Application of Fuzzy logic for the analysis of the pandemic (COVID-19), if there was no social isolation

At the end of 2019 a respiratory syndrome hit the population of China. Studies have found that this contamination was caused by the SARS-CoV-2 virus. By 2020, the coronavirus contamination spread around the world, generating a pandemic that has impacted the health of millions of people. Looking for methods to understand the spread of the pandemic is fundamental to define prevention and containment measures, the use of computer software provide a view of the evolution of contamination. Fuzzy logic is a logical technique based on Fuzzy set theory and, using this theory, it is possible to deal with uncertainties, approximate reasoning, vague and ambiguous terms, which classical logic does not allow. In order to model the system, you must define the input and output variables, write the rule sets and insert the pertinence functions with the graph type to be used. For this work, the modeling was performed having two variables in the input and each variable presented three pertinence functions, and one output variable that also had three pertinence functions and nine rules. The results obtained were coherent and demonstrated graphically what would happen to a susceptible group if they were exposed without any form of isolation or protection