Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China

Chaolong Wang; Li Liu; Xingjie Hao; Huan Guo; Qi Wang; Jiao Huang; Na He; Hongjie Yu; Xihong Lin; An Pan; Sheng Wei; Tangchun Wu

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.03.20030593 doi: medRxiv preprint delay in the predicted ending date of the epidemic when taking the unascertained cases into account (Table S4) . Therefore, understanding the proportion of unascertained cases and the rate of asymptomatic spread will be critical for pandemic prevention of Covid-19, including prioritization the surveillance and control measures. 23, 28 We demonstrated that the series of interventions has been highly effective in controlling the epidemic in Wuhan. Our estimate of R t =3.88 for the first period reflected the basic reproductive number R 0 as few interventions had been implemented by then. Some previous studies have reported varied R 0 (range 1.40 to 6.49 with a mean of 3.28) due to different data sources, time periods and statistical methods. 29 Even using the same dataset of the first 425 patients in Wuhan, an early study reported a R 0 of 2.20 based on the growth rate of the epidemic curve and the serial interval, 8 while a recent analysis based on a transmission network model reported a R 0 of 3.58, similar to our estimate. The transmissibility was higher than that for the SARS-CoV in 2003 (from 2.2 to 3.6), 30 and was consistent with the rapid spreading of Covid-19. Nevertheless, by taking drastic social distancing measures and policies of controlling the source of infection, with the tremendous joint efforts from the government, healthcare workers, and the people (Fig. 1) , R t was substantially reduced to 0.32 in Wuhan after February 2, which was encouraging for the global efforts fighting against the Covid-19 outbreak using traditional non-pharmaceutical measures. 31 Some limitations of this study need to be noted. First, while our model prediction . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.