Christopher Thron, Vianney Mbazumutima, Luis V Tamayo, Léonard Todjihounde
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引用次数: 0
Abstract
In epidemiology, the effective reproduction number is used to characterize the growth rate of an epidemic outbreak. If , the epidemic worsens, and if , then it subsides and eventually dies out. In this paper, we investigate properties of for a modified SEIR model of COVID-19 in the city of Houston, TX USA, in which the population is divided into low-risk and high-risk subpopulations. The response of to two types of control measures (testing and distancing) applied to the two different subpopulations is characterized. A nonlinear cost model is used for control measures, to include the effects of diminishing returns. Lowest-cost control combinations for reducing instantaneous to a given value are computed. We propose three types of heuristic strategies for mitigating COVID-19 that are targeted at reducing , and we exhibit the tradeoffs between strategy implementation costs and number of deaths. We also consider two variants of each type of strategy: basic strategies, which consider only the effects of controls on , without regard to subpopulation; and high-risk prioritizing strategies, which maximize control of the high-risk subpopulation. Results showed that of the three heuristic strategy types, the most cost-effective involved setting a target value for and applying sufficient controls to attain that target value. This heuristic led to strategies that begin with strict distancing of the entire population, later followed by increased testing. Strategies that maximize control on high-risk individuals were less cost-effective than basic strategies that emphasize reduction of the rate of spreading of the disease. The model shows that delaying the start of control measures past a certain point greatly worsens strategy outcomes. We conclude that the effective reproduction can be a valuable real-time indicator in determining cost-effective control strategies.
在流行病学中,有效繁殖数 R e 用于描述流行病爆发的增长率。如果 R e > 1,则疫情恶化,如果 R e 1,则疫情减弱并最终消亡。在本文中,我们研究了美国德克萨斯州休斯敦市 COVID-19 改良 SEIR 模型中 R e 的特性,该模型将人口分为低风险亚人口和高风险亚人口。该模型将人口分为低风险亚人口和高风险亚人口,并描述了 R e 对应用于两种不同亚人口的两种控制措施(检测和拉开距离)的响应。控制措施采用非线性成本模型,以包括收益递减效应。计算出将瞬时 R e 降低到给定值的最低成本控制组合。我们提出了三种旨在减少 R e 的 COVID-19 启发式策略,并展示了策略实施成本与死亡人数之间的权衡。我们还考虑了每种策略的两种变体:基本策略,即只考虑控制措施对 R e 的影响,而不考虑亚人群;高风险优先策略,即最大限度地控制高风险亚人群。结果表明,在这三种启发式策略中,最具成本效益的策略是为 R e 设定一个目标值,并采取足够的控制措施来达到该目标值。这种启发式策略首先是严格控制整个人群,然后增加检测。与强调降低疾病传播速度的基本策略相比,最大限度地控制高危人群的策略成本效益较低。模型显示,将控制措施的开始时间推迟到某一点后,战略结果会大大恶化。我们的结论是,有效繁殖率可以作为一个有价值的实时指标,用于确定具有成本效益的控制策略。
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.