Political Affiliation and Human Mobility Under Stay-at-Home Orders: A Difference-in-Difference Analysis with County and Time Fixed Effects

Abstract

Background In late March 2020, state and local governments across the country issued stay-at-home directives to slow the spread of COVID-19. However, divergent messages from political parties on the severity of COVID-19 and differing levels of support of these social distancing measures have potentially prompted differential behaviors across political groups. This study examines state-level partisan differences in changes in human mobility during stay-at-home orders. Methods Aggregated and de-identified large-scale human mobility data was collected from Cuebiq, a mobility insights platform, to measure the fraction of users that staying at home. A difference-in-difference analysis was performed to evaluate the changes in human mobility before and after stay-at-home orders were implemented by state political afflictions. Results Before March 19th, 2020, there was a 0.82% difference (SE=0.003, p<0.001) between the percent of users staying at home in republican states versus democratic states. Difference-in-difference analysis revealed that on average, democratic states experienced a 4.11% (SE = 0.006, p<0.001) greater increase in the percent of users that stayed at home compared to republican states pre-post the implementation of stay-at-home orders. States that were not issued state-wide stay-at-home orders were excluded from the study. Conclusion Evidence supports the differential changes in adherence to stay-at-home orders by state political affiliation. These results suggest that political messaging may be a strong factor in influencing social distancing behaviors.

The evolving roles of US political partisanship and social vulnerability in the COVID-19 pandemic from February 2020–February 2021

“…In other words, summarizing approximately three months' worth of mask-wearing or mobility washes out critical week-to-week fluctuations in these variables. However, other studies have overcome this limitation by using different methods to make the connection between behavior, politics, and disease outcomes [2,4,27]. Second, we are limited by certain shortcomings in our data sources: sparsity in the maskwearing data and the potential reflection of COVID-19 related effects in our data: the nursing home data used in this analysis is from 2021 and might intrinsically contain COVID-19 related effects due to the large number of deaths among elderly individuals across the pandemic.…”

“…Over the course of 2020, multiple interventions aimed at mitigating the spread of COVID-19 became highly politicized amid the hyper-partisan environment of the United States in an election year. While local political partisanship may have been and still be an important contributor to the effectiveness of pandemic management, few studies to date have explored its role beyond anecdotal observations [1][2][3][4]. In order to better understand how political partisanship may influence local pandemic response, we propose considering other possible important contributing factors including but not limited to racial demographics, income, education, and population density.…”

E quando ainda não há vacina? A importância dos hábitos de uso de mídia na adesão a intervenções não farmacológicas durante a COVID-19 no Brasil

“…Nos EUA, os eleitores republicanos mantiveram menor distanciamento social do que os democratas [Clements, 2020], reproduzindo a divisão das elites políticas expressa nas redes sociais [Green et al, 2020]. A menor adesão às INFs entre os republicanos não foi observada apenas em respostas a pesquisas, mas também por meio de dados de geolocalização [Gollwitzer et al, 2020;Prasad & Hswen, 2021]. Em comparação com os democratas, os republicanos também afirmaram que se sentiam menos vulneráveis ao vírus, consideravam-no menos grave e acreditavam que a mídia exagerava sua importância [Calvillo, Ross, Garcia, Smelter & Rutchick, 2020].…”