Determining the location of isolation hospitals for COVID-19 via Delphi-based MCDM method.
Nezir AydinSukran SekerPublished in: International journal of intelligent systems (2021)
The existing contagious epidemic disease, [SARS]-CoV-2, has been one of the biggest public health problems that humankind combatting against since December 2019. Answering the increase in the number of infected patients during the pandemic is one of the biggest challenges for healthcare systems, where resources have already been employed by a significant number of patients. While assigning most of the resources to infected people is an effective way in a short-term planning, its bitter effects on regular healthcare cannot be undervalued. Moreover, within this plan the risk of spreading the disease to other patients and healthcare providers is another risk that should not be underestimated. Therefore, in this study, we proposed the Delphi-based multicriteria decision-making (MCDM) framework for selecting the most appropriate location for an isolation hospital serving only epidemic-based patients with mild to moderate symptoms. The integrated framework consists of Delphi, Best-Worst Method, and interval type-2 fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies. Nine most effecting criteria are considered in the evaluation of five alternative locations in a real case study conducted at the European side of Istanbul. Ataturk Airport is determined as the best location to set up an isolation hospital based on determined nine evaluation criteria. The effectiveness and robustness of the framework are analyzed through comparative and sensitivity analyses.
Keyphrases
- systematic review
- healthcare
- sars cov
- public health
- end stage renal disease
- coronavirus disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- mental health
- decision making
- peritoneal dialysis
- randomized controlled trial
- respiratory syndrome coronavirus
- depressive symptoms
- physical activity
- patient reported
- global health