Review 2: "Characterizing Responsiveness to the COVID-19 Pandemic in the United States and Canada Using Mobility Data"

Nicola Shaw

doi:doi:10.1162/2e3983f5.8fdfa002

This preprint utilizes mobile phone-derived human mobility data to characterize population responsiveness to rising Covid-19 case rates. Reviewers agree that the model and sensitivity analyses are valid, though the manuscript could have better addressed confounding.

by Nicola Shaw

Published onFeb 04, 2023

Characterizing responsiveness to the COVID-19 pandemic in the United States and Canada using mobility data

by Jean-Paul R. Soucy, David N. Fisman, Derek R. MacFadden, and Kevin A. Brown

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dx.doi.org

Description

AbstractBackgroundMobile phone-derived human mobility data are a proxy for disease transmission risk and have proven useful during the COVID-19 pandemic for forecasting cases and evaluating interventions. We propose a novel metric using mobility data to characterize responsiveness to rising case rates.MethodsWe examined weekly reported COVID-19 incidence and retail and recreation mobility from Google Community Mobility Reports for 50 U.S. states and nine Canadian provinces from December 2020 to November 2021. For each jurisdiction, we calculated the responsiveness of mobility to COVID-19 incidence when cases were rising. Responsiveness across countries was summarized using subgroup meta-analysis. We also calculated the correlation between the responsiveness metric and the reported COVID-19 death rate during the study period.FindingsResponsiveness in Canadian provinces (β= -1·45; 95% CI: -2·45, -0·44) was approximately five times greater than in U.S. states (β= -0·30; 95% CI: -0·38, -0·21). Greater responsiveness was moderately correlated with a lower reported COVID-19 death rate during the study period (Spearman’sρ= 0·51), whereas average mobility was only weakly correlated the COVID-19 death rate (Spearman’sρ= 0·20).InterpretationOur study used a novel mobility-derived metric to reveal a near-universal phenomenon of reductions in mobility subsequent to rising COVID-19 incidence across 59 states and provinces of the U.S. and Canada, while also highlighting the different public health approaches taken by the two countries.FundingThis study received no funding.Research in contextEvidence before the studyThere exists a wide body of literature establishing the usefulness of mobile phone-derived human mobility data for forecasting cases and other metrics during the COVID-19 pandemic. We performed a literature search to identify studies examining the opposite relationship, attempting to quantify the responsiveness of human mobility to changes in COVID-19 incidence. We searched PubMed on October 21, 2022 using the keywords “COVID-19”, “2019-nCoV”, or “SARS-CoV-2” in combination with “responsiveness” and one or more of “mobility”, “distancing”, “lockdown”, and “non-pharmaceutical interventions”. We scanned 46 published studies and found one that used a mobile phone data-derived index to measure the intensity of social distancing in U.S. counties from January 2020 to January 2021. The authors of this study found that an increase in cases in the last 7 days was associated with an increase in the intensity of social distancing, and that this effect was larger during periods of lockdown/shop closures.Added value of the studyOur study developed a metric of the responsiveness of mobility to rising case rates for COVID-19 and calculated it for 59 subnational jurisdictions in the United States and Canada. While nearly all jurisdictions displayed some degree of responsiveness, average responsiveness in Canada was nearly five times greater than in the United States. Responsiveness was moderately associated with the reported COVID-19 death rate during the study period, such that jurisdictions with greater responsiveness had lower death rates, and was more strongly associated with death rates than average mobility in a jurisdiction.Implications of all the available evidenceMobile phone-derived human mobility data has proven useful in the context of infectious disease surveillance during the COVID-19 pandemic, such as for forecasting cases and evaluating non-pharmaceutical interventions. In our study, we derived a metric of responsiveness to show that mobility data may be used to track the efficiency of public health responses as the pandemic evolves. This responsiveness metric was also correlated with reported COVID-19 death rates during the study period. Together, these results demonstrate the usefulness of mobility data for making broad characterizations of public health responses across jurisdictions during the COVID-19 pandemic and reinforce the value of mobility data as an infectious disease surveillance tool for answering present and future threats.

RR:C19 Evidence Scale rating by reviewer:

Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.

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Review:

In this preprint, the authors use mobile phone-derived human mobility data as a proxy for disease transmission risk, a metric that has proven useful during the COVID-19 pandemic for forecasting cases and evaluating interventions. They then propose a novel metric using mobility data to characterize responsiveness to rising case rates. Using this model, they examine weekly reported COVID-19 incidence and retail and recreation mobility from Google Community Mobility Reports for 50 U.S. states and nine Canadian provinces from December 2020 to November 2021. For each jurisdiction, they calculated the responsiveness of mobility to COVID-19 incidence as case numbers rose. Responsiveness across countries was summarized using subgroup meta-analysis. They also calculated the correlation between the responsiveness metric and the reported COVID-19 death rate during the study period.

Ultimately, the authors’ findings are noteworthy as they contribute to a broader research understanding. The manuscript cites current literature and contextualizes their contribution to the subject area. Limitations are discussed and addressed well, and the preprint has the potential to impact the implementation of policies and programs. It is clearly and accurately presented, well-structured and well-written, and has the potential to reach key audiences. This being said, the authors could have further discussed equity, rights and diversity. The addition of a section clearly stating their approach to these initiatives would be beneficial.

Review 2: "Characterizing Responsiveness to the COVID-19 Pandemic in the United States and Canada Using Mobility Data"

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