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

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.

Keywords

• basic reproduction
• clustering
• COVID-19
• doubling period
• dynamical systems
• parameter estimation