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e-Epidemic Model on Covid-19: A Fuzzy Approach

Published: 04 November 2021 Publication History

Abstract

The intend of this paper is to use fuzzy mathematics to dynamically formulate an e-epidemic compartmental model in the human population. The most recent edition of individual corona virus said to be COVID-19 came out as a sudden pandemic disease within human population and in the absence of vaccination and proper treatment till date, it daunting threats heavily to human lives, infecting more than 30Mpeople and death more than 830Kpeople in more than 208 countries across the globe as on February2020, which is highly alarming. When no treatment or vaccine is available till date and to avoid COVID-19 to be transmitted in the community, to follow the minimum criteria (social distancing, using masks etc.) is the only way to prevent the disease. We have studied the ways of classical basic reproduction number as well as fuzzy basic reproduction number means at what time both differ and when matched. We have also analyzed the control strategies. For this, we have taken three cases for disease in population as: low, medium and high which tells that at what condition the disease will invade the population.

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IC3-2021: Proceedings of the 2021 Thirteenth International Conference on Contemporary Computing
August 2021
483 pages
ISBN:9781450389204
DOI:10.1145/3474124
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2021

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