S.T.D.M. Silva . I.T.S.Piyatilake . S.S.N. Perera

Department of Mathematics, Email: madumalidineshi@gmail.com, Department of Computational Mathematics, Email: thilinisp@uom.lk, Department of Mathematics, Email: ssnp@maths.cmb.ac.lk

Received in final form on January 22, 2022

Abstract
COVID-19 is one of the worst epidemics in human history. In 2019 infected individuals were found in Wuhan, China, and subsequently, the disease was spread to the other regions in the world too. It is important to identify high risk regions in the world in the context of COVID-19 spread. The dynamics of COVID-19 transmission are complex and uncertain due to various factors such as social, biological, environmental, educational, climate and economic conditions. Fuzzy logic and fuzzy set theory are mathematical tools proven to work effectively in modelling the systems with uncertainty for which the classical approaches do not provide accurate solutions. This explains the applicability of fuzzy concepts for modelling the transmission risk. We capture the transmission risk of COVID-19 with respect to factors such as healthcare index, poverty rate, population density, number of hospital beds, social distancing, hand washing facilities and percentage of mask wearing. Fourteen countries are used to develop the model. Interactions of these factors are modelled using fuzzy operators such as Hamacher, concentration, dilation, and algebraic product. Considering literature and expert opinions, membership functions are defined for each risk factor. These membership functions are combined using the Hamacher operator to determine the overall risk of countries. Five other countries are selected for model validation. Using the developed model, three risk levels are identified. These three risk levels are compared with the total number of cases in each country to validate the proposed model.

Keywords
COVID-19, Fuzzy Sets, Hamacher Operator, Risk, Membership function, Interaction, Transmission.

Cite This Article
S.T.D.M. Silva . I.T.S.Piyatilake . S.S.N. Perera, Developing a Fuzzy Operator Based Model to Capture Transmission Risk of COVID-19, J.Innovation Sciences and Sustainable Technologies, 2(2) (2022), 91- 98. https://doie.org/10.0608/JISST.2022933728

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