TY - JOUR
T1 - Analyses on ICU and non-ICU capacity of government hospitals during the COVID-19 outbreak via multi-objective linear programming
T2 - An evidence from Istanbul
AU - Aydin, Nezir
AU - Cetinkale, Zeynep
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - COVID-19
KW - Epidemic logistics
KW - Multi-objective
KW - Patient allocation
KW - Resource optimization
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85130094327&partnerID=8YFLogxK
U2 - 10.1016/j.compbiomed.2022.105562
DO - 10.1016/j.compbiomed.2022.105562
M3 - Article
C2 - 35569338
AN - SCOPUS:85130094327
SN - 0010-4825
VL - 146
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 105562
ER -