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对全球 COVID-19 政府干预措施的效果进行排名。

Ranking the effectiveness of worldwide COVID-19 government interventions.

机构信息

Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS, Vienna, Austria.

Complexity Science Hub Vienna, Vienna, Austria.

出版信息

Nat Hum Behav. 2020 Dec;4(12):1303-1312. doi: 10.1038/s41562-020-01009-0. Epub 2020 Nov 16.

Abstract

Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, R, of COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. We validate our findings with two external datasets recording 42,151 additional NPIs from 226 countries. Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. Less disruptive and costly NPIs can be as effective as more intrusive, drastic, ones (for example, a national lockdown). Using country-specific 'what-if' scenarios, we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions.

摘要

评估非药物干预(NPIs)措施在减轻 SARS-CoV-2 传播方面的效果对于制定未来的防范应对计划至关重要。在这里,我们量化了在 79 个地区实施的 6068 项分层编码的 NPIs 对 COVID-19 的有效繁殖数 R 的影响。我们提出了一种结合了四种计算技术的建模方法,这些技术融合了统计、推理和人工智能工具。我们使用记录了来自 226 个国家的 42151 项额外 NPIs 的两个外部数据集验证了我们的发现。我们的研究结果表明,适当组合 NPIs 是遏制病毒传播的必要条件。破坏性和成本较低的 NPIs 可以与更具侵入性和剧烈性的 NPIs 一样有效(例如,全国封锁)。通过使用特定于国家的“假设情景”,我们评估了 NPIs 的效果如何取决于当地情况,例如它们的采用时间,为预测未来干预措施的效果开辟了道路。

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