Post-earthquake infectious disease risk assessment approach using AHP and MULTIMOORA with decomposed fuzzy sets

Abstract

This study introduces a novel approach to post-earthquake infectious disease risk assessment, a critical component of emergency planning for public health and safety. Focusing on the districts of the European side of Istanbul, the risk assessment is based on the opinions of three experts. The novel two-level methodology, which integrates Decomposed Fuzzy Set Analytic Hierarchy Process (DFS-AHP) with Decomposed Fuzzy Multi-objective Optimization by Ratio Analysis Plus the Full Multiplicative Form (DFS-MULTIMOORA), aims to improve decision-making under linguistic uncertainty and ambiguity. By integrating DFS-AHP with DFS-MOORA, the problems of precision and consistency in expert judgments are addressed. Criteria importance weights determined using DFS-AHP enable successful district ranking with DFS-MOORA. The results reveal that Adequacy of housing conditions is the most important sub-criteria, while Bagc & imath;lar district is identified as the highest risk due to its crowded living spaces and poor health conditions after the earthquake. Bes,iktas, exhibits the lowest risk. Among the contributions are the introduction of the DFS-AHP integrated DFS-MOORA methodology, the development of criteria and importance weights for risk assessment, and the pioneering of the implementation Multiple Criteria Decision Making (MCDM) approaches for post-earthquake infectious disease risk assessment. This study provides decision makers with a quick and effective procedure for assessing post-earthquake infectious disease risk.