Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission
Accurately estimating the effectiveness of stay-at-home orders (SHOs) on reducing social contact and disease spread is crucial for mitigating pandemics. Leveraging individual-level location data for 10 million smartphones, we observe that by April 30th---when nine in ten Americans were under a SHO--...
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Zusammenfassung: | Accurately estimating the effectiveness of stay-at-home orders (SHOs) on
reducing social contact and disease spread is crucial for mitigating pandemics.
Leveraging individual-level location data for 10 million smartphones, we
observe that by April 30th---when nine in ten Americans were under a
SHO---daily movement had fallen 70% from pre-COVID levels. One-quarter of this
decline is causally attributable to SHOs, with wide demographic differences in
compliance, most notably by political affiliation. Likely Trump voters reduce
movement by 9% following a local SHO, compared to a 21% reduction among their
Clinton-voting neighbors, who face similar exposure risks and identical
government orders. Linking social distancing behavior with an epidemic model,
we estimate that reductions in movement have causally reduced SARS-CoV-2
transmission rates by 49%. |
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DOI: | 10.48550/arxiv.2005.05469 |