Community Healthcare Network in Underserved Areas: Design, Mathematical Models, and Analysis

Abstract

In community health programs implemented in underserved areas, community healthcare workers (CHWs) prevent, diagnose, and treat the most common diseases. To ensure continuous in‐service training of CHWs, some countries have mentored highly skilled CHWs to become supervisors. Designing a network in such a context implies determining the number of CHWs and supervisors, as well as the routing of the supervisors. This can be defined as a location‐routing covering problem (LRCP), a variant of the location‐routing and the covering tour problems. To solve the LRCP, we propose set‐partitioning formulations and a procedure to generate only non‐dominated variables without losing optimality, which also allows to break the symmetry between variables. Finding the most appropriate mathematical model is important to solve real‐life instances, improve the quality of the solution, and reduce the total computation time. Therefore, we develop tools to assist with the design and analysis of a community healthcare network in order to increase health coverage for underserved areas. Results are presented for an application in Liberia, including sensitivity analyses on various parameters and managerial insights.