Yupeng Chen

All Publications

• Cost-effectiveness of contingency management for methamphetamine use disorder: A model-based analysis. Addiction (Abingdon, England) Qian, G. L., Chen, Y., Rawson, R. A., Humphreys, K., Brandeau, M. L. 2026

  Abstract

  The United States (US) is experiencing a surge in methamphetamine use. Treatment options for methamphetamine use disorder (MethUD) focus on behavior change, particularly via contingency management (CM), where individuals receive rewards for submitting drug-free urine samples or for other positive behaviors such as attending treatment sessions. Little is known about the cost-effectiveness of CM for treating MethUD, including the January 2025 decision by the US federal government to increase the maximum annual CM incentive ten-fold to $750 per patient. This study aimed to assess the cost-effectiveness of CM for individuals with MethUD in the US.We developed a microsimulation model of methamphetamine use behavior among individuals with MethUD to assess the effectiveness and cost-effectiveness of CM for treating MethUD. We modeled methamphetamine use states and psychiatric and cardiovascular comorbidities. We considered a 12-week and 24-week CM program, with a maximum $750 incentive. We simulated the model in weekly time steps over the lifetime of a cohort of 10 000 individuals with MethUD, under the status quo (no treatment) and with the CM program.Number of deaths over one year and lifetime per person healthcare costs (healthcare sector perspective) and quality-adjusted life years (QALYs) experienced.With no treatment, 274 overdose deaths and 305 total deaths occurred in the cohort over 1 year. Individuals experienced 11.37 lifetime QALYs and incurred $216 320 in lifetime healthcare costs. With a 12-week CM program, an estimated 117 deaths were prevented over 1 year, with a net gain of 0.70 lifetime QALYs per person and incremental cost of $6850 compared with no treatment, yielding an incremental cost-effectiveness ratio (ICER) of $9830/QALY gained [95% credible interval (CR) = $8100-$11 400]. With a 24-week program, 153 deaths were prevented over 1 year, with a net gain of 0.81 lifetime QALYs per person and incremental cost of $10 000, yielding an ICER of $12 312/QALY gained (95% CR = $10 400-$14 100). Even under the pessimistic assumption of no lasting behavior change after CM program completion, the programs cost less than $130 000/QALY gained. Threshold analysis suggests that at a $50 000 willingness to pay, the 24-week program would be cost-effective even if the maximum incentive were $2491.Modelling shows that contingency management appears to be a highly cost-effective intervention for treating methamphetamine use disorder, even with conservative assumptions and a $750 incentive cap. When cost impacts in the criminal justice and child welfare systems are included, such programs are likely cost-saving.

  View details for DOI 10.1111/add.70377

  View details for PubMedID 41807076

• 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 Snir, S., Chen, Y., Yechezkel, M., Patalon, T., Shmueli, E., Brandeau, M. L., Yamin, D. 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