An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)

Tang, Biao; Bragazzi, Nicola Luigi; Li, Qian; Tang, Sanyi; Xiao, Yanni; Wu, Jianhong

We first plot the time series on the predicted number of reported cases, i.e., the number of hospitalized individuals H(t) and the predicted cumulative cases based on the updated parameters listed in Table 1 , and shown in Fig. 2 . It shows that the number of hospitalized individuals will peak on around February 4th , 2020 ( Fig. 2(A, C) ), while the predicted number of cumulative cases will continue to grow for some duration but with a slower growth rate (Fig. 2(D) ). Moreover, sensitivity analysis revealed that further enhanced measures can reduce the peak value and hence decrease the predicted cumulative case numbers (( Fig. 2(A and B) ). We caution that increasing the number of susceptible individuals may lead to an increase in the peak value and enlarge the predicted cumulative case numbers (( Fig. 2(C and D) ), emphasizing the importance of sustaining the implemented control strategies such as self-isolation in order to reduce the susceptibility. We emphasize that the peak time is defined here as the time when the number of confirmed cases reaches the maximum, so sustaining the intervention measures is critical. We repeated the procedure as above but fitted our model to the data of confirmed cases between January 23rd and February 1st , 2020 (Fig. 3) and observed the improved d I ðtÞ. As a result, in comparison with the results in Fig. 2 , we obtained higher projected cumulative confirmed cases and delayed peak time.