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一个具有明确易感染人群和无症状隔离舱的新型 COVID-19 传染病模型揭示了时机性社会隔离的意外后果。

A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing.

机构信息

Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ, United States.

Department of Mathematics, Clarkson University, Potsdam, NY, United States.

出版信息

J Theor Biol. 2021 Feb 7;510:110539. doi: 10.1016/j.jtbi.2020.110539. Epub 2020 Nov 24.

Abstract

Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic "socially distant" populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight "window of opportunity" for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections - so as to take advantage of potential new therapies and vaccines - action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule's frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.

摘要

受当前 COVID-19 疫情的启发,这项工作引入了一个流行病学模型,该模型使用单独的隔室来容纳易感人群和无症状的“社交隔离”人群。隔离指令通过流入这些隔室的速度以及减少接触来实现,从而减少疾病传播。分析了在各种不同的速率控制策略下,该系统的动态行为,并研究了基本再生数对各种参数的敏感性。该模型的一个显著特点是,在发布隔离命令时存在一个临界实施延迟(CID):虽然大约两周的延迟对感染高峰数量没有明显影响,但在这个关键时间之后发布命令,感染的发生率会大大增加。因此,为了满足医疗资源的能力,开始社会隔离有一个非实质性但又非常紧迫的“机会之窗”。然而,如果还想延迟感染高峰的时间——以便利用潜在的新疗法和疫苗,那么行动必须比 CID 更快。还模拟了不同的放松策略,结果令人惊讶。周期性放松策略表明,有一种方案可以显著抑制感染高峰负荷,但该方案对参数值和方案的频率非常敏感。此外,我们还考虑了随着时间的推移逐渐减少社会隔离措施的影响。我们发现,如果社会突然重新开放,可能会否定最初的隔离指南所取得的进展,但如果精心设计放松策略,可以减轻负面影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e1a/7840295/a867448bc999/gr1_lrg.jpg

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