Purely Data-driven Exploration of COVID-19 Pandemic After Three Months of the Outbreak

Authors

  • Shirali Kadyrov Faculty of Engineering and Natural Sciences, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan
  • Alibek Orynbassar Faculty of Education and Humanities Sciences, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan
  • Hayot Berk Saydaliev Business School, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan

DOI:

https://doi.org/10.5614/j.math.fund.sci.2021.53.3.2

Keywords:

basic reproduction, clustering, COVID-19, doubling period, dynamical systems, parameter estimation, SIR model

Abstract

Many research studies have been carried out to understand the epidemiological characteristics of the COVID-19 pandemic in its early phase. The current study is yet another contribution to better understand the disease properties by parameter estimation based on mathematical SIR epidemic modeling. The authors used Johns Hopkins University?s dataset to estimate the basic reproduction number of COVID-19 for five representative countries (Japan, Germany, Italy, France, and the Netherlands) that were selected using cluster analysis. As byproducts, the authors estimated the transmission, recovery, and death rates for each selected country and carried out statistical tests to see if there were any significant differences.

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Published

2021-12-03

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Articles