Epidemic analysis of COVID-19 in China by dynamical modeling

Liangrong Peng; Wuyue Yang; Dongyan Zhang; Changjing Zhuge; Liu Hong

It is noted that here we assume the cure rate λ and the mortality rate κ are both time dependent. As confirmed in Fig. 2a -d, the cure rate λ(t) is gradually increasing with the time, while the mortality rate κ(t) quickly decreases to less than 1% and becomes stabilized after Jan. 30th. This phenomenon is likely raised by the assistance of other emergency medical teams, the application of new drugs, etc. Furthermore, the average contact number of an infectious person is calculated in Fig. 2e-f and could provide some clue on the infection rate. It is clearly seen that the average contact number is basically stable over time, but shows a remarkable difference among various regions, which could be attributed to different quarantine policies and implements inside and outside Hubei (or Wuhan), since a less severe region is more likely to inquiry the close contacts of a confirmed case. A similar regional difference is observed for the severe condition rate too. In Fig. 2g -h, Hubei and Wuhan overall show a much higher severe condition rate than Shanghai. Although it is generally expected that the patients need a period of time to become infectious, to be quarantined, or to be recovered from illness, but we do not find a strong evidence for the necessity of including time delay (see SI for more details). As a result, the time-delayed equations are not considered in the current work for simplicity.