The population of truck drivers plays a key role in the spread of HIV and other infectious diseases in sub-Saharan Africa. Truck drivers thereby affect the health and lives of many, but also suffer from poor health and significantly reduced life expectancy themselves. Due to professional circumstances, their health service needs are generally not well addressed. Therefore, the non-governmental organization North Star Alliance builds a network of healthcare facilities along the largest trucking routes in sub-Saharan Africa. This paper studies the problem where to place additional facilities, and which health service packages to offer at each facility. The objective combines the maximization of the patient volume at these facilities and the maximization of the effectiveness of the health service delivery to the population served. The latter criterion is modeled through three novel access measures which capture the needs for effective service provisioning. The resulting optimization problem is essentially different from previously studied healthcare facility location problems because of the specific mobile nature of health service demand of truck drivers. Applying our model to the network of major transport corridors in South-East Africa, we investigate several prominent questions managers and decision-makers face. We show that the present network expansion strategy, which primarily focuses on patient volumes, may need to be reconsidered: substantial gains in effectiveness can be made when allowing a small reduction in patient volumes. We furthermore show that solutions are rather robust to data impreciseness and that long-term network planning can bring substantial benefits, particularly in greenfield situations.

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doi.org/10.1111/poms.13152, hdl.handle.net/1765/124868
Production and Operations Management
Rotterdam School of Management (RSM), Erasmus University

de Vries, H., van de Klundert, J., & Wagelmans, A. (2020). The Roadside Healthcare Facility Location Problem A Managerial Network Design Challenge. Production and Operations Management. doi:10.1111/poms.13152