FUZZY COGNITIVE MAPS: A NEW MODELLING APPROACH IN TACKLING COVID-19
Coronavirus disease, first detected in late 2019 the COVID-19 pandemic has considerably affected lives of all people around the globe. The health discipline has been using extensively mathematical models to address difficult medical problems. Mathematical models cannot be useful to anyone without specific theories. The crucial and important difference between correlation and causation is analyzed and discussed. There is uncertainty and ambiguity on several aspects of the COVID-19 pandemic. The symptoms are many and vary from person to person and from geographical region to geographical region. Challenging issues of the COVID-19 pandemic are analyzed. Recently new mutations of COVID-19 have shown us how rapidly a new disease can take new roots and spread. Such events are accompanied by an explosion of clinical and epidemiological information and research. Billions of data are provided every day. Many theories are summoned to battle COVID-19 especially artificial intelligence (AI). Most techniques that are being used in the detection, diagnosis and epidemiological predictions, forecasting and social control for combating COVID-19 are using statistical theories and the correlation coefficient. The recent theories of Fuzzy Cognitive Maps (FCM) are used to model and study COVID-19. Simulation results using real data are provided and discussed. The use of Fuzzy Cognitive Maps (FCM) prove to be an effective and useful approach in studying COVID-19. Many future research directions are highlighted with concrete applications of FCM in tackling COVID-19.