Mathematical optimization models for reallocating and sharing health equipment in pandemic situations

Víctor Blanco (), Ricardo Gázquez () and Marina Leal ()
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Víctor Blanco: Universidad de Granada
Ricardo Gázquez: Universidad de Granada
Marina Leal: Universidad Miguel Hernández

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2023, vol. 31, issue 2, No 4, 355-390

Abstract: Abstract In this paper we provide a mathematical programming based decision tool to optimally reallocate and share equipment between different units to efficiently equip hospitals in pandemic emergency situations under lack of resources. The approach is motivated by the COVID-19 pandemic in which many Heath National Systems were not able to satisfy the demand of ventilators, sanitary individual protection equipment or different human resources. Our tool is based in two main principles: (1) Part of the stock of equipment at a unit that is not needed (in near future) could be shared to other units; and (2) extra stock to be shared among the units in a region can be efficiently distributed taking into account the demand of the units. The decisions are taken with the aim of minimizing certain measures of the non-covered demand in a region where units are structured in a given network. The mathematical programming models that we provide are stochastic and multiperiod with different robust objective functions. Since the proposed models are computationally hard to solve, we provide a divide-et-conquer math-heuristic approach. We report the results of applying our approach to the COVID-19 case in different regions of Spain, highlighting some interesting conclusions of our analysis, such as the great increase of treated patients if the proposed redistribution tool is applied.

Keywords: Reallocation; Sharing policies; Robust integer linear programming; Math-Heuristic; COVID-19; 91B32; 90C15; 90C10; 90B15 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11750-022-00643-3

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