Bio


Dr. Rishi Mediratta, MD, MSc, MA, is a Clinical Associate Professor in Pediatrics, a Pediatric Hospitalist at Lucile Packard Children’s Hospital, and a Faculty Fellow at the Stanford Center for Innovation in Global Health (CIGH). He graduated from Johns Hopkins University with a BA in Public Health and went to medical school at Stanford University. Dr. Mediratta has conducted community-based, pediatrics, and public health research in Ethiopia since 2005. He founded the Ethiopian Orphan Health Foundation to provide community-based health care and education to orphans in Ethiopia. As a British Marshall Scholar, he received an MA in Medical Anthropology from the School of Oriental and African Studies and an MSc in Public Health at the London School of Hygiene and Tropical Medicine. As a pediatrics resident at Stanford, he became passionate about decreasing neonatal mortality through hospital- and community-based education programs. As faculty, he supervises trainees and cares for hospitalized children and integrates his field experience and interdisciplinary background to create newborn and child health programs. He has worked with policymakers at the World Bank, the World Health Organization, UNICEF, and Save the Children. At Stanford University, he teaches a course to undergraduate and graduate students from all disciplines about the medical and societal implications of the COVID-19 pandemic.

Clinical Focus


  • Pediatrics

Academic Appointments


Boards, Advisory Committees, Professional Organizations


  • Faculty Fellow, Center for Innovation in Global Health (CIGH) (2021 - Present)

Professional Education


  • Board Certification, Pediatrics, American Board of Pediatrics (2018)
  • Residency, Stanford University School of Medicine, Pediatrics (2018)
  • MD, Stanford University School of Medicine (2015)
  • MSc, London School of Hygiene and Tropical Medicine, Public Health (2011)
  • MA, School of Oriental and African Studies, Medical Anthropology (2010)
  • BA, Johns Hopkins University, Public Health Studies (2008)

Current Research and Scholarly Interests


I have developed a new promising neonatal mortality prediction score at the University of Gondar Neonatal Intensive Care Unit (NICU) in Gondar, Ethiopia. The score predicts approximately 84% of neonatal deaths in the NICU using clinical variables. I have a dataset over 800 NICU admissions in Gondar. I am recruiting scholars who are interested in conducting clinical and epidemiological research to validate, refine, and implement the mortality score to reduce neonatal mortality in Ethiopia. I can mentor scholars to conduct research in Ethiopia, facilitate in-country supervision at the University of Gondar, and facilitate statistical support with Stanford's Department of Statistics.

Clinical Trials


  • Comparison of Virtual Training to In-Person Training of Helping Babies Breathe in Ethiopia Not Recruiting

    Helping Babies Breathe (HBB) is a program that teaches providers in low- and middle-income countries about neonatal resuscitation. Historically, HBB training was delivered in person. During the COVID-19 pandemic, many subject matter experts were unable to travel to conduct HBB courses. Innovative methods for teaching HBB are needed to promote the acquisition and retention of resuscitation skills and knowledge.

    Stanford is currently not accepting patients for this trial.

    View full details

2023-24 Courses


Stanford Advisees


All Publications


  • Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet (London, England) 2024

    Abstract

    Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period.22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(24)00476-8

    View details for PubMedID 38484753

  • Implementing adaptive e-learning for newborn care in Tanzania: an observational study of provider engagement and knowledge gains. BMJ open Meaney, P. A., Hokororo, A., Ndosi, H., Dahlen, A., Jacob, T., Mwanga, J. R., Kalabamu, F. S., Joyce, C. L., Mediratta, R., Rozenfeld, B., Berg, M., Smith, Z. H., Chami, N., Mkopi, N., Mwanga, C., Diocles, E., Agweyu, A. 2024; 14 (2): e077834

    Abstract

    To improve healthcare provider knowledge of Tanzanian newborn care guidelines, we developed adaptive Essential and Sick Newborn Care (aESNC), an adaptive e-learning environment. The objectives of this study were to (1) assess implementation success with use of in-person support and nudging strategy and (2) describe baseline provider knowledge and metacognition.6-month observational study at one zonal hospital and three health centres in Mwanza, Tanzania. To assess implementation success, we used the Reach, Efficacy, Adoption, Implementation and Maintenance framework and to describe baseline provider knowledge and metacognition we used Howell's conscious-competence model. Additionally, we explored provider characteristics associated with initial learning completion or persistent activity.aESNC reached 85% (195/231) of providers: 75 medical, 53 nursing and 21 clinical officers; 110 (56%) were at the zonal hospital and 85 (44%) at health centres. Median clinical experience was 4 years (IQR 1-9) and 45 (23%) had previous in-service training for both newborn essential and sick newborn care. Efficacy was 42% (SD ±17%). Providers averaged 78% (SD ±31%) completion of initial learning and 7% (SD ±11%) of refresher assignments. 130 (67%) providers had ≥1 episode of inactivity >30 day, no episodes were due to lack of internet access. Baseline conscious-competence was 53% (IQR: 38%-63%), unconscious-incompetence 32% (IQR: 23%-42%), conscious-incompetence 7% (IQR: 2%-15%), and unconscious-competence 2% (IQR: 0%-3%). Higher baseline conscious-competence (OR 31.6 (95% CI 5.8 to 183.5)) and being a nursing officer (aOR: 5.6 (95% CI 1.8 to 18.1)), compared with medical officer, were associated with initial learning completion or persistent activity.aESNC reach was high in a population of frontline providers across diverse levels of care in Tanzania. Use of in-person support and nudging increased reach, initial learning and refresher assignment completion, but refresher assignment completion remains low. Providers were often unaware of knowledge gaps, and lower baseline knowledge may decrease initial learning completion or activity. Further study to identify barriers to adaptive e-learning normalisation is needed.

    View details for DOI 10.1136/bmjopen-2023-077834

    View details for PubMedID 38309746

  • Research Methods: Diagnostic Test Characteristics. Hospital pediatrics Mediratta, R. P., Newman, T. B., Wang, M. E. 2023

    Abstract

    The goal of a diagnostic test is to provide information on the probability of disease. In this article, we review the principles of diagnostic test characteristics, including sensitivity, specificity, positive and negative predictive value, receiver operating characteristics curves, likelihood ratios, and interval likelihood ratios. We illustrate how interval likelihood ratios optimize the information that can be obtained from test results that can take on >2 values, how they are reflected in the slope of the receiver operating characteristics curve, and how they can be easily calculated from published data.

    View details for DOI 10.1542/hpeds.2023-007149

    View details for PubMedID 37144292

  • Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries. Nature human behaviour Calvert, C., Brockway, M. M., Zoega, H., Miller, J. E., Been, J. V., Amegah, A. K., Racine-Poon, A., Oskoui, S. E., Abok, I. I., Aghaeepour, N., Akwaowo, C. D., Alshaikh, B. N., Ayede, A. I., Bacchini, F., Barekatain, B., Barnes, R., Bebak, K., Berard, A., Bhutta, Z. A., Brook, J. R., Bryan, L. R., Cajachagua-Torres, K. N., Campbell-Yeo, M., Chu, D. T., Connor, K. L., Cornette, L., Cortés, S., Daly, M., Debauche, C., Dedeke, I. O., Einarsdóttir, K., Engjom, H., Estrada-Gutierrez, G., Fantasia, I., Fiorentino, N. M., Franklin, M., Fraser, A., Gachuno, O. W., Gallo, L. A., Gissler, M., Håberg, S. E., Habibelahi, A., Häggström, J., Hookham, L., Hui, L., Huicho, L., Hunter, K. J., Huq, S., Kc, A., Kadambari, S., Kelishadi, R., Khalili, N., Kippen, J., Le Doare, K., Llorca, J., Magee, L. A., Magnus, M. C., Man, K. K., Mburugu, P. M., Mediratta, R. P., Morris, A. D., Muhajarine, N., Mulholland, R. H., Bonnard, L. N., Nakibuuka, V., Nassar, N., Nyadanu, S. D., Oakley, L., Oladokun, A., Olayemi, O. O., Olutekunbi, O. A., Oluwafemi, R. O., Ogunkunle, T. O., Orton, C., Örtqvist, A. K., Ouma, J., Oyapero, O., Palmer, K. R., Pedersen, L. H., Pereira, G., Pereyra, I., Philip, R. K., Pruski, D., Przybylski, M., Quezada-Pinedo, H. G., Regan, A. K., Rhoda, N. R., Rihs, T. A., Riley, T., Rocha, T. A., Rolnik, D. L., Saner, C., Schneuer, F. J., Souter, V. L., Stephansson, O., Sun, S., Swift, E. M., Szabó, M., Temmerman, M., Tooke, L., Urquia, M. L., von Dadelszen, P., Wellenius, G. A., Whitehead, C., Wong, I. C., Wood, R., Wróblewska-Seniuk, K., Yeboah-Antwi, K., Yilgwan, C. S., Zawiejska, A., Sheikh, A., Rodriguez, N., Burgner, D., Stock, S. J., Azad, M. B. 2023

    Abstract

    Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.

    View details for DOI 10.1038/s41562-023-01522-y

    View details for PubMedID 36849590

    View details for PubMedCentralID 8417352

  • Applying Kern's Six Steps to the Development of a Community-Engaged, Just-in-Time, Interdisciplinary COVID-19 Curriculum. Journal of medical education and curricular development Scala, J. J., Braun, N. J., Shamardani, K., Rashes, E. R., Wang, W., Mediratta, R. P. 2022; 9: 23821205221096370

    Abstract

    Universities and medical schools often work towards operationalizing their shared mission of facilitating community-engaged work independently. Based on their experience teaching the COVID-19 Elective course at Stanford University School of Medicine, the authors proposed a novel solution for universities and medical schools to achieve an interdisciplinary collaboration within a diverse student population by creating targeted, project-based, and community-engaged courses for addressing emergent health needs. In this article, the authors discuss their curriculum, which was created using Kern's six-step approach for curriculum development, to address emergent health needs related to the novel coronavirus pandemic. The curriculum provides an opportunity for universities and medical schools to advance community health, educate students across the medical and non-medical education continuum, and foster interdisciplinary cooperation.

    View details for DOI 10.1177/23821205221096370

    View details for PubMedID 35509682

    View details for PubMedCentralID PMC9058336

  • Overnight admissions to a neonatal intensive care unit in Ethiopia are not associated with increased mortality. PloS one Mediratta, R. P., Rajamani, M., Ayalew, M., Shehibo, A., Tazebew, A., Teklu, A. 2022; 17 (3): e0264926

    Abstract

    In 2019, 2.4 million neonates died globally, with most deaths occurring in low-resource settings. Despite the introduction of neonatal intensive care units (NICUs) in these settings, neonatal mortality remains high, and caring for sick neonates around the clock can be challenging due to limited staff and resources.To evaluate whether neonatal intensive care admissions during daytime and overnight hours affects in-hospital neonatal mortality.A retrospective case-control study was conducted using 2016 chart data at a University hospital in Ethiopia. Cases were defined as neonates who died in the NICU, and controls were defined as neonates who survived. Overnight hours were defined as 17:00 to 07:59, and day hours were defined as 08:00 to 16:59. Univariate and multivariate logistic regressions were used to investigate the relationship between time of admission and mortality, along with perinatal characteristics.A total of 812 neonates, 207 cases and 605 controls, met inclusion criteria. There were 342 admissions during the day and 470 overnight. Neonatal mortality (aOR 1.02, 95% CI [0.64-1.62], p = 0.93) was not associated with overnight admissions after controlling for maternal age, parity, C-section, birthweight, and gestational age, respiratory distress, and admission level of consciousness. Admission heart rate >160 (aOR 0.52, 95% CI [0.30-0.91], p = 0.02) was the only variable significantly associated with overnight admissions.Being admitted overnight to the NICU in Gondar, Ethiopia was not associated with increased mortality, consistent with a constant level of care, regardless of the time of admission. Further qualitative and implementation research are needed to understand contextual factors that have affected these data.

    View details for DOI 10.1371/journal.pone.0264926

    View details for PubMedID 35324936

    View details for PubMedCentralID PMC8947129

  • The Burden of Critical Illness in Hospitalized Children in Low- and Middle-Income Countries: Protocol for a Systematic Review and Meta-Analysis. Frontiers in pediatrics Kortz, T. B., Nielsen, K. R., Mediratta, R. P., Reeves, H., O'Brien, N. F., Lee, J. H., Attebery, J. E., Bhutta, E. G., Biewen, C., Coronado Munoz, A., deAlmeida, M. L., Fonseca, Y., Hooli, S., Johnson, H., Kissoon, N., Leimanis-Laurens, M. L., McCarthy, A. M., Pineda, C., Remy, K. E., Sanders, S. C., Takwoingi, Y., Wiens, M. O., Bhutta, A. T. 2022; 10: 756643

    Abstract

    Background: The majority of childhood deaths occur in low- and middle-income countries (LMICs). Many of these deaths are avoidable with basic critical care interventions. Quantifying the burden of pediatric critical illness in LMICs is essential for targeting interventions to reduce childhood mortality.Objective: To determine the burden of hospitalization and mortality associated with acute pediatric critical illness in LMICs through a systematic review and meta-analysis of the literature.Data Sources and Search Strategy: We will identify eligible studies by searching MEDLINE, EMBASE, CINAHL, and LILACS using MeSH terms and keywords. Results will be limited to infants or children (ages >28 days to 12 years) hospitalized in LMICs and publications in English, Spanish, or French. Publications with non-original data (e.g., comments, editorials, letters, notes, conference materials) will be excluded.Study Selection: We will include observational studies published since January 1, 2005, that meet all eligibility criteria and for which a full text can be located.Data Extraction: Data extraction will include information related to study characteristics, hospital characteristics, underlying population characteristics, patient population characteristics, and outcomes.Data Synthesis: We will extract and report data on study, hospital, and patient characteristics; outcomes; and risk of bias. We will report the causes of admission and mortality by region, country income level, and age. We will report or calculate the case fatality rate (CFR) for each diagnosis when data allow.Conclusions: By understanding the burden of pediatric critical illness in LMICs, we can advocate for resources and inform resource allocation and investment decisions to improve the management and outcomes of children with acute pediatric critical illness in LMICs.

    View details for DOI 10.3389/fped.2022.756643

    View details for PubMedID 35372149

  • Challenges and Opportunities in Deploying COVID-19 Cough AI Systems. Journal of voice : official journal of the Voice Foundation Khanzada, A., Hegde, S., Sreeram, S., Bower, G., Wang, W., Mediratta, R. P., Meister, K. D., Rameau, A. 2021

    View details for DOI 10.1016/j.jvoice.2021.08.009

    View details for PubMedID 34610883

  • Derivation and validation of a prognostic score for neonatal mortality in Ethiopia: a case-control study. BMC pediatrics Mediratta, R. P., Amare, A. T., Behl, R., Efron, B., Narasimhan, B., Teklu, A., Shehibo, A., Ayalew, M., Kache, S. 2020; 20 (1): 238

    Abstract

    BACKGROUND: Early warning scores for neonatal mortality have not been designed for low income countries. We developed and validated a score to predict mortality upon admission to a NICU in Ethiopia.METHODS: We conducted a retrospective case-control study at the University of Gondar Hospital, Gondar, Ethiopia. Neonates hospitalized in the NICU between January 1, 2016 to June 31, 2017. Cases were neonates who died and controls were neonates who survived.RESULTS: Univariate logistic regression identified variables associated with mortality. The final model was developed with stepwise logistic regression. We created the Neonatal Mortality Score, which ranged from 0 to 52, from the model's coefficients. Bootstrap analysis internally validated the model. The discrimination and calibration were calculated. In the derivation dataset, there were 207 cases and 605 controls. Variables associated with mortality were admission level of consciousness, admission respiratory distress, gestational age, and birthweight. The AUC for neonatal mortality using these variables in aggregate was 0.88 (95% CI 0.85-0.91). The model achieved excellent discrimination (bias-corrected AUC) under internal validation. Using a cut-off of 12, the sensitivity and specificity of the Neonatal Mortality Score was 81 and 80%, respectively. The AUC for the Neonatal Mortality Score was 0.88 (95% CI 0.85-0.91), with similar bias-corrected AUC. In the validation dataset, there were 124 cases and 122 controls, the final model and the Neonatal Mortality Score had similar discrimination and calibration.CONCLUSIONS: We developed, internally validated, and externally validated a score that predicts neonatal mortality upon NICU admission with excellent discrimination and calibration.

    View details for DOI 10.1186/s12887-020-02107-8

    View details for PubMedID 32434513

  • Liver Failure and Rash in a 6-week-old Girl PEDIATRICS IN REVIEW Mediratta, R., Schwenk, H., Rao, A., Chitkara, R. 2018; 39 (6): 315–U22

    View details for PubMedID 29858298

  • Galvanizing medical students in the administration of influenza vaccines: the Stanford Flu Crew. Advances in medical education and practice Rizal, R. E., Mediratta, R. P., Xie, J., Kambhampati, S., Hills-Evans, K., Montacute, T., Zhang, M., Zaw, C., He, J., Sanchez, M., Pischel, L. 2015; 6: 471-477

    Abstract

    Many national organizations call for medical students to receive more public health education in medical school. Nonetheless, limited evidence exists about successful servicelearning programs that administer preventive health services in nonclinical settings. The Flu Crew program, started in 2001 at the Stanford University School of Medicine, provides preclinical medical students with opportunities to administer influenza immunizations in the local community. Medical students consider Flu Crew to be an important part of their medical education that cannot be learned in the classroom. Through delivering vaccines to where people live, eat, work, and pray, Flu Crew teaches medical students about patient care, preventive medicine, and population health needs. Additionally, Flu Crew allows students to work with several partners in the community in order to understand how various stakeholders improve the delivery of population health services. Flu Crew teaches students how to address common vaccination myths and provides insights into implementing public health interventions. This article describes the Stanford Flu Crew curriculum, outlines the planning needed to organize immunization events, shares findings from medical students' attitudes about population health, highlights the program's outcomes, and summarizes the lessons learned. This article suggests that Flu Crew is an example of one viable service-learning modality that supports influenza vaccinations in nonclinical settings while simultaneously benefiting future clinicians.

    View details for DOI 10.2147/AMEP.S70294

    View details for PubMedID 26170731

    View details for PubMedCentralID PMC4492543

  • Risk Factors and Case Management of Acute Diarrhoea in North Gondar Zone, Ethiopia JOURNAL OF HEALTH POPULATION AND NUTRITION Mediratta, R. P., Feleke, A., Moulton, L. H., Yifru, S., Sack, R. B. 2010; 28 (3): 253-263

    Abstract

    In Ethiopia, evidence is lacking about maternal care-taking and environmental risk factors that contribute to acute diarrhoea and the case management of diarrhoea. The aim of this study was to identify the risk factors and to understand the management of acute diarrhoea. A pretested structured questionnaire was used for interviewing mothers of 440 children in a prospective, matched, case-control study at the University of Gondar Referral and Teaching Hospital in Gondar, Ethiopia. Results of multivariate analysis demonstrated that children who were breastfed and not completely weaned and mothers who were farmers were protective factors; risk factors for diarrhoea included sharing drinking-water and introducing supplemental foods. Children presented with acute diarrhoea for 3.9 days with 4.3 stools per day. Mothers usually did not increase breastmilk and other fluids during diarrhoea episodes and generally did not take children with diarrhoea to traditional healers. Incorporating messages about the prevention and treatment of acute diarrhoea into child-health interventions will help reduce morbidity and mortality associated with this disease.

    View details for Web of Science ID 000279758900007

    View details for PubMedID 20635636