Department of Mathematics, University of Manchester, United Kingdom.
Department of Mathematics, University of Manchester, United Kingdom.
J Theor Biol. 2023 Jan 21;557:111335. doi: 10.1016/j.jtbi.2022.111335. Epub 2022 Nov 2.
Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
为了识别和隔离具有传染性的个体，重复进行无症状检测已成为广泛使用的控制 SARS-CoV-2 传播的干预措施。在某些工作场所，特别是在有易感患者的卫生和社会保健环境中，定期对工作人员进行无症状检测，以降低工作场所暴发的可能性。我们根据文献中可用的数据开发了一个模型，以预测重复无症状检测对 SARS-CoV-2 传播的潜在影响。结果突出了在建模检测干预措施时需要考虑的特征，包括传染性的人群异质性和与检测阳性概率的相关性，以及对政策的遵守行为。此外，本文基于提出的传播潜力降低的模型，可以用来参数化现有的流行病学模型，而无需明确模拟检测过程。总体而言，我们发现，即使在不同的模型参数化条件下，从理论上讲，定期进行无症状检测很可能是一种非常有效的措施，可以降低工作场所的传播，前提是要遵守规定。本文作为关于“COVID-19 建模和为未来大流行做准备”主题特刊的一部分提交。
