Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission

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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Veröffentlicht in:arXiv.org 2020-05
Hauptverfasser: Chen, M Keith, Zhuo, Yilin, Malena de la Fuente, Rohla, Ryne, Long, Elisa F
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Disease control
Severe acute respiratory syndrome coronavirus 2
Shelter in place
Smartphones
Viral diseases
Voters
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Zhuo, Yilin
Malena de la Fuente
Rohla, Ryne
Long, Elisa F
description 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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subjects Disease control
Severe acute respiratory syndrome coronavirus 2
Shelter in place
Smartphones
Viral diseases
Voters
title Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission
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