Tracking Public and Private Responses to the COVID-19 Epidemic

Abstract

This paper examines the determinants of social distancing during the COVID-19 epidemic. We classify state and local government actions, and we study multiple proxies for social distancing based on data from smart devices. Mobility fell substantially in all states, even ones that have not adopted major distancing mandates. There is little evidence, for example, that stay-at-home mandates induced distancing. In contrast, early and information-focused actions have had bigger effects. Event studies show that first case announcements, emergency declarations, and school closures reduced mobility by 1-5% after 5 days and 7-45% after 20 days. Between March 1 and April 11, average time spent at home grew from 9.1 hours to 13.9 hours. We find, for example, that without state emergency declarations, event study estimates imply that hours at home would have been 11.3 hours in April, suggesting that 55% of the growth comes from emergency declarations and 45% comes from secular (non-policy) trends. State and local government actions induced changes in mobility on top of a large response across all states to the prevailing knowledge of public health risks. Early state policies conveyed information about the epidemic, suggesting that even the policy response mainly operates through a voluntary channel.

Rethinking Lockdown Policies in the Pre-Vaccine Era of COVID-19: A Configurational Perspective

“…Stay-at-home policies are among the most frequently discussed measures in the literature. They have been considered to be the most conservative and effective anti-COVID-19 measures since the beginning of the pandemic, as such policies reduce social contact and maximise social distancing [ 18 , 20 ]. Travel restrictions constitute another important measure discussed in the literature.…”

“…However, some researchers note that school closures may have a counterproductive effect of COVID-19 contamination. Whereas school closures may increase community awareness of infection prevention, they are less effective than other government intervention measures in reducing the death toll due to the resulting possibility of increased family travel [ 18 , 28 ].…”

“…Consequently, even with the availability of vaccines, the significance of NPIs has been constantly reiterated by governments, public health experts, and medical practitioners [ 14 , 15 ]. The aim of NPIs is to reduce the spread of the virus by limiting human-to-human contact [ 16 , 17 ] through social distancing [ 18 ] and lockdown measures [ 19 ]. However, it is difficult to assess the effectiveness of such measures in containing the pandemic for the following reasons.…”

“…Several studies have examined the significance of NPIs, highlighting their importance in controlling the pandemic [ 18 , 25 , 26 , 27 ]. However, two research limitations can be identified.…”

Do Human Mobility Network Analyses Produced from Different Location-based Data Sources Yield Similar Results across Scales?

“…Studies related to social impact delved into socio-economic gaps in mobility reduction (Fraiberger et al, 2020) and mobility change and association with social distancing (Bourassa, Sbarra, Caspi, & Moffitt, 2020). Studies related to regulations and policies investigated mobility changes and association with national lockdown (Pepe et al, 2020), mobility and control measures on traffic safety (Zhang et al, 2021), modeling human mobility trends under non-pharmaceutical interventions (Hu et al, 2021), the impact of restricting staff mobility between nursing homes (Jones et al, 2021), and public and private responses to government actions (Gupta et al, 2021). Studies related to predicting the future state of the pandemic include early warnings for reopening of U.S. universities (Mehrab et al, 2020), evaluating proximity metrics in predicting the spread (Mehrab, Adiga, Marathe, Venkatramanan, & Swarup, 2021), opportunities for local containment , and spatiotemporal risk scores (Rambhatla, Zeighami, Shahabi, Shahabi, & Liu, 2022).…”