Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study

Jinghua Li; Yijing Wang; Stuart Gilmour; Mengying Wang; Daisuke Yoneoka; Ying Wang; Xinyi You; Jing Gu; Chun Hao; Liping Peng; Zhicheng Du; Dong Roman Xu; Yuantao Hao

Because all five modeling methods use different assumptions and tools and are likely to produce widely varying estimates of the basic reproduction number based on different aspects of the epidemic process, we combined all five estimates to produce an overall value for the basic reproduction number. We calculated a weighted average of the five basic reproduction numbers by calculating weights from a Poisson loss function, 22 which is similar to a Poisson likelihood but which was not used for estimation of parameters in any of the models. We also estimated a weighted standard error from the models. Where standard errors do not overlap point estimates in the pre-and post-closure periods, we conclude there is a significant difference in the epidemic process between the periods. Finally, we estimated the predicted epidemic trend from all models in each period, and plotted these against the observed number of cases for each period.