Dynamic Estimation of Epidemiological Parameters of COVID-19 Outbreak and Effects of Interventions on Its Spread

Hongzhe Zhang; Xiaohang Zhao; Kexin Yin; Yiren Yan; Wei Qian; Bintong Chen; Xiao Fang

A novel coronavirus has quickly spread across China and penetrated into many other countries since December 2019 1 . As of April 6, 2020, the virus has infected 83,005 individuals in China and 1,210,956 individuals globally according to WHO reports 2 . An essential step to contain or slow the outbreak of COVID-19 (i.e., the disease caused by the novel coronavirus) is to uncover its epidemiological parameters over time so that we can analyze the effect of different interventions on its spread 3 . Toward that end, a number of studies have attempted to estimate its epidemiological parameters such as the number of infected cases and the reproduction number 1, 4, 5, 6, 7, 8, 9 . A key challenge for these studies is that the officially reported number of infections (hereafter referred to as the official number) could be much lower than the true number of infections, especially in the early stage of the pandemic and at the center of the pandemic in China, the city of Wuhan 10 . This under-reporting problem could be attributed to many factors, such as insufficient amount of virus test kits and the shortage of hospital beds.