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中国城市内部和城市之间的新冠病毒传播的封锁政策的故事:基于异质处理效应的研究。

A tale of lockdown policies on the transmission of COVID-19 within and between Chinese cities: A study based on heterogeneous treatment effect.

机构信息

Department of Strategic Management Engineering at National University of Defense Technology, Deya Rd, Kaifu District, Hunan 410073, China.

Department of Health Policy and Management at the University of Maryland, 4200 Valley Drive, College Park, MD 20742, United States.

出版信息

Econ Hum Biol. 2024 Apr;53:101365. doi: 10.1016/j.ehb.2024.101365. Epub 2024 Feb 5.

Abstract

During the early outbreak phase of COVID-19 in China, lockdowns prevailed as the only available policy tools to mitigate the spread of infection. To evaluate the impact of lockdown policies in the context of the first phase of COVID-19 pandemic, we leverage data on daily confirmed cases per million people and related characteristics of a large set of cities. The study analyzed 369 Chinese cities, among which 188 implemented lockdowns of varying severity levels from January 23 to March 31, 2020. We use nationwide Baidu Mobility data to estimate the impact of lockdown policies on mitigating COVID-19 cases through reducing human mobility. We adopt a heterogeneous treatment effect model to quantify the effect of lockdown policies on containing confirmed case counts. Our results suggest that lockdowns substantially reduced human mobility, and larger reduction in mobility occurred within-city compared to between-city. The COVID-19 daily confirmed cases per million people decreased by 9% - 9.2% for every ten-percentage point fall in within-city travel intensity in t+7 timeframe. We also find that one city's lockdowns can effectively reduce the spillover cases of the traveler's destination cities. We find no evidence that stricter lockdowns are more effective at mitigating COVID-19 risks. Our findings provide practical insights about the effectiveness of NPI during the early outbreak phase of the unprecedented pandemic.

摘要

在 COVID-19 在中国的早期爆发阶段,封锁是唯一可用的减轻感染传播的政策工具。为了评估封锁政策在 COVID-19 大流行第一阶段的影响,我们利用了每天每百万人确诊病例的数据以及大量城市的相关特征。该研究分析了 369 个中国城市,其中 188 个城市于 2020 年 1 月 23 日至 3 月 31 日实施了不同严重程度的封锁。我们利用全国性的百度移动数据来估计封锁政策通过减少人员流动对减轻 COVID-19 病例的影响。我们采用异质处理效应模型来量化封锁政策对遏制确诊病例数的影响。研究结果表明,封锁措施大大降低了人员流动性,而且市内流动性的减少要大于市际间的减少。在 t+7 时间框架内,每降低 10%的市内出行强度,每百万人的 COVID-19 日确诊病例就会减少 9%-9.2%。我们还发现,一个城市的封锁措施可以有效地减少旅行者目的地城市的溢出病例。我们没有发现更严格的封锁措施在减轻 COVID-19 风险方面更有效的证据。我们的研究结果为前所未有的大流行早期阶段非药物干预措施的有效性提供了实际的见解。

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