Department of Mathematics, State University of New York at New Paltz, New Paltz, NY, 12561, USA.
Departments of Mathematics and Mechanical Engineering, State University of New York at New Paltz, New Paltz, NY, 12561, USA.
Sci Rep. 2020 Dec 4;10(1):21256. doi: 10.1038/s41598-020-77628-4.
The 2019 Novel Corona virus infection (COVID 19) is an ongoing public health emergency of international focus. Significant gaps persist in our knowledge of COVID 19 epidemiology, transmission dynamics, investigation tools and management, despite (or possibly because of) the fact that the outbreak is an unprecedented global threat. On the positive side, enough is currently known about the epidemic process to permit the construction of mathematical predictive models. In our work, we adapt a traditional SEIR epidemic model to the specific dynamic compartments and epidemic parameters of COVID 19, as it spreads in an age-heterogeneous community. We analyze management strategies of the epidemic course (as they were implemented through lockdown and reopening procedures in many of the US states and countries worldwide); however, to more clearly illustrate ideas, we focus on the example of a small scale college town community, with the timeline of control measures introduced in the state of New York. We generate predictions, and assess the efficiency of these control measures (closures, mobility restrictions, social distancing), in a sustainability context.
2019 年新型冠状病毒感染（COVID-19）是一场备受国际关注的持续公共卫生紧急事件。尽管（或者可能是因为）疫情是一场前所未有的全球威胁，但我们对 COVID-19 的流行病学、传播动力学、调查工具和管理的了解仍然存在重大差距。从积极的方面来看，我们目前对疫情发展过程已经有足够的了解，可以构建数学预测模型。在我们的工作中，我们将传统的 SEIR 传染病模型适用于 COVID-19 在年龄异质社区中的特定动态隔室和流行参数。我们分析了疫情过程的管理策略（因为这些策略在全球许多美国各州和国家通过封锁和重新开放程序实施）；然而，为了更清楚地说明问题，我们以纽约州引入的控制措施时间表为例，重点关注一个小型大学城社区。我们生成预测，并在可持续性背景下评估这些控制措施（关闭、流动性限制、社会隔离）的效率。
