Using the flexible analytic hierarchy process method to solve the emergency decision making of public health for COVID-19

Abstract

Abstract The novel coronavirus COVID-19 was initially found in December 2019 in Wuhan, China. Since then, the COVID-19 virus has rapidly spread throughout the world, causing the collapse of medical systems and economic depression. In addition to providing various relief programs, many countries have implemented various anti-epidemic measures to stop the continuous deterioration of the epidemic and maintain the stability of their economies. Especially during the COVID-19 pandemic, emergency decision making and risk assessment is an important issue for guaranteeing the stable life of the people are considered emergency multicriteria decision making (MCDM) problems. The assessment information of the criteria simultaneously includes complete, incomplete and hesitant fuzzy linguistic information in emergency MCDM problems. The analytic hierarchy process (AHP) approach can effectively process MCDM problems; however, the traditional AHP approach cannot handle the incomplete and hesitant fuzzy linguistic information of emergency MCDM problems. In order to overcome these issues, this paper proposed a novel flexible AHP method to solve emergency MCDM problems under the COVID-19 pandemic, and adopted a numerical case about public health emergency decision making and risk assessment under the COVID-19 pandemic to verify the effectiveness and correctness of the proposed flexible AHP method.