ArticleComputers in biology and medicine2022
Analyses on ICU and non-ICU capacity of government hospitals during the COVID-19 outbreak via multi-objective linear programming: An evidence from Istanbul.
Article in Computers in biology and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimal resource allocation model for COVID-19: a systematic review and meta-analysis.BMC infectious diseases · 2024Pooled it
- A stochastic programming approach for dynamic allocation of bed capacity and assignment of patients to collaborating hospitals during pandemic outbreaks.Health care management science · 2026Article
- Integrating epidemiological modeling and time-series forecasting to optimize pandemic patient allocation.International journal of health geographics · 2026Article
- Risk assessment approach for analyzing risk factors to overcome pandemic using interval-valued q-rung orthopair fuzzy decision making method.Applied soft computing · 2023Article
- Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment.BMC medical informatics and decision making · 2022Article
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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.
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