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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.