School of Mathematics and Information Science, Shaanxi Normal University, Xi'an, 710119, China.
Department of Mathematics, University of Florida, Gainesville, 32611, USA.
Math Biosci Eng. 2020 Mar 16;17(4):2792-2804. doi: 10.3934/mbe.2020153.
The novel Coronavirus (COVID-19) is spreading and has caused a large-scale infection in China since December 2019. This has led to a significant impact on the lives and economy in China and other countries. Here we develop a discrete-time stochastic epidemic model with binomial distributions to study the transmission of the disease. Model parameters are estimated on the basis of fitting to newly reported data from January 11 to February 13, 2020 in China. The estimates of the contact rate and the effective reproductive number support the efficiency of the control measures that have been implemented so far. Simulations show the newly confirmed cases will continue to decline and the total confirmed cases will reach the peak around the end of February of 2020 under the current control measures. The impact of the timing of returning to work is also evaluated on the disease transmission given different strength of protection and control measures.
新型冠状病毒（COVID-19）自 2019 年 12 月以来在中国传播并造成大规模感染。这对中国和其他国家的生活和经济造成了重大影响。在这里，我们开发了一个具有二项分布的离散时间随机传染病模型来研究疾病的传播。根据 2020 年 1 月 11 日至 2 月 13 日在中国新报告的数据进行拟合，对模型参数进行了估计。接触率和有效繁殖数的估计支持迄今为止实施的控制措施的效率。模拟结果表明，在当前的控制措施下，新确诊病例将继续下降，总确诊病例将在 2020 年 2 月底左右达到峰值。还评估了在不同保护和控制措施强度下返工时间对疾病传播的影响。
