December 2022 Causal inference for the effect of mobility on COVID-19 deaths
Matteo Bonvini, Edward H. Kennedy, Valerie Ventura, Larry Wasserman
Author Affiliations +
Ann. Appl. Stat. 16(4): 2458-2480 (December 2022). DOI: 10.1214/22-AOAS1599


In this paper we develop statistical methods for causal inference in epidemics. Our focus is in estimating the effect of social mobility on deaths in the first year of the Covid-19 pandemic. We propose a marginal structural model motivated by a basic epidemic model. We estimate the counterfactual time series of deaths under interventions on mobility. We conduct several types of sensitivity analyses. We find that the data support the idea that reduced mobility causes reduced deaths, but the conclusion comes with caveats. There is evidence of sensitivity to model misspecification and unmeasured confounding which implies that the size of the causal effect needs to be interpreted with caution. While there is little doubt the effect is real, our work highlights the challenges in drawing causal inferences from pandemic data.

Funding Statement

Edward Kennedy gratefully acknowledges support from NSF Grant DMS-1810979.


Ventura and Wasserman are members of the Delphi Group at CMU This project arose from their work with Delphi. We are grateful for their help and support. All the data can be obtained from the Delphi website The authors would like to thank Rob Tibshirani and the reviewers for providing helpful feedback on an earlier draft of the paper.


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Matteo Bonvini. Edward H. Kennedy. Valerie Ventura. Larry Wasserman. "Causal inference for the effect of mobility on COVID-19 deaths." Ann. Appl. Stat. 16 (4) 2458 - 2480, December 2022.


Received: 1 March 2021; Revised: 1 December 2021; Published: December 2022
First available in Project Euclid: 26 September 2022

MathSciNet: MR4489219
zbMATH: 1498.62193
Digital Object Identifier: 10.1214/22-AOAS1599

Keywords: Causal inference , Covid-19 , marginal structural model

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.16 • No. 4 • December 2022
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