A fuzzy approach in the study of COVID-19 pandemic in Brazil

Abstract

PurposeThe COVID-19 pandemic has spread widely through the world. Most countries impose severe intervention measures to contain the spread of the virus, and this worldwide scenario has motivated the development of researches in all areas of knowledge. In this context, this paper presents a study about how intervention measures such as lockdown, partial lockdown, and no-lockdown help to impede the extent of the severe outbreak of COVID-19.MethodsSince mathematical models are used to describe population dynamics and the behavior of epidemics, this paper presents a fuzzy approach to describe the behavior of new daily cases of COVID-19 in Brazil based on the p-fuzzy dynamic systems, considering as input variables, the infected population and the environment action. The evaluated output variable is the level of infestation.ResultsThe results of a fuzzy model showed that intervention measures play a crucial role in determining the success of COVID-19 eradication programs, while there is no vaccine available for all the population. The proposed fuzzy model was developed by posing intervention measures and the results showed that to consider partial-lockdown helped to slow down the transmission rates of COVID-19 in the population, however the total lockdown is more effective, while the vaccine is not available.ConclusionTherefore, mathematical models consist of an effective tool to investigate the situation with intervention strategies and estimate the potential benefits and costs of different strategies. The fuzzy model proposed assists government decision-making in order to minimize the economic impacts caused by the pandemic.