COVID-19全球时变再生产数字:强制性和自愿性社会距离的实证分析

A. Chudik, M. Pesaran, A. Rebucci
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引用次数: 13

摘要

本文仅根据报告的感染病例数估计全球随时间变化的COVID-19繁殖数,允许漏报。估计基于一个矩条件,该矩条件可以从基于agent的COVID-19传播随机网络模型中得到。到2020年底,在再生产数量和人均病例的发展轨迹方面,结果非常不同。繁殖数量取决于传播率和易感人群的比例,或群体免疫效应。传播率的变化取决于病毒行为的变化,这反映了变异和接种疫苗,以及人们行为的变化,这反映了自愿或政府强制隔离。在我们的样本期内,突变和疫苗接种都不是主要因素,因此人们可以将传播率的变化归因于行为的变化。基于解释9个欧洲国家传播率的小组数据模型的证据表明,结果的多样性是强制性遏制措施、自愿预防性隔离以及各国政府为支持隔离而提供的经济激励措施的非线性相互作用造成的。这些影响是精确估计的,对各种假设都是可靠的。因此,社会距离政策看似不同的国家在繁殖数量方面取得了相当相似的结果。这些结果表明,忽略社交距离的自愿成分可能会在估计封锁和支持政策对传播率的影响时产生向上的偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing
This paper estimates time-varying COVID-19 reproduction numbers worldwide solely based on the number of reported infected cases, allowing for under-reporting. Estimation is based on a moment condition that can be derived from an agent-based stochastic network model of COVID-19 transmission. The outcomes in terms of the reproduction number and the trajectory of per-capita cases through the end of 2020 are very diverse. The reproduction number depends on the transmission rate and the proportion of susceptible population, or the herd immunity effect. Changes in the transmission rate depends on changes in the behaviour of the virus, reflecting mutations and vaccinations, and changes in people's behaviour, reflecting voluntary or government mandated isolation. Over our sample period, neither mutation not vaccination are major factors, so one can attribute variation in the transmission rate to variations in behaviour. Evidence based on panel data models explaining transmission rates for nine European countries indicates that the diversity of outcomes resulted from the non-linear interaction of mandatory containment measures, voluntary precautionary isolation, and the economic incentives that governments provided to support isolation. These effects are precisely estimated and robust to various assumptions. As a result, countries with seemingly different social distancing policies achieved quite similar outcomes in terms of the reproduction number. These results imply that ignoring the voluntary component of social distancing could introduce an upward bias in the estimates of the effects of lock-downs and support policies on the transmission rates.
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