Evidence-based Decision Making: Infectious Disease Modeling Training for Policymakers in East Africa
Authors:
- Sylvia K. OforiSOSylvia K. Ofori
- Emmanuelle A. DankwaEDEmmanuelle A. Dankwa
- Emmanuel NgwakongnwiENEmmanuel Ngwakongnwi
- Alemayehu AmberbirAAAlemayehu Amberbir
- Abebe BekeleABAbebe Bekele
- Megan B. MurrayMMMegan B. Murray
- Yonatan H. GradYGYonatan H. Grad
- Caroline O. BuckeeCBCaroline O. Buckee
- Bethany L. Hedt-GauthierBHBethany L. Hedt-Gauthier
Open Access
- 5 January 2024
- journal article
- research article
- Published by Ubiquity Press, Ltd. in Annals of Global Health
- Vol. 90 (1) , 22-15
Abstract
Background: Mathematical modeling of infectious diseases is an important decision-making tool for outbreak control. However, in Africa, limited expertise reduces the use and impact of these tools on policy. Therefore, there is a need to build capacity in Africa for the use of mathematical modeling to inform policy. Here we describe our experience implementing a mathematical modeling training program for public health professionals in East Africa. Methods: We used a deliverable-driven and learning-by-doing model to introduce trainees to the mathematical modeling of infectious diseases. The training comprised two two-week in-person sessions and a practicum where trainees received intensive mentorship. Trainees evaluated the content and structure of the course at the end of each week, and this feedback informed the strategy for subsequent weeks. Findings: Out of 875 applications from 38 countries, we selected ten trainees from three countries – Rwanda (6), Kenya (2), and Uganda (2) – with guidance from an advisory committee. Nine trainees were based at government institutions and one at an academic organization. Participants gained skills in developing models to answer questions of interest and critically appraising modeling studies. At the end of the training, trainees prepared policy briefs summarizing their modeling study findings. These were presented at a dissemination event to policymakers, researchers, and program managers. All trainees indicated they would recommend the course to colleagues and rated the quality of the training with a median score of 9/10. Conclusions: Mathematical modeling training programs for public health professionals in Africa can be an effective tool for research capacity building and policy support to mitigate infectious disease burden and forecast resources. Overall, the course was successful, owing to a combination of factors, including institutional support, trainees’ commitment, intensive mentorship, a diverse trainee pool, and regular evaluations.Keywords
Funding Information
- Centers for Disease Control and Prevention Foundation (200-2016-91779)
This publication has 22 references indexed in Scilit:
- Training and capacity building in medical statistics in Sub‐Saharan Africa: Impact of the London School of Hygiene & Tropical Medicine MSc in Medical Statistics, 1969 to 2021Statistics in Medicine, 2022
- The Use and Misuse of Mathematical Modeling for Infectious Disease Policymaking: Lessons for the COVID-19 PandemicMedical Decision Making, 2021
- African-led health research and capacity building- is it working?BMC Public Health, 2020
- Disease modeling for public health: added value, challenges, and institutional constraintsJournal of Public Health Policy, 2019
- Emerging infectious diseases in Africa in the 21st centuryNew Microbes and New Infections, 2018
- Adapting operational research training to the Rwandan context: the Intermediate Operational Research Training programmeGlobal Health Action, 2017
- Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-makingInternational Journal of Infectious Diseases, 2016
- Strengthening research capacity through the medical education partnership initiative: the Mozambique experienceHuman Resources for Health, 2013
- Investing in African research training institutions creates sustainable capacity for Africa: the case of the University of the Witwatersrand School of Public Health masters programme in epidemiology and biostatisticsHealth Research Policy and Systems, 2012
- Mathematical models in the evaluation of health programmesThe Lancet, 2011