COVID-19 poses many challenges for hospitals around the world. Each country attempts to solve the problems in its hospitals using different methods. In Turkey, two pandemic hospitals were built in İstanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals. This study focuses on the methods used for site selection for a pandemic hospital in Atakum, a district of Samsun City, Turkey. As a solution to the problem, initially, spatial analysis was performed using GIS to produce maps based on seven criteria obtained from the insight of an expert team. Analytic hierarchy process (AHP) augmented by interval-valued Pythagorean fuzzy numbers (PFNs) was then used to determine weights for the criteria. Distance to transportation network was the most important criterion influencing the selection process and the least significant one was the distance to fire stations. Based on the criteria weights, and five rules specified by the expert team, 13 suitable locations for a pandemic hospital were determined using GIS. The technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the final ranking of 13 alternative locations (A1-A13). A10 was identified as the most appropriate site and A11 as the least appropriate site for a pandemic hospital. Finally, sensitivity analysis was performed to investigate how changes in weight values of the criteria affect the ranking of the alternatives.

Occupational health and safety (OHS) risk assessment studies have gained importance recently as a result of increasing occupational accidents and occupational diseases. The health sector has a greater risk than many sectors for occupational accidents and occupational diseases. Although the health sector is one of the priority sectors in Turkey, OHS practices have not been fully implemented in this field. For this reason, this study adopts a two-stage approach to assess the OHS risks in the health sector by combining the Fine-Kinney and multi-criteria hesitant fuzzy linguistic term set (HFLTS) methods. The proposed method was applied to the OHS risks in the operating room of a public hospital in Turkey. As a solution to the problem, first, the potential hazards and related risks in the operating room were determined by the experts. In this first stage, 44 hazards were determined from the opinions of experts and records of past incidents. Parameter weights were then determined using the multi-criteria HFLTS method. The multi-criteria HFLTS method was used to evaluate seven hazards to be categorized as substantial-risk or higher according to the Fine-Kinney method, taking into account parameter weights. Sensitivity analysis was then carried out. Finally, actions were taken to mitigate the risks.

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Inclusion of cost factor in addition to probability, frequency, and severity factors  Risk assessment using MC-HFLTS  Comparative analysis for pre-improvement and post-improvement conditions According to the occupational health and safety law, it is necessary to take protective and preventive measures against risks by conducting risk assessment to ensure occupational health and safety in the workplaces. Many qualitative or quantitative methods are used in occupational health and safety risk assessment. In this study, which offers a new perspective on the Fine-Kinney method which is widely used in workplaces, "Cost" factor was included in addition to the "Probability", "Frequency", and "Severity" factors and a risk assessment model based on Multi-Criteria Hesitant Fuzzy Linguistic Term Sets (MC-HFLTS) was proposed. Figure A. The flow chart of the proposed method Purpose: The aim of this study is to determine the weights of factors, evaluate the hazards, determine the weights of measures, and take corrective and preventive control measures by using the proposed model. Theory and Methods: In this study "cost" factor was included in addition to the "probability", "frequency", and "severity" factors used in Fine-Kinney method and a risk assessment model based on Multi-Criteria HFLTS was implemented in the molding unit of a company operating in the plastics industry. Firstly, the hazards were determined in line with the opinions of the experts and the weights of factors were determined using MC-HFLTS method and then the hazards were prioritized on the basis of factors. Following the assessment of the hazards, measures that could be taken were weighted by using the same method and necessary measures were taken. Results: The most important factor was the "Severity" and the hazard type with the highest weight was determined as "Hazards that may cause fire and explosion". After improvement, the hazards were reevaluated using the same method and the rankings were compared. Conclusion: It is appropriate to use the proposed to evaluate the occupational health and safety risks. For future work, the number of factors may be increased and sensitivity analysis may be performed to show the robustness of the decision-making process.