论文标题

接触式追踪在减轻COVID-19的传播方面有多效率?数学建模方法

How Efficient is Contact Tracing in Mitigating the Spread of Covid-19? A Mathematical Modeling Approach

论文作者

Biala, T. A., Afolabi, Y. O., Khaliq, A. Q. M.

论文摘要

接触跟踪(CT)是政府和卫生官员采取的减轻新颖冠状病毒蔓延的措施之一。在本文中,我们通过开发隔离模型来评估其对病毒传播的影响来研究其功效。我们描述了covid-19的繁殖数$ {\ Mathcal {r} _0} $的影响。特别是,我们讨论了该模型参数的重要性和相关性,例如报告案例的数量,跟踪和监视策略的有效性以及传输速率与接触跟踪的传输率。我们描述了“完美跟踪”,“完美监控”和“完美报告”术语,以表明在孵化时会跟踪跟踪的接触,对跟踪的接触进行有效监测,以免引起继发性感染,并分别报告所有受感染的人。我们考虑三种特殊情况:(1)完美的监视和完美的跟踪报告案例的触点,(2)案件的完美报告以及对所报告的案例的完美监控以及(3)完美的报告和完美的报告案例触点的完美跟踪。此外,我们在接触的比例上给出了一个下限,以确保有效的复制$ {\ Mathcal {r} _c} $在下面,并描述$ {\ Mathcal {r} _c} $,以可观察到的数量和可观察的情况,例如报告和跟踪的情况的比例。使用从约翰·霍普金斯大学(John Hopkins University)获得的COVID-19数据的模型模拟模拟,该数据在美国一些选定的州表明,即使是CT的晚期干预也可以合理地减少COVID-19的传播,并减少峰值住院和死亡。

Contact Tracing (CT) is one of the measures taken by government and health officials to mitigate the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number ${\mathcal{R}_0}$ of COVID-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission rates to contact tracing. We describe the terms "perfect tracking", "perfect monitoring" and "perfect reporting" to indicate that traced contacts will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced to ensure that the effective reproduction, ${\mathcal{R}_c}$, is below one and describe ${\mathcal{R}_c}$ in terms of observable quantities such as the proportion of reported and traced cases. Model simulations using the COVID-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission of COVID-19 and reduce peak hospitalizations and deaths.

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