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新冠病毒的流动性与有效繁殖率

Mobility and the effective reproduction rate of COVID-19.

作者信息

Noland Robert B

机构信息

Alan M. Voorhees Transportation Center, Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ, 08901, United States.

出版信息

J Transp Health. 2021 Mar;20:101016. doi: 10.1016/j.jth.2021.101016. Epub 2021 Jan 28.

Abstract

OBJECTIVES

Due to the infectiousness of COVID-19, the mobility of individuals has sharply decreased, both in response to government policy and self-protection. This analysis seeks to understand how mobility reductions reduce the spread of the coronavirus (SAR-CoV-2), using readily available data sources.

METHODS

Mobility data from Google is correlated with estimates of the effective reproduction rate, which is a measure of viral infectiousness (Google, 2020). The Google mobility data provides estimates of reductions in mobility, for six types of trips and activities. for US states are downloaded from an on-line platform that derives daily estimates based on data from the Covid Tracking Project (Wissel et al., 2020; Systrom et al., 2020). Fixed effects models are estimated relating mean and 80% upper level credible interval estimates to changes in mobility and a time-trend value and with both 7-day and 14-day lags.

RESULTS

All mobility variables are correlated with median and the upper level credible interval of . Staying at home is effective at reducing . Time spent at parks has a small positive effect, while other activities all have larger positive effects. The time trend is negative suggesting increases in self-protective behavior. Predictions suggest that returning to baseline levels of activity for retail, transit, and workplaces, will increase above 1.0, but not for other activities. Mobility reductions of about 20-40% are needed to achieve an below 1.0 (for the upper level 80% credible interval) and even larger reductions to achieve an below 0.7.

CONCLUSIONS

Policy makers need to be cautious with encouraging return to normal mobility behavior, especially returns to workplaces, transit, and retail locations. Activity at parks appears to not increase as much. This research also demonstrates the value of using on-line data sources to conduct rapid policy-relevant analysis of emerging issues.

摘要

目的

由于新冠病毒病(COVID-19)具有传染性,无论是响应政府政策还是出于自我保护,个人的流动性都急剧下降。本分析旨在利用现有的数据来源,了解流动性降低如何减少冠状病毒(严重急性呼吸综合征冠状病毒2,SAR-CoV-2)的传播。

方法

谷歌的流动性数据与有效繁殖率的估计值相关,有效繁殖率是衡量病毒传染性的指标(谷歌,2020年)。谷歌流动性数据提供了六种出行和活动类型的流动性降低估计值。美国各州的数据从一个在线平台下载,该平台根据新冠病毒追踪项目的数据得出每日估计值(维塞尔等人,2020年;西斯特罗姆等人,2020年)。估计固定效应模型,将均值和80%上限可信区间估计值与流动性变化、时间趋势值以及7天和14天滞后相关联。

结果

所有流动性变量均与有效繁殖率的中位数及其上限可信区间相关。待在家中对降低有效繁殖率有效。在公园度过的时间有较小的正向影响,而其他活动都有较大的正向影响。时间趋势为负,表明自我保护行为增加。预测表明,零售、交通和工作场所的活动恢复到基线水平,将使有效繁殖率升至1.0以上,但其他活动不会。需要将流动性降低约20%-40%才能使有效繁殖率低于1.0(对于80%上限可信区间),而要使有效繁殖率低于0.7则需要更大幅度的降低。

结论

政策制定者在鼓励恢复正常流动行为时需谨慎,尤其是恢复到工作场所、交通和零售场所。公园活动似乎不会使有效繁殖率增加太多。本研究还证明了利用在线数据来源对新出现问题进行与政策相关的快速分析的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f014/7843082/430d611da49b/gr1_lrg.jpg

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