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

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.