首页> 外文期刊>Globalization and Health >Using volunteered geographic information to assess mobility in the early phases of the COVID-19 pandemic: a?cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020
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Using volunteered geographic information to assess mobility in the early phases of the COVID-19 pandemic: a?cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020

机译:使用志愿地理信息评估Covid-19大流行早期阶段的移动性:a?2月2日至2020年3月22日的22个国家的四个城市的交通城市时间序列分析

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OBJECTIVES:Restricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different non-pharmaceutical countermeasures in the earlier stages of the pandemic is not well-understood.DESIGN:Trends were evaluated using Citymapper's mobility index covering 2nd to 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings.SETTING:41 cities worldwide.MAIN OUTCOME MEASURES:Citymapper's mobility index.RESULTS:Mobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r?=?-?0.75, p??0.001). After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36 to 15.7%), 15.0% for workplace closures (95% CI: 10.2 to 19.8%), 7.09% for cancelling public events (95% CI: 1.98 to 12.2%), 18.0% for closing public transport (95% CI: 6.74 to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85 to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment.CONCLUSIONS:Understanding the effect of public policy on mobility in the early stages is crucial to slowing and reducing COVID-19 transmission. By using Citymapper's mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful.
机译:目标:限制移动性是降低接触率和防止Covid-19传输的中心旨在。然而,在大流行早期的阶段对不同非药物对策的影响并不适应。使用CityMapper的2020年3月26日的CityMapper的移动性指数评估了典型使用期的百分比从0%的百分比评估作为最低,100%正常。中国和印度没有涵盖。多变量固定效果模型用于估计在介绍之前和之后限制移动性的政策的关联。使用牛津Covid-19政府反应严格指数进行评估的政策限制以及编码学校和工作场所关闭,运输限制以及取消群众集合的措施。全球41个城市.Main成果措施:CityMapper的流动性索引。结果:在三月整个主要城市中,移动性拒绝。在欧洲城市中看到较大的下降。 Covid-19政府反应严格指数与流动性下降强烈有关(R?=? - ?0.75,P?<0.001)。在调整时间趋势后,我们观察到实施非药物对策与学校闭合的流动性下降有关(95%CI:4.36至15.7%),工作场所闭塞15.0%(95%CI:10.2取消公共活动的7.09%(95%CI:1.98至12.2%),收盘公共交通的18.0%(95%CI:6.74至29.2%),限制内部运动的13.3%(95%CI: 8.85至17.8%)和国际旅行管制的5.30%(95%CI:1.69至8.90)。相反,正如预期的那样,人口流动变化和财政或货币措施或紧急医疗投资之间没有关联。结论:了解公共政策在早期阶段对流动性的影响至关重要,对减缓和减少Covid-19传输至关重要。通过使用CityMapper的流动性指数,这项工作提供了有关流动性趋势和不同政策干预措施的影响的第一个证据,这表明公共交通工具,工作场所和学校的闭包特别有影响。

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