Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies.

IF 4.3 2区 生物学 PLoS Computational Biology Pub Date : 2023-09-01 DOI:10.1371/journal.pcbi.1011423
Kun Zhang, Zhichu Xia, Shudong Huang, Gui-Quan Sun, Jiancheng Lv, Marco Ajelli, Keisuke Ejima, Quan-Hui Liu
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Abstract

There are many contrasting results concerning the effectiveness of Test-Trace-Isolate (TTI) strategies in mitigating SARS-CoV-2 spread. To shed light on this debate, we developed a novel static-temporal multiplex network characterizing both the regular (static) and random (temporal) contact patterns of individuals and a SARS-CoV-2 transmission model calibrated with historical COVID-19 epidemiological data. We estimated that the TTI strategy alone could not control the disease spread: assuming R0 = 2.5, the infection attack rate would be reduced by 24.5%. Increased test capacity and improved contact trace efficiency only slightly improved the effectiveness of the TTI. We thus investigated the effectiveness of the TTI strategy when coupled with reactive social distancing policies. Limiting contacts on the temporal contact layer would be insufficient to control an epidemic and contacts on both layers would need to be limited simultaneously. For example, the infection attack rate would be reduced by 68.1% when the reactive distancing policy disconnects 30% and 50% of contacts on static and temporal layers, respectively. Our findings highlight that, to reduce the overall transmission, it is important to limit contacts regardless of their types in addition to identifying infected individuals through contact tracing, given the substantial proportion of asymptomatic and pre-symptomatic SARS-CoV-2 transmission.

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评估测试跑道隔离物对新冠肺炎管理和替代策略的影响。
关于测试追踪隔离(TTI)策略在缓解严重急性呼吸系统综合征冠状病毒2型传播方面的有效性,有许多对比结果。为了阐明这一争论,我们开发了一种新的静态-时间多重网络,该网络表征了个体的规则(静态)和随机(时间)接触模式,并利用历史新冠肺炎流行病学数据校准了SARS-CoV-2传播模型。我们估计,单独的TTI策略无法控制疾病传播:假设R0=2.5,感染发病率将降低24.5%。检测能力的提高和接触者追踪效率的提高只是略微提高了TTI的有效性。因此,我们研究了TTI策略与反应性社交距离政策相结合的有效性。限制临时接触层的接触不足以控制流行病,需要同时限制两层的接触。例如,当反应性距离策略分别断开静态层和时间层上30%和50%的接触时,感染攻击率将降低68.1%。我们的研究结果强调,鉴于严重急性呼吸系统综合征冠状病毒2型无症状和症状前传播的比例很大,除了通过接触者追踪识别感染者外,为了减少总体传播,重要的是限制接触者,无论其类型如何。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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