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COVID-19 非药物干预措施:快速变化的本地政策信息的数据标注。

COVID-19 non-pharmaceutical interventions: data annotation for rapidly changing local policy information.

机构信息

Network Systems Science and Advanced Computing, Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA.

Dept of Computer Science, Stanford University, Stanford, USA.

出版信息

Sci Data. 2023 Mar 9;10(1):126. doi: 10.1038/s41597-023-01979-6.

Abstract

Understanding the scope, prevalence, and impact of the COVID-19 pandemic response will be a rich ground for research for many years. Key to the response to COVID-19 was the non-pharmaceutical intervention (NPI) measures, such as mask mandates or stay-in-place orders. For future pandemic preparedness, it is critical to understand the impact and scope of these interventions. Given the ongoing nature of the pandemic, existing NPI studies covering only the initial portion provide only a narrow view of the impact of NPI measures. This paper describes a dataset of NPI measures taken by counties in the U.S. state of Virginia that include measures taken over the first two years of the pandemic beginning in March 2020. This data enables analyses of NPI measures over a long time period that can produce impact analyses on both the individual NPI effectiveness in slowing the pandemic spread, and the impact of various NPI measures on the behavior and conditions of the different counties and state.

摘要

理解 COVID-19 大流行应对措施的范围、普遍性和影响将是未来多年丰富的研究领域。应对 COVID-19 的关键是采取非药物干预(NPI)措施,例如强制戴口罩或就地隔离令。为了未来的大流行防范,了解这些干预措施的影响和范围至关重要。鉴于大流行仍在持续,仅涵盖初始阶段的现有 NPI 研究仅提供了对 NPI 措施影响的狭隘看法。本文描述了一个美国弗吉尼亚州各县采取的 NPI 措施数据集,其中包括自 2020 年 3 月以来大流行头两年采取的措施。该数据集可用于分析长时间跨度的 NPI 措施,从而对减缓大流行传播的个别 NPI 措施的效果以及各种 NPI 措施对不同县和州的行为和状况的影响进行影响分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a96b/9998627/29a2a13acf39/41597_2023_1979_Fig1_HTML.jpg

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