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An Equity-Based Optimization Model to Solve the Location Problem for Healthcare Centers Applied to Hospital Beds and COVID-19 Vaccination

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  • Erwin J. Delgado

    (Faculty of Natural Sciences and Mathematics, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador
    Pacific International Center for Disaster Risk Reduction, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador)

  • Xavier Cabezas

    (Faculty of Natural Sciences and Mathematics, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador)

  • Carlos Martin-Barreiro

    (Faculty of Natural Sciences and Mathematics, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador
    Faculty of Engineering, Universidad Espíritu Santo, Samborondón 0901952, Ecuador)

  • Víctor Leiva

    (School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile)

  • Fernando Rojas

    (Eating Behavior Research Center, School of Nutrition and Dietetics, Faculty of Pharmacy, Universidad de Valparaíso, Valparaíso 2360102, Chile
    Center of Micro-Bioinnovation, Faculty of Pharmacy, Universidad de Valparaíso, Valparaíso 2360102, Chile)

Abstract

Governments must consider different issues when deciding on the location of healthcare centers. In addition to the costs of opening such centers, three further elements should be addressed: accessibility, demand, and equity. Such locations must be chosen to meet the corresponding demand, so that they guarantee a socially equitable distribution, and to ensure that they are accessible to a sufficient degree. The location of the centers must be chosen from a set of possible facilities to guarantee certain minimum standards for the operational viability of the centers. Since the set of potential locations does not necessarily cover the demand of all geographical zones, the efficiency criterion must be maximized. However, the efficient distribution of resources does not necessarily meet the equity criterion. Thus, decision-makers must consider the trade-off between these two criteria: efficiency and equity. The described problem corresponds to the challenge that governments face in seeking to minimize the impact of the pandemic on citizens, where healthcare centers may be either public hospitals that care for COVID-19 patients or vaccination points. In this paper, we focus on the problem of a zone-divided region requiring the localization of healthcare centers. We propose a non-linear programming model to solve this problem based on a coverage formula using the Gini index to measure equity and accessibility. Then, we consider an approach using epsilon constraints that makes this problem solvable with mixed integer linear computations at each iteration. A simulation algorithm is also considered to generate problem instances, while computational experiments are carried out to show the potential use of the proposed mathematical programming model. The results show that the spatial distribution influences the coverage level of the healthcare system. Nevertheless, this distribution does not reduce inequity at accessible healthcare centers, as the distribution of the supply of health centers must be incorporated into the decision-making process.

Suggested Citation

  • Erwin J. Delgado & Xavier Cabezas & Carlos Martin-Barreiro & Víctor Leiva & Fernando Rojas, 2022. "An Equity-Based Optimization Model to Solve the Location Problem for Healthcare Centers Applied to Hospital Beds and COVID-19 Vaccination," Mathematics, MDPI, vol. 10(11), pages 1-24, May.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1825-:d:824311
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    References listed on IDEAS

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    1. Fernando Rojas & Peter Wanke & Víctor Leiva & Mauricio Huerta & Carlos Martin-Barreiro, 2022. "Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    2. Amin Ullah & Khalid Mahmood Malik & Abdul Khader Jilani Saudagar & Muhammad Badruddin Khan & Mozaherul Hoque Abul Hasanat & Abdullah AlTameem & Mohammed AlKhathami & Muhammad Sajjad, 2022. "COVID-19 Genome Sequence Analysis for New Variant Prediction and Generation," Mathematics, MDPI, vol. 10(22), pages 1-16, November.

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