Purely Data-driven Exploration of COVID-19 Pandemic After Three Months of the Outbreak
Kadyrov S. Orynbassar A. Saydaliev H.B.
3 December 2021Institute for Research and Community Services, Institut Teknologi Bandung
Journal of Mathematical and Fundamental Sciences
2021#53Issue 3358 - 368 pp.
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.
Basic reproduction , Clustering , COVID-19 , Doubling period , Dynamical systems , Parameter estimation , SIR model
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Faculty of Engineering and Natural Sciences, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan
Faculty of Education and Humanities Sciences, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan
Business School, Suleyman Demirel University, Kaskelen, Almaty, 040900, Kazakhstan
Mathematical Methods in Economics, Tashkent State University of Economics, Tashkent, 100003, Uzbekistan
Faculty of Engineering and Natural Sciences
Faculty of Education and Humanities Sciences
Business School
Mathematical Methods in Economics
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