估计荷兰非药物干预措施对COVID-19传播的有效性。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2025-09-17 eCollection Date: 2025-09-01 DOI:10.1371/journal.pcbi.1013502
Jantien A Backer, Don Klinkenberg, Fuminari Miura, Jacco Wallinga
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引用次数: 0

摘要

在COVID-19大流行期间,采取了非药物干预措施(npi)来缓解病毒传播。评估这些措施的有效性对政策支持至关重要,但由于措施之间的相互作用、免疫力的增强、变异的出现和季节性影响,评估这些措施的有效性往往具有挑战性。这些因素使结果在很长一段时间内难以解释。使用一种机制方法,我们估计了一组npi在减少传播方面的总体有效性。我们的方法通过比较观察到的有效繁殖数(即典型感染者引起的继发感染的数量)与未采取npi的反事实繁殖数来量化有效性。反事实繁殖数解释了传染性的季节性变化、更多传染性变异的出现以及人群免疫力的变化。免疫分数是根据纵向血清学调查和疫苗接种覆盖率的年龄特异性数据重建的,考虑到由于衰退而导致的免疫丧失。我们估计了从2020年3月大流行开始到2021年11月欧米克隆变体出现期间荷兰npi的有效性。我们发现,2020年3月和4月第一波大流行期间以及2021年1月和2月,npi的有效性较高,这两个时期的措施最严格。这两个时期的有效性估计约为50%,即,如果不采取任何措施,繁殖数量将是所观察到的两倍。所提出的方法综合了来自不同来源的现有流行病学数据,以重建人口水平的免疫力。有了足够的数据,它不仅可以应用于COVID-19,还可以应用于流感等其他直接传播疾病。当获得所需数据时,这种方法可以对控制措施的有效性进行近乎实时的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission in the Netherlands.

Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission in the Netherlands.

Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission in the Netherlands.

Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission in the Netherlands.

During the COVID-19 pandemic non-pharmaceutical interventions (NPIs) were taken to mitigate virus spread. Assessing their effectiveness is essential in policy support but often challenging, due to interactions between measures, the increase of immunity, variant emergence and seasonal effects. These factors make results difficult to interpret over a long period of time. Using a mechanistic approach, we estimate the overall effectiveness of sets of NPIs in reducing transmission over time. Our approach quantifies the effectiveness by comparing the observed effective reproduction number, which is the number of secondary infections caused by a typical infected person, to a counterfactual reproduction number if no NPIs were taken. The counterfactual reproduction number accounts for seasonal variations in transmissibility, for emergence of more transmissible variants, and for changes in immunity in the population. The immune fraction is reconstructed from age-specific data of longitudinal serological surveys and vaccination coverage, taking immunity loss due to waning into account. We estimate the effectiveness of NPIs in the Netherlands from the start of the pandemic in March 2020 until the emergence of the Omicron variant in November 2021. We find that the effectiveness of NPIs was high in March and April 2020 during the first pandemic wave and in January and February 2021, coinciding with the two periods with the most stringent measures. For both periods the effectiveness was estimated at approximately 50%, i.e., without any measures the reproduction number would have been twice as high as observed. The proposed approach synthesises available epidemiological data from different sources to reconstruct the population-level immunity. With sufficient data, it can be applied not only to COVID-19 but also to other directly transmitted diseases, such as influenza. This method provides a near real-time assessment of the effectiveness of control measures when the required data are available.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
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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