2026-09-20T14:13:57Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1515132023-08-01T03:55:26Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Jónasson, Jónas Oddur Reubenstein, Rebecca Massachusetts Institute of Technology. Operations Research Center 2023-07-31T19:45:27Z 2023-07-31T19:45:27Z 2023-06 2023-07-13T16:04:00.650Z https://hdl.handle.net/1721.1/151513 https://orcid.org/0000-0003-4758-451X Community health workers (CHWs) are increasingly important to healthcare delivery in many African countries. As CHW programs are being scaled up and integrated into national healthcare delivery systems, an important policy question is how to deploy CHWs to various localities, given their differences in disease burden and population density as well as the limited national resources for the program. We develop a modeling framework which jointly describes the health impact of a CHW program as a function of an area’s disease characteristics, operational environment, and CHW deployment density. Specifically, we use a continuous logistical model to capture the travel time constraints of CHWs and a novel continuous time stochastic model to describe individual health progression. We then demonstrate how our model can be used to inform policy decisions by formulating and solving an optimization problem for CHW deployment. Our numerical results demonstrate that we can prioritize equity in our deployment approach without incurring too high a price in terms of total country-wide utility. S.M. Massachusetts Institute of Technology In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ Equitable Community Health Worker Deployment in sub-Saharan Africa: A Modeling Framework for Stochastic Health Progression Thesis application/pdf Master Master of Science in Operations Research Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="608058d2-19d8-4e16-aedc-c279e167e02e"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Equitable Community Health Worker Deployment in sub-Saharan Africa: A Modeling Framework for Stochastic Health Progression</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2023-06</PublicationDate> <Authors> <Author> <DisplayName>Reubenstein, Rebecca</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://rightsstatements.org/page/InC-EDU/1.0/</License> <Abstract>Community health workers (CHWs) are increasingly important to healthcare delivery in many African countries. As CHW programs are being scaled up and integrated into national healthcare delivery systems, an important policy question is how to deploy CHWs to various localities, given their differences in disease burden and population density as well as the limited national resources for the program. We develop a modeling framework which jointly describes the health impact of a CHW program as a function of an area’s disease characteristics, operational environment, and CHW deployment density. Specifically, we use a continuous logistical model to capture the travel time constraints of CHWs and a novel continuous time stochastic model to describe individual health progression. We then demonstrate how our model can be used to inform policy decisions by formulating and solving an optimization problem for CHW deployment. Our numerical results demonstrate that we can prioritize equity in our deployment approach without incurring too high a price in terms of total country-wide utility.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>