A new Mathematical Modell for COVID-19: A Fuzzy Cognitive Map Approach for Coronavirus Diseases

Abstract

The novel Coronavirus outbreak late in 2019 and early 2020, known today as COVID-19 or SARS-CoV-2. is with us. The WHO has accepted COVID-19 as a pandemic disease. The outbreak of COVID-19 has gained ground in many countries, leading towards a global health emergency. Increased national and international measures are being taken to contain the outbreak leading to total 'lockdown' of many countries directly affecting urban economies on a multi-lateral level.. This is a perspective paper, written from a classical engineering point of view only four months after detecting the COVID-19 pandemic. All known studies for COVID-19 are done based on statistical models. These statistical approaches depend solely on correlation factors. The factor of causality has not been considered due to the luck of sufficient mathematical models based on causality. Correlation does not imply causality while causality always implies correlation. The approach of Fuzzy Cognitive Maps (FCM) that is considering the causality factors is proposed, for the first time, to investigate the whole spectrum of COVID-19. An FCM model is proposed and referred as the classical FCM methods. Early theoretical simulation studies using a COVID-19 FCM are very promising. Simulations were performed and results were compared with the classical FCM approach. Useful conclusions and future research directions are provided.