). We considered communities with HIV prevalence among injection drug users of 5% and 40%.Additional methadone maintenance capacity costs $8200 per QALY gained in the high-prevalence community and $10,900 per QALY gained in the low-prevalence community. More than half of the benefits are gained by individuals who do not inject drugs. Even if the benefits realized by treated and untreated injection drug users are ignored, methadone maintenance expansion costs between $14,100 and $15,200 per QALY gained. Additional capacity remains cost-effective even if it is twice as expensive and half as effective as current methadone maintenance slots.Expansion of methadone maintenance is cost-effective on the basis of commonly accepted criteria for medical interventions. Barriers to methadone maintenance deny injection drug users access to a cost-effective intervention that generates significant health benefits for the general population.
View details for Web of Science ID 000087810000017
View details for PubMedID 10897189
View details for PubMedCentralID PMC1446290
- Optimal commonality in component design. Operations Research 2000; 1 (48): 1-19.
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Optimal commonality in component design
OPERATIONS RESEARCH
2000; 48 (1): 1-19
View details for Web of Science ID 000086464300001
- Methadone maintenance and HIV prevention: A costeffectiveness analysis. Management Science 2000; 8 (46): 1013-1031.
- HIV transmission and the cost-effectiveness of methadone maintenance. American Journal of Public Health 2000; 7 (90): 1100-1111.
- The cost effectiveness of voluntary prenatal and routine newborn HIV screening in th United States. Journal of AIDS and Human Retrovirology 2000; 5 (25): 403-416.
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An analysis of optimal resource allocation for prevention of infection with human immunodeficiency virus (HIV) in injection drug users and non-users
MEDICAL DECISION MAKING
1999; 19 (2): 167-179
Abstract
Millions of dollars are spent annually to prevent infection with human immunodeficiency virus (HIV) without a thorough understanding of the most effective way to allocate these resources. The authors' objective was to determine the allocation of new resources among prevention programs targeted to a population of injection drug users (IDUs) and a population of non-injection drug users (non-IDUs) that would minimize the total number of incident cases of HIV infection over a given time horizon. They developed a dynamic model of HIV transmission in IDUs and non-IDUs and estimated the relationship between prevention program expenditures and reductions in HIV transmission. They evaluated three prevention programs: HIV testing with routine counseling, HIV testing with intensive counseling, and HIV testing and counseling linked to methadone maintenance programs. They modeled a low-risk IDU population (5% HIV prevalence) and a moderate-risk IDU population (10% HIV prevalence). For different available budgets, they determined the allocation of resources among the prevention programs and populations that would minimize the number of new cases of HIV infection over a five-year period, as well as the incremental value of additional prevention funds. The study framework provides a quantitative, systematic approach to funding programs to prevent HIV infection that accounts for HIV transmission dynamics, population size, and the costs and effectiveness of the interventions in reducing HIV transmission. The approach is general and can be used to evaluate a broader group of prevention programs and risk populations. This framework thus could enable policy makers and clinicians to identify a portfolio of programs that provide, collectively, the most benefit for a given budget.
View details for Web of Science ID 000079539000007
View details for PubMedID 10231079
- An analysis of optimal resource allocation for prevention of infection with human immunodeficiency virus in jection drug users and non-users. Medical Decision Making, 1999; 2 (19): 167-179.
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Design of an automated shop floor material handling system with inventory considerations
OPERATIONS RESEARCH
1999; 47 (1): 65-80
View details for Web of Science ID 000082320600008
- Design of an automated shop floor material handling system with inventory considerations. Operations Research 1999; 1 (47): 65-80
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The effects of protease inhibitors on the spread of HIV and the development of drug-resistant HIV strains: A simulation study
SIMULATION
1998; 71 (4): 262-275
View details for Web of Science ID 000078219200006
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Optimal component assignment and board grouping in printed circuit board manufacturing
OPERATIONS RESEARCH
1998; 46 (5): 675-689
View details for Web of Science ID 000084981000006
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Effect of relapse to high-risk behavior on the costs and benefits of a program to screen women for human immunodeficiency virus
INTERFACES
1998; 28 (3): 52-74
View details for Web of Science ID 000075316200005
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OR modeling and AIDS policy: From theory to practice
INTERFACES
1998; 28 (3): 3-22
View details for Web of Science ID 000075316200002
- OR modeling and AIDS policy: From theory to practice. Interfaces 1998; 3 (28): 3-22.
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Note. Optimal storage assignment policies for automated storage and retrieval systems with stochastic demands
MANAGEMENT SCIENCE
1998; 44 (1): 142-148
View details for Web of Science ID 000072627200009
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Simulating the effects of protease inhibitors on the HIV epidemic: Treatment, compliance, and drug resistance
Medical Sciences Simulation Conference held at the 1998 Western MultiConference
SOC MODELING SIMULATION INT-SCS. 1998: 65–72
View details for Web of Science ID 000082161100011
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Using simulation to find optimal funding levels for HIV prevention programs with different costs and effectiveness
Medical Sciences Simulation Conference held at the 1998 Western MultiConference
SOC MODELING SIMULATION INT-SCS. 1998: 58–64
View details for Web of Science ID 000082161100010
- Effects of relapse to high-risk behavior on the costs andbenefits of a voluntary program to screen women for HIV. Interfaces 1998; 3 (28): 52-74.
- Note: Optimal storage assignment policies for automated storage and retrieval systems with stochastic demands. Management Science 1998; 1 (44): 142-148.
- Using simulation to find optimal funding levels for HIV prevention programs with different costs and effectiveness. 1998
- Optimal component assignment and board grouping in printed circuit board manufacturing. Operations Research 1998; 5 (46): 675-689.
- The effects of protease inhibitors on the spread of HIV and the development of drug-resistant HIV strains: A simulation study. Simulation 1998; 4 (71): 262-275.
- AIDS policy modeling: A social role for operations research. Ricerca Operativa 1998; 81-82 (27): 5-33
- Simulating the effects of protease inhibitors on the HIV epidemic: Treatment, compliance, and drug resistance. 1998
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Designing a zoned automated guided vehicle system with multiple vehicles and multiple load capacity
OPERATIONS RESEARCH
1997; 45 (6): 857-873
View details for Web of Science ID 000071690800007
- Review of Network and Discrete Location – Models, Algorithms, and Applications by M.S. Daskin. Interfaces 1997; 1 (27): 157-158.
- Designing a zoned automated guided vehicle system with multiple vehicles and multiple load capacity. Operations Research 1997; 6 (45): 857-873.
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Stochastic modeling for automated material handling system design and control
TRANSPORTATION SCIENCE
1996; 30 (4): 330-350
View details for Web of Science ID A1996VX47400005
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Designing a single-vehicle automated guided vehicle system with multiple load capacity
TRANSPORTATION SCIENCE
1996; 30 (4): 351-363
View details for Web of Science ID A1996VX47400006
- Designing a single-vehicle automated guided vehicle system with multiple load capacity. Transportation Science 1996; 4 (30): 351-363.
- Policy analysis of preventive HIV interventions targeted to adolescents. 1996
- Stochastic modeling for automated material handling systemdesign and control. Transportation Science 1996; 4 (30): 330-350.
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DESIGNING MULTIPLE-LOAD AUTOMATED GUIDED VEHICLE SYSTEMS FOR DELIVERING MATERIAL FROM A CENTRAL DEPOT
JOURNAL OF ENGINEERING FOR INDUSTRY-TRANSACTIONS OF THE ASME
1995; 117 (1): 33-41
View details for Web of Science ID A1995QK15500005
- Designing multiple-load automated guided vehicle systems for delivering material from a central depot. Transactions of the ASME: Journal of Engineering for Industry 1995; 1 (117): 33-41.
- Location with market externalities. In Facility Location: A Survey of Applications and Methods Springer-Verlag, New York, NY. 1995: 121–150.
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AN ANALYTIC MODEL FOR DESIGN AND ANALYSIS OF SINGLE-VEHICLE ASYNCHRONOUS MATERIAL HANDLING SYSTEMS
TRANSPORTATION SCIENCE
1994; 28 (4): 337-353
View details for Web of Science ID A1994PT89800006
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AN APPROACH FOR WORST-CASE ANALYSIS OF HEURISTICS - ANALYSIS OF A FLEXIBLE 0-1 KNAPSACK-PROBLEM
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN
1994; 37 (3): 197-210
View details for Web of Science ID A1994QF81100004
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LOCATION OF COMPETING FACILITIES IN A USER-OPTIMIZING ENVIRONMENT WITH MARKET EXTERNALITIES
TRANSPORTATION SCIENCE
1994; 28 (2): 125-140
View details for Web of Science ID A1994NM18300004
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WHEN WOMEN RETURN TO RISK - COSTS AND BENEFITS OF HIV SCREENING IN THE PRESENCE OF RELAPSE
34th Joint National Meeting of the Operations-Research-Society-of-America and The Institute-of-Management-Sciences
RAVEN PRESS. 1994: 121–136
View details for Web of Science ID A1994BA41L00007
- An analytic model for design and analysis of single-vehicle asynchronous material handling systems. Transportation Science 1994; 4 (28): 337-353.
- When women return to risk: Costs and benefits of HIV screening in the presence of relapse. In Modeling the AIDS Epidemic: Planning, Policy and Prediction Raven Press, New York, NY. 1994: 121–136
- An approach for worst case analysis of heuristics: Analysis of a flexible 0-1 knapsack problem. Journal of the Operations Research Society of Japan 1994; 3 (37): 197-210.
- Location of competing facilities in a user-optimizing environment with market externalities. Transportation Science 1994; 2 (28): 125-140.
- Facility location in a user-optimizing environment with market externalities: Analysis of customer equilibria and optimal public facility locations. Location Science 1994; 3 (2): 129-147.
- Modeling the AIDS Epidemic: Planning, Policy and Prediction. edited by Kaplan, E., H., Brandeau, M., L. Raven Press, New York, NY. 1994
- AIDS policy modeling by example. AIDS 1994; Suppl 1 (8): S333-S340.
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AN ANALYTIC MODEL FOR DESIGN OF A MULTIVEHICLE AUTOMATED GUIDED VEHICLE SYSTEM
MANAGEMENT SCIENCE
1993; 39 (12): 1477-1489
View details for Web of Science ID A1993MQ37900004
- Application of analytic models for material handling system design: Analysis of stochastic effects. In Progress in Material Handling Research, Braun-Brumfield, Inc., Ann Arbor, MI 1993: 97-120
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SCREENING WOMEN OF CHILDBEARING AGE FOR HUMAN-IMMUNODEFICIENCY-VIRUS - A MODEL-BASED POLICY ANALYSIS
MANAGEMENT SCIENCE
1993; 39 (1): 72-92
View details for Web of Science ID A1993KM62000006
- Sequential location and allocation: Worst case performance and statistical estimation. Location Science 1993; 4 (1): 289-298
- Screening women of childbearing age for human immunodeficiency virus: A model-based policy analysis. Management Science 1993; 1 (39): 72-92.
- PR for OR/MS: How can you get involved? OR/MS Today 1993: 68-69.
- An analytic model for design of a multivehicle automated guided vehicle system. Management Science 1993; 12 (39): 1477-1489.
- Strategic production planning: Operation assignment and product grouping. 1993
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SCREENING WOMEN OF CHILDBEARING AGE FOR HUMAN-IMMUNODEFICIENCY-VIRUS - A COST-BENEFIT-ANALYSIS
ARCHIVES OF INTERNAL MEDICINE
1992; 152 (11): 2229-2237
Abstract
In light of the increasing problem of perinatal human immunodeficiency virus (HIV) transmission, the issue of screening women for HIV is receiving considerable attention. We analyzed the costs and benefits of screening women of childbearing age for HIV. The analysis was based on a dynamic model of the HIV epidemic that incorporated disease transmission and progression, behavioral changes, and effects of screening and counseling. We found that the primary benefit of screening programs targeted to women of childbearing age lies not in the prevention of HIV infection in their newborns but in the prevention of infection in their adult contacts. Because of this benefit, screening medium- and high-risk women is likely to be cost-beneficial over a wide range of assumptions about program cost and behavioral changes in response to screening.
View details for PubMedID 1444682
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CHARACTERIZATION OF THE STOCHASTIC MEDIAN QUEUE TRAJECTORY IN A PLANE WITH GENERALIZED DISTANCES
OPERATIONS RESEARCH
1992; 40 (2): 331-341
View details for Web of Science ID A1992HP30800010
- A center location problem with congestion. Annals of Operations Research 1992; 1 (40): 17-32.
- Application of analytic models for material handling system design: Analysis of stochastic effects. 1992
- Screening women of childbearing age for human immunodeficiency virus: A cost-benefit analysis. Archives of Internal Medicine 1992; 11 (152): 2229-2237
- Characterization of the stochastic queue median trajectory in a plane with generalized distances. Operations Research 1992; 2 (40): 331-341.
- Integrated design and control of automated guided vehicle systems. Planning and Control of Material Handling Systems American Society of Manufacturing Engineers. 1992: 17–32.
- Analytical models for design of automated guided vehicle systems. 1992
- AIDS: Thoughts on managing a deadly epidemic. OR/MS Today. 1992: 50-52.
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A POLICY MODEL OF HUMAN-IMMUNODEFICIENCY-VIRUS SCREENING AND INTERVENTION
INTERFACES
1991; 21 (3): 5-25
View details for Web of Science ID A1991FR52300002
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DESIGN OF MANUFACTURING CELLS - OPERATION ASSIGNMENT IN PRINTED-CIRCUIT BOARD MANUFACTURING
JOURNAL OF INTELLIGENT MANUFACTURING
1991; 2 (2): 95-106
View details for Web of Science ID A1991FJ53200005
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HIV TESTING OF PREGNANT-WOMEN AND NEWBORNS
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
1991; 265 (12): 1525-1525
View details for Web of Science ID A1991FC60400009
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PARAMETRIC ANALYSIS OF OPTIMAL FACILITY LOCATIONS
NETWORKS
1991; 21 (2): 223-243
View details for Web of Science ID A1991EY92300006
- A policy model of human immunodeficiency virus screening and intervention. Interfaces 1991; 3 (21): 5-25.
- Parametric analysis of optimal facility locations. Networks 1991; 2 (21): 223-243.
- Design of manufacturing cells: Operation assignment in printed circuit board manufacturing. Journal of Intelligent Manufacturing, 1991; 2 (2): 95-106
- HIV testing of pregnant women and newborns [Letter]. Journal of the American Medical Association 1991; 265: 1525
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A UNIFIED FAMILY OF SINGLE-SERVER QUEUING LOCATION MODELS
OPERATIONS RESEARCH
1990; 38 (6): 1034-1044
View details for Web of Science ID A1990EW40100009
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TRAJECTORY ANALYSIS OF THE STOCHASTIC QUEUE MEDIAN IN A PLANE WITH RECTILINEAR DISTANCES
TRANSPORTATION SCIENCE
1990; 24 (3): 230-243
View details for Web of Science ID A1990DR78300006
- A unified family of single-server queuing location models. Operations Research 1990; 6 (38): 1034-1044.
- Trajectory analysis of the stochastic queue median in a plane with rectilinear distances. Transportation Science 1990; 3 (24): 230-243
- Policy analysis of human immunodeficiency virus screening and intervention: An overview of modeling approaches. AIDS and Public Policy Journal 1990; 3 (5): 119-131.
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AN OVERVIEW OF REPRESENTATIVE PROBLEMS IN LOCATION RESEARCH
MANAGEMENT SCIENCE
1989; 35 (6): 645-674
View details for Web of Science ID A1989AE55800001
- An overview of representative problems in location research [Extended abstract]. OR/MS Today 1989: 57-58.
- An overview of representative problems in location research. Management Science 1989; 6 (35): 645-674
- Review of Operations Management for Distributed Service Networks by N. Ahituv and O. Berman. Interfaces 1989: 84-86.
- A mathematical model of AIDS screening. Stanford Engineering 1989: 8-15.
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ESTABLISHING CONTINUITY OF CERTAIN OPTIMAL PARAMETRIC FACILITY LOCATION TRAJECTORIES
TRANSPORTATION SCIENCE
1988; 22 (3): 224-225
View details for Web of Science ID A1988P725000007
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PARAMETRIC FACILITY LOCATION ON A TREE NETWORK WITH AN LP-NORM COST FUNCTION
TRANSPORTATION SCIENCE
1988; 22 (1): 59-69
View details for Web of Science ID A1988M301600006
- Parametric facility location on a tree network with an Lp norm cost function. Transportation Science 1988; 1 (22): 59-69.
- Establishing continuity of certain optimal parametric facility location trajectories. Transportation Science 1988; 3 (22): 224-225.
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AN INTEGRATED BUDGET MODEL FOR MEDICAL-SCHOOL FINANCIAL-PLANNING
OPERATIONS RESEARCH
1987; 35 (5): 684-703
View details for Web of Science ID A1987M514500003
- The workup of the asymptomatic patient with a positive fecal occult blood test. Medical Decision Making 1987; 1 (7): 32-46.
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THE WORKUP OF THE ASYMPTOMATIC PATIENT WITH A POSITIVE FECAL OCCULT BLOOD-TEST
MEDICAL DECISION MAKING
1987; 7 (1): 32-46
Abstract
Twenty-two protocols for working up an asymptomatic patient who has a positive fecal occult blood test were evaluated using existing information on the prevalences of cancers, adenomas and other conditions in such patients; the natural history of colorectal cancer; the effectiveness of screening tests; risks; and costs. The authors estimate the impacts of the 22 workup strategies on outcomes such as the chance of finding an existing cancer or adenoma, risks (bleeding and perforation), and financial costs of different strategies involving rigid sigmoidoscopy, flexible sigmoidoscopy, barium enema, and colonoscopy. Two protocols were particularly effective. The first involves performing a barium enema study and following it with colonoscopy; if colonoscopy is negative, the barium enema study should be repeated. The second is to perform colonoscopy and if it is negative, follow it with a barium enema study.
View details for Web of Science ID A1987F586400008
View details for PubMedID 3100902
- An integrated budget model for medical school financial planning. Operations Research 1987; 5 (35): 684-703.
- Extending and applying the Hypercube Queueing Model to deploy ambulances in Boston. In Management Science and the Delivery of Urban Service, Vol. 22, 121-154, North- Holland/Elsevier, 1986. TIMS Studies in the Management Sciences Series, North-Holland/Elsevier,. 1986: 121–154
- Locating the two-median of a tree network with continuous link demands. Annals of Operations Research 1986; 7 (6): 223-253.
- A patient mix model for hospital financial planning Inquiry 1984; 1 (21): 32-44
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A PATIENT MIX MODEL FOR HOSPITAL FINANCIAL-PLANNING
INQUIRY-THE JOURNAL OF HEALTH CARE ORGANIZATION PROVISION AND FINANCING
1984; 21 (1): 32-44
Abstract
A linear programming model was formulated to examine the impact on hospital finances and resource use of changes in patient mix under current and proposed government reimbursement regulations. The model specifically incorporated the costs, revenues, and resource consumption patterns associated with patients drawn from different intensity level and payer class combinations. The necessary data were obtained from financial reports and other records, and the model was used in policy analysis at a major university teaching hospital.
View details for Web of Science ID A1984TQ78500004
View details for PubMedID 6232215
- A National Assessment of Police Command, Control, and Communications Systems. National Institute of Justice, Washington, DC 1983