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%.
@article{arxiv.2005.05469,
title = {Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission},
author = {M. Keith Chen and Yilin Zhuo and Malena de la Fuente and Ryne Rohla and Elisa F. Long},
journal= {arXiv preprint arXiv:2005.05469},
year = {2020}
}