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Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy

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  • Dijkstra, Sander
  • Baas, Stef
  • Braaksma, Aleida
  • Boucherie, Richard J.

Abstract

This paper introduces mathematical models that support dynamic fair balancing of COVID-19 patients over hospitals in a region and across regions. Patient flow is captured in an infinite server queueing network. The dynamic fair balancing model within a region is a load balancing model incorporating a forecast of the bed occupancy, while across regions, it is a stochastic program taking into account scenarios of the future bed surpluses or shortages. Our dynamic fair balancing models yield decision rules for patient allocation to hospitals within the region and reallocation across regions based on safety levels and forecast bed surplus or bed shortage for each hospital or region.

Suggested Citation

  • Dijkstra, Sander & Baas, Stef & Braaksma, Aleida & Boucherie, Richard J., 2023. "Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy," Omega, Elsevier, vol. 116(C).
    • Handle: RePEc:eee:jomega:v:116:y:2023:i:c:s0305048322002079
    DOI: 10.1016/j.omega.2022.102801
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    References listed on IDEAS

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