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Accessible location of mobile labs for COVID-19 testing

Author

Listed:
  • Dianne Villicaña-Cervantes

    (Universidad Autónoma de Nuevo León)

  • Omar J. Ibarra-Rojas

    (Universidad Autónoma de Nuevo León)

Abstract

In this study, we address the problem of finding the best locations for mobile labs offering COVID-19 testing. We assume that people within known demand centroids have a degree of mobility, i.e., they can travel a reasonable distance, and mobile labs have a limited-and-variable service area. Thus, we define a location problem concerned with optimizing a measure representing the accessibility of service to its potential clients. In particular, we use the concepts of classical, gradual, and cooperative coverage to define a weighted sum of multiple accessibility indicators. We formulate our optimization problem via a mixed-integer linear program which is intractable by commercial solvers for large instances. In response, we designed a Biased Random-Key Genetic Algorithm to solve the defined problem; this is capable of obtaining high-quality feasible solutions over large numbers of instances in seconds. Moreover, we present insights derived from a case study into the locations of COVID-19 testing mobile laboratories in Nuevo Leon, Mexico. Our experimental results show that our optimization approach can be used as a diagnostic tool to determine the number of mobile labs needed to satisfy a set of demand centroids, assuming that users have reduced mobility due to the restrictions because of the pandemic.

Suggested Citation

  • Dianne Villicaña-Cervantes & Omar J. Ibarra-Rojas, 2024. "Accessible location of mobile labs for COVID-19 testing," Health Care Management Science, Springer, vol. 27(1), pages 1-19, March.
    • Handle: RePEc:kap:hcarem:v:27:y:2024:i:1:d:10.1007_s10729-022-09614-3
    DOI: 10.1007/s10729-022-09614-3
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