Optimizing COVID-19 control with asymptomatic surveillance testing in a university environment.
Optimizing COVID-19 control with asymptomatic surveillance testing in a university environment.
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DOI：
10.1016/j.epidem.2021.100527
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发表时间：
2021-12
期刊：
影响因子：
3.8
通讯作者：
Boots M
中科院分区：
文献类型：
--
作者：
Brook CE;Northrup GR;Ehrenberg AJ;IGI SARS-CoV-2 Testing Consortium;Doudna JA;Boots M
由无症状或症状前感染引起的传播事件所占比例很高，这使得新冠肺炎的病原体SARS-CoV-2很难通过基于症状的隔离和接触者追踪的传统非药物干预(NPI)进行控制。因此，许多美国大学开发了无症状监测检测实验室，以增强NPI并在2020-2021学年(AY)控制校园疫情；其中几个实验室在2021-2022学年继续支持校园无症状监测努力。在疫情最严重的时候，我们在加州大学伯克利分校建立了新冠肺炎动力学的随机分支过程模型，以在大学环境中提供最优控制策略建议。我们的模型结合了以群体规模限制的形式进行的行为干预，以阻止超级传播、基于症状的隔离和接触者追踪，以及无症状监测测试。我们发现，行为干预提供了一种具有成本效益的疫情控制手段：群体规模限制在6人或更少极大地减少了超级传播，快速隔离有症状的感染可以阻止流行病的上升，这取决于人口中无症状传播的频率。监测检测可以克服围绕无症状感染的不确定性，最有效的方法是优先考虑频繁检测，并迅速周转隔离，而不是检测敏感性。重要的是，接触者追踪放大了所有感染隔离对人群的影响，即使是延迟的干预措施也是有效的。以行为为基础的NPI和无症状监测的结合也减少了每日病例计数的变化，以产生更可预测的流行病。此外，对少数传播高危人群进行有针对性、密集的检测，可以有效控制新冠肺炎疫情对周边人群的影响。即使在AY2021-2022年的一些高度接种疫苗的大学环境中，无症状监测检测也提供了一种有效的手段来识别突破性感染，阻止继续传播，并减少总病例量。我们向其他学术或专业团体提供此蓝图和易于实施的建模工具，以导航最佳重返工作的策略。
The high proportion of transmission events derived from asymptomatic or presymptomatic infections make SARS-CoV-2, the causative agent in COVID-19, difficult to control through the traditional non-pharmaceutical interventions (NPIs) of symptom-based isolation and contact tracing. As a consequence, many US universities developed asymptomatic surveillance testing labs, to augment NPIs and control outbreaks on campus throughout the 2020–2021 academic year (AY); several of those labs continue to support asymptomatic surveillance efforts on campus in AY2021–2022. At the height of the pandemic, we built a stochastic branching process model of COVID-19 dynamics at UC Berkeley to advise optimal control strategies in a university environment. Our model combines behavioral interventions in the form of group size limits to deter superspreading, symptom-based isolation, and contact tracing, with asymptomatic surveillance testing. We found that behavioral interventions offer a cost-effective means of epidemic control: group size limits of six or fewer greatly reduce superspreading, and rapid isolation of symptomatic infections can halt rising epidemics, depending on the frequency of asymptomatic transmission in the population. Surveillance testing can overcome uncertainty surrounding asymptomatic infections, with the most effective approaches prioritizing frequent testing with rapid turnaround time to isolation over test sensitivity. Importantly, contact tracing amplifies population-level impacts of all infection isolations, making even delayed interventions effective. Combination of behavior-based NPIs and asymptomatic surveillance also reduces variation in daily case counts to produce more predictable epidemics. Furthermore, targeted, intensive testing of a minority of high transmission risk individuals can effectively control the COVID-19 epidemic for the surrounding population. Even in some highly vaccinated university settings in AY2021–2022, asymptomatic surveillance testing offers an effective means of identifying breakthrough infections, halting onward transmission, and reducing total caseload. We offer this blueprint and easy-to-implement modeling tool to other academic or professional communities navigating optimal return-to-work strategies.
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DOI：
10.1098/rsif.2020.0393
发表时间：
2020-11
期刊：
Journal of the Royal Society, Interface
影响因子：
--
作者：
Hébert-Dufresne L;Althouse BM;Scarpino SV;Allard A
通讯作者：
Allard A
影响因子：
8.8
作者：
Bordi, Licia;Piralla, Antonio;Capobianchi, Maria Rosaria
通讯作者：
Capobianchi, Maria Rosaria
影响因子：
7.7
作者：
Emery JC;Russell TW;Liu Y;Hellewell J;Pearson CA;CMMID COVID-19 Working Group;Knight GM;Eggo RM;Kucharski AJ;Funk S;Flasche S;Houben RM
通讯作者：
Houben RM
影响因子：
3.8
作者：
Kain MP;Childs ML;Becker AD;Mordecai EA
通讯作者：
Mordecai EA
DOI：
10.1098/rspa.1927.0118
发表时间：
1927-08-01
期刊：
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER
影响因子：
--
作者：
Kermack, WO;McKendrick, AG
通讯作者：
McKendrick, AG