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

Abstract

The COVID-19 pandemic has had intense, heterogeneous impacts on different communities and geographies in the United States. We explore county-level associations between COVID-19 attributed deaths and social, demographic, vulnerability, and political variables to develop a better understanding of the evolving roles these variables have played in relation to mortality. We focus on the role of political variables, as captured by support for either the Republican or Democratic presidential candidates in the 2020 elections and the stringency of state-wide governor mandates, during three non-overlapping time periods between February 2020 and February 2021. We find that during the first three months of the pandemic, Democratic-leaning and internationally-connected urban counties were affected. During subsequent months (between May and September 2020), Republican counties with high percentages of Hispanic and Black populations were most hardly hit. In the third time period –between October 2020 and February 2021– we find that Republican-leaning counties with loose mask mandates experienced up to 3 times higher death rates than Democratic-leaning counties, even after controlling for multiple social vulnerability factors. Some of these deaths could perhaps have been avoided given that the effectiveness of non-pharmaceutical interventions in preventing uncontrolled disease transmission, such as social distancing and wearing masks indoors, had been well-established at this point in time.

Misinformation, Trust, and Use of Ivermectin and Hydroxychloroquine for COVID-19

“…None of these were simple proxies for political affiliation, which was included as a covariate in all regression models; the effects of trust in institutions persisted after accounting for trust in Donald Trump. This finding counters many narratives that focus on how partisan divides drive gaps in COVID-19–related behaviors . This distinction is important insofar as altering one’s party identification may be an unrealistic bar, whereas combating misinformation and trying to build institutional trust may be more feasible …”

“…This finding counters many narratives that focus on how partisan divides drive gaps in COVID-19-related behaviors. 6 This distinction is important insofar as altering one's party identification may be an unrealistic bar, whereas combating misinformation and trying to build institutional trust may be more feasible. 20 More generally, endorsement of misinformation related to COVID-19 has been shown to decrease the intention to vaccinate against COVID-19, to decrease the belief that it is required for herd immunity, and to correlate with forgoing various COVID-19 prevention behaviors.…”

“…5 Their use thus introduced inefficiencies and expense as well as potential adverse effects on health and may help explain the observed association between more misinformation-prone counties and greater COVID-19 death rates. 6 In light of the potential consequences of non-evidence-based treatment, to inform future pandemic responses, we sought to better understand the prevalence of such treatment during the COVID-19 pandemic and the features associated with its use. Prior studies [1][2][3][4] using prescription databases may not capture overall prevalence of non-evidence-based treatment use if these medications were acquired in other ways and have not described the full range of sociodemographic features associated with their use.…”

“…Beyond a lack of efficacy, such prescriptions were associated with risk of toxic effects . Their use thus introduced inefficiencies and expense as well as potential adverse effects on health and may help explain the observed association between more misinformation-prone counties and greater COVID-19 death rates …”

Disease, Scapegoating, and Social Contexts: Examining Social Contexts of the Support for Racist Naming of COVID-19 on Twitter

“…Seventh, political party affiliation at the county level is associated with COVID-19 spread. Democratic-leaning urban counties were affected during the early months of the pandemic (Kaashoek et al 2022). Also, Republicans are found to be less likely to use Twitter than Democrats (Perrin and Anderson 2019), and so there may be less discussion of COVID-19 in Republican-majority counties (Mutz 2018).…”