When is the COVID-19 Pandemic Over? Evidence from the Stay-at-Home Policy Execution in 106 Chinese Cities

Jingyuan Wang, Ke Tang, Kai Feng, Weifeng Lv
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引用次数: 16

Abstract

As more and more countries have employed stay-at-home policy to halt the spread of COVID-19, the effectiveness of this policy has become an important question to both researchers and policymakers. To answer this question, our paper empirically measures the effect of stay-at-home policy on the control of COVID-19. Using the city-level Baidu Mobility Index, measured by the total number of outside travels per day divided by the resident population, we find that reducing the number of outings can effectively decrease the new-onset cases; a 1% decline in the outing number will reduce about 1% of the new-onset-cases growth rate in 7 days (one serial interval). The critical level is a 50% drop in mobility, in which case the number of new-onset cases is lower than it was 7 days before, and hence the epidemic will gradually disappear holding this policy long enough. A strong stay-at-home policy execution with a short duration has a smaller economic cost than a loose execution with a long duration. For example, the mobility in Wuhan is down 85% after lockdown, in which case we estimate the number of new-onset cases is reduced by 50% in only 12 days.
COVID-19大流行何时结束?来自中国106个城市居家政策执行的证据
随着越来越多的国家采取居家隔离政策来遏制新冠病毒的传播,这一政策的有效性已成为研究人员和政策制定者的一个重要问题。为了回答这个问题,我们的论文实证地衡量了居家政策对COVID-19控制的影响。利用城市层面的百度流动指数,即每天外出旅行的总人数除以常住人口,我们发现减少外出次数可以有效减少新发病例;外出人数每减少1%,将使7天(一个连续间隔)内的新发病例增长率减少约1%。关键水平是流动性下降50%,在这种情况下,新发病例数比7天前要低,因此,只要坚持这一政策足够长时间,疫情就会逐渐消失。短时间内强力的“不动”政策执行比长时间内宽松的政策执行的经济成本要小。例如,武汉的流动性在封锁后下降了85%,在这种情况下,我们估计新发病例数在12天内减少了50%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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