Selecting effective ways to prevent COVID-19 spread using the Fuzzy Analytic Hierarchy Process (FAHP) method

The COVID-19 pandemic has had a significant impact on global health and economies. This study aims to identify highly effective prevention strategies for mitigating the spread of COVID-19 using the Fuzzy Analytic Hierarchy Process (FAHP) method. The FAHP is a fuzzy logic-based extension of the Analytic Hierarchy Process (AHP) technique, allowing for the consideration of both tangible and intangible criteria. The study focuses on seven key criteria: social/physical measures, health monitoring, avoidance of unnecessary contact, hygiene practices, immunity/fitness, healthy diet, and sharing personal items. By involving three decision-makers, including a nurse, a Medical Officer (MO), and a Medical Assistant (MA), the relative weights of these criteria are calculated using pair-wise comparisons and Buckley's approach. The findings reveal that hygiene emerges as the most critical factor in preventing the spread of COVID-19, followed by social/physical measures and health monitoring. The study provides valuable insights for policymakers and healthcare professionals in selecting and implementing effective preventive measures to control the spread of COVID-19.