Analyses on ICU and non-ICU capacity of government hospitals during the COVID-19 outbreak via multi-objective linear programming: An evidence from Istanbul

https://doi.org/10.1016/j.compbiomed.2022.105562Get rights and content

Highlights

  • An analysis tool is created to help capacity building at government hospitals for healthcare managers.

  • A multi-objective linear model is created to determine additional resource needs in terms of ICUs, non-ICUs and ventilators.

  • Mitigating risk of the disease infectious for healthcare professionals is one of the important concerns of this study.

  • The model can be adjusted to other contagious infection epidemics. We demonstrate a case study of the ongoing COVID-19.

Abstract

The current infectious disease outbreak, a novel acute respiratory syndrome [SARS]-CoV-2, is one of the greatest public health concerns that the humanity has been struggling since the end of 2019. Although, dedicating the majority of hospital-based resources is an effective method to deal with the upsurge in the number of infected individuals, its drastic impact on routine healthcare services cannot be underestimated. In this study, the proposed multi-objective, multi-period linear programming model optimizes the distribution decision of infected patients and the evacuation rate of non-infected patients simultaneously. Moreover, the presented model determines the number of new COVID-19 intensive care units, which are established by using existing hospital-based resources. Three objectives are considered: (1) minimization of total distance travelled by infected patients, (2) minimization of the maximum evacuation rate of non-infected patients and (3) minimization of the infectious risk of healthcare professionals. A case study is performed for the European side of Istanbul, Turkey. The effect of the uncertain length of the stay of infected patients is demonstrated via sensitivity analyses.

Keywords

Multi-objective
Resource optimization
Patient allocation
Uncertainty
COVID-19
Epidemic logistics

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