Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts.
Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts.
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DOI：
10.1016/s2214-109x(20)30074-7
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发表时间：
2020-04-01
期刊：
影响因子：
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通讯作者：
Eggo, Rosalind M
中科院分区：
文献类型：
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作者：
Hellewell, Joel;Abbott, Sam;Eggo, Rosalind M
背景技术背景：病例隔离和接触者追踪用于控制传染病爆发，并已用于2019冠状病毒病（COVID-19）。这一策略能否实现控制取决于病原体和反应的特征。在这里，我们使用一个数学模型来评估隔离和接触者追踪是否能够控制COVID-19输入病例的传播。方法：我们开发了一个随机传播模型，参数化COVID-19爆发。我们使用该模型来量化接触者追踪和病例隔离在控制严重急性呼吸综合征冠状病毒2（SARS-CoV-2）样病原体方面的潜在有效性。我们考虑了不同的情况下，初始病例数，基本繁殖数（R 0），从症状发作到隔离的延迟，接触者被追踪的概率，发生在症状发作前的传播比例，以及亚临床感染的比例。我们假设隔离阻止了模型中的所有进一步传播。如果传播在12周内或在总共5000例病例之前结束，则认为疫情得到控制。我们测量了使用隔离和接触者追踪控制暴发的成功率，并量化了每周追踪到的最大病例数，以衡量公共卫生工作的可行性。然而，当R 0为2.5或3.5时，控制暴发的概率随着初始病例数的增加而降低，并且在症状出现之前传播更多。在不同的初始病例数中，R 0为1.5的大多数情况都是可控的，成功追踪的接触者不到50%。为了控制大多数疫情，R 0为2.5时，必须追踪70%以上的接触者，R 0为3.5时，必须追踪90%以上的接触者。当R 0为1.5时，症状发作和隔离之间的延迟在确定暴发是否可控方面起着最大的作用。当R 0值为2·5或3·5时，如果有40例初始病例，则只有在症状出现前发生的传播少于1%时，接触者追踪和隔离才可能可行。解释：在大多数情况下，高效的接触者追踪和病例隔离足以在3个月内控制新的COVID-19疫情。随着从症状发作到隔离的长时间延迟，通过接触者追踪确定的病例减少，以及症状出现前传播增加，控制的概率降低。这个模型可以修改，以反映最新的传播特征和更具体的定义，疫情控制，以评估当地的反应努力的潜在成功。
BACKGROUND: Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19.METHODS: We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort.FINDINGS: Simulated outbreaks starting with five initial cases, an R0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R0 of 2·5 more than 70% of contacts had to be traced, and for an R0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R0 was 1·5. For R0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset.INTERPRETATION: In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts.FUNDING: Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.