Modelling and Predictive Analytics of COVID-19 Transmission Using Gustafson–Kessel Fuzzy Clustering Approach. (25th March 2022)

• Record Type: Journal Article
• Authors: Vijayakarthick, M; Sivaraman, E; Sathishbabu, S; Vinoth, N; Sivaraj, S N
• Is Part Of: Computer journal. Volume 65:Number 12(2022)
• Page Start: 3240
• Page End: 3249
• Publication Date: 2022-03-25
• Subjects: mathematical modelling -- COVID-19 -- G-K Fuzzy clustering -- epidemic -- numerical simulations; Computers -- Periodicals; 005.1
• DOI: 10.1093/comjnl/bxac022
• Languages: English
• ISSNs: 0010-4620

Abstract

Abstract: A novel Corona virus disease 2019 (COVID-19) outbreak is declared as the international public health emergency concern by the World Health Organization in the month of March 2020. This viral disease invented from China in the month of December 2019 has previously caused havoc around the world, including India. In this paper, efficient mathematical models using Gustafson–Kessel fuzzy clustering approach for the transmission of the COVID-19 are developed by considering the actual reported cases in the state of Tamil Nadu, India. The results proved a good concord between the reported data and the estimated data given by the proposed models. Moreover, the developed models are also capable to predict the requirements of beds in hospitals on the month of August 2020 in Tamil Nadu, India. Also, this work suggests strictly implementing/extending the complete lockdown for at least 21 days in the month of August 2020 and immediate separation of infected cases are the positive steps to reduce the spread of novel corona virus in Tamil Nadu state, India.