Fuzzy Logic-Based Decision Support System for Covid-19 Emergency State Determination

Abstract

The World Health Organization defined the COVID-19 outbreak as a global epidemic (pandemic) on March 11 due to the occurrence of COVID-19 cases in 113 countries outside China where the first epidemic started, and the spread and severity of the virus. The virus epidemic, which emerged in Wuhan, the capital of the Hubei region of China on 1 December 2019, has spread throughout the world.
The number of cases has exceeded 200 million and the number of deaths has exceeded 4 million. In this study, the symptoms and results of covid-19 were modeled with fuzzy logic and evaluated. In the model, the symptoms of the virus such as fever, dry cough, fatigue, loss of taste and smell, permanent pain in the chest, travel history, and sore throat were identified as input. The risk situation, quarantine situation, and isolation situation were determined as output, decision rules were created. These rules will make it easier to understand and use a model that cannot be built mathematically by building on natural languages and showing it with graphics as well as a rule table. With this study, it is predicted that it will be a model for decision-makers in the field of health.

Keywords

• Covid-19
• Fuzzy Logic
• Decision Making

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