Resource Allocation with Sigmoidal Demands: Mobile Healthcare Units and Service Adoption.



Achieving broad access to health services requires reaching rural populations. Mobile healthcare units (MHUs) visit remote sites to offer health services to these populations. However, limited exposure, health literacy, and trust can lead to sigmoidal (S-shaped) adoption dynamics, presenting a difficult obstacle in allocating limited MHU resources. It is tempting to allocate resources in line with current demand, as seen in practice. However, to maximize access in the long term, this may be far from optimal, and insights into allocation decisions are limited. We present a formal model of the long-term allocation of MHU resources as the optimization of a sum of sigmoidal functions. We develop insights into optimal allocation decisions and propose pragmatic methods for estimating our model’s parameters from data available in practice and demonstrate the potential of our approach by applying our methods to family planning MHUs in Uganda.

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About Harwin de Vries

Harwin de Vries is Associate Professor at the Technology and Operations Management department at RSM. His research focuses on health & humanitarian logistics, with a particular focus on disaster relief logistics and the logistics behind enhancing access to essential medicines and health services in LMICs. He particularly explores the potential role of data and prescriptive analytics and new business and operating models in the sectors (e.g., service delivery through mobile health units).