Stochastic vs. Deterministic Modeling for the Spread of COVID-19 in Small Networks
Stochastic vs. Deterministic Modeling for the Spread of COVID-19 in Small Networks
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DOI：
10.23919/acc50511.2021.9482985
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Mohammad Yousuf Mubarak;James Berneburg;Cameron Nowzari
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文献类型：
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作者：
Mohammad Yousuf Mubarak;James Berneburg;Cameron Nowzari
本文提出并分析了一种随机的网络易感-暴露-隐藏-移除（SEIR）传播模型。想象一下，一家养老院有28名老人和7名员工，其中一名员工的COVID-19检测呈阳性。不幸的是，这个测试的结果是3天后，感染者没有被确诊，而等待他们的测试结果。对于住在这个养老院的不同的人来说，现在的个人风险是什么？如果家庭可以获得两种快速COVID-19病毒检测，应该给谁，为什么？为了回答这样的问题，我们需要研究随机模型，而不是确定性模型。与绝大多数分析各种确定性模型的作品不同，在分析COVID-19对个人的风险时，需要随机模型，而不是跟踪给定地区的总体数字。更具体地说，本文比较了通过分析随机模型和确定性模型以及调查何时适合使用不同模型提供的结果。特别是，我们展示了为什么它是不适合使用确定性模型时，分析在小社区的传播，以及如何使用随机的可以更好地解决这些问题。最后，我们展示了由于COVID-19的潜伏期相对较长而产生的额外并发症，以及如何解决。一个模拟的案例研究COVID-19在一个35人的养老院的传播是用来帮助说明我们的结果。
This paper proposes and analyzes a stochastic Susceptible-Exposed-Infected-Removed (SEIR) spreading model on networks. Imagine a nursing home housing 28 seniors and 7 staff workers, in which one of the staff has tested positive for COVID-19. Unfortunately, the results of this test are 3 days late and the infected person had not been quarantining while waiting for their test results. What is now the individual risk to the different people living in this nursing home? If the home has access to two rapid COVID-19 viral tests, who should they be given to and why? In order to answer questions like this, we need to study stochastic models rather than deterministic ones. Unlike the vast majority of works that analyze various deterministic models, stochastic models are required when analyzing the risk of COVID-19 to individual people rather than tracking aggregate numbers in a given region. More specifically, this paper compares the results provided by analyzing stochastic and deterministic models and investigating when it is suitable to use the different models. In particular, we show why it is not suitable to use deterministic models when analyzing the spread in small communities and how these questions can be better addressed using stochastic ones. Finally, we show the added complications that arise due to the relatively long incubation period of COVID-19, and how it can be addressed. A simulated case study of the spread of COVID-19 in a 35-person nursing home is used to help illustrate our results.