Extended SIR prediction of the epidemics trend of COVID-19 in Italy and compared with Hunan, China
Wangping Jia, Ke Han, Yang Song, Wenzhe Cao, Shengshu Wang, Shanshan Yang, Jianwei Wang, Fuyin Kou, Penggang Tai, Jing Li, Miao Liu, Yao He
doi: https://doi.org/10.1101/2020.03.18.20038570
Abstract
Background: Coronavirus Disease 2019 (COVID19) is currently a global public health threat. Outside of China, Italy is one of the most suffering countries with the COVID19 epidemic. It is important to predict the epidemics trend of COVID19 epidemic in Italy to help develop public health strategies. Methods: We used time series data of COVID 19 from Jan 22,2020 to Mar 16,2020. An infectious disease dynamic extended susceptible infected removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with similar total number of populations in Italy, was used as a comparative item.
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