An Allocation Problem Considering Coverage for COVID-19 Testing

In this chapter, we propose an optimization methodology to design a home delivery service for COVID-19 testing in the metropolitan area of Monterrey. The aim of implementing this social program is to mitigate contagion. Therefore, we focus on increasing the number of home delivery service tests applied. Some hospitals or medical centers do not offer COVID-19 testing; thus, vehicles are used to perform the testing process, but we consider a given mobility radius to transfer the tests. Patients (infection points) receive the tests at their homes, and afterward, those tests are transferred to medical centers. We design a linear binary mathematical program for our proposed problem. Moreover, we analyze a real case study based on the information of medical centers, available mobile units, and possible infected points in the metropolitan area of Monterrey. Numerical results give the best configuration for implementing this social program regarding the allocation of mobile units to affected points and medical centers. Finally, we find optimal solutions in minutes of computational times, which is essential for this decision-making context since planners may take decisions several times during the day. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

An Allocation Problem Considering Coverage for COVID-19 Testing Chapter in Scopus