Yang Chayu, Wang Jin
Department of Mathematics, University of Florida, Gainesville, FL, 32611, USA.
Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN, 37403, USA.
Infect Dis Model. 2020 Dec 30;6:195-211. doi: 10.1016/j.idm.2020.12.006. eCollection 2021.
We propose a mathematical model to investigate the transmission dynamics of COVID-19. The model incorporates both human-to-human and environment-to-human transmission pathways, and employs different transmission rates to represent the epidemiological characteristics at different time periods. Using this model and publicly reported data, we perform a case study for Hamilton County, the fourth-most populous county in the state of Tennessee and a region that could represent the typical situation of COVID-19 in the United States (US). Our data fitting and simulation results show that the environment may play an important role in the transmission and spread of the coronavirus. In addition, we numerically simulate a range of epidemic scenarios and make near-term forecasts on the development and trend of COVID-19 in Hamilton County.
我们提出了一个数学模型来研究新冠病毒病（COVID-19）的传播动态。该模型纳入了人际传播和环境-人传播途径，并采用不同的传播率来表征不同时间段的流行病学特征。利用这个模型和公开报告的数据，我们对田纳西州人口第四多的汉密尔顿县进行了案例研究，该地区可以代表美国新冠病毒病的典型情况。我们的数据拟合和模拟结果表明，环境可能在冠状病毒的传播和扩散中发挥重要作用。此外，我们对一系列疫情场景进行了数值模拟，并对汉密尔顿县新冠病毒病的发展和趋势做出了近期预测。
