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. 2024 Jan 7;21(1):67.
doi: 10.3390/ijerph21010067.

Assessing the Impact of Non-Pharmaceutical Interventions on Consumer Mobility Patterns and COVID-19 Transmission in the US

Joseph Zuccarelli  1   2 , Laura Seaman  1 , Kevin Rader  2
Affiliations

Assessing the Impact of Non-Pharmaceutical Interventions on Consumer Mobility Patterns and COVID-19 Transmission in the US

Joseph Zuccarelli et al. Int J Environ Res Public Health. .

Abstract

The initial outbreak of COVID-19 during late December 2019 and the subsequent global pandemic markedly changed consumer mobility patterns worldwide, largely in response to government-ordered non-pharmaceutical interventions (NPIs). In this study, we investigate these changes as they relate to the initial spread of COVID-19 within two states-Massachusetts and Michigan. Specifically, we use linear and generalized linear mixed-effects models to quantify the relationship between four NPIs and individuals' point-of-sale (POS) credit card transactions, as well as the relationship between subsequent changes in POS transactions and county-level COVID-19 case growth rates. Our analysis reveals a significant negative association between NPIs and daily POS transactions, particularly a dose-response relationship, in which stringent workplace closures, stay-at-home requirements, and gathering restrictions were all associated with decreased POS transactions. We also uncover a significant positive association between 12-day lagged changes in POS transactions compared to pre-pandemic baselines and county-level COVID-19 case growth rates. Overall, our study supports previous findings that early NPIs reduced human mobility and COVID-19 transmission in the US, providing policymakers with quantitative evidence concerning the effectiveness of NPIs.

Keywords: COVID-19; longitudinal study; mixed-effects modeling; mobility; policy analysis; social distancing measures.

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Conflict of interest statement

Authors J.Z. and L.S. were employed by the non-profit organization The Charles Stark Draper Laboratory. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Non-pharmaceutical intervention stringency by date (MA and MI).
Figure 2
Figure 2
Average individual POS transaction count by date.
Figure 3
Figure 3
Confirmed COVID-19 case rate (per 100k population) by date.
Figure 4
Figure 4
Δ Transactions (percentage change vs. pre−pandemic baseline) by date.
See this image and copyright information in PMC

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