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      Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic

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          Abstract

          Objective

          To study the U.S. public’s health behaviors, attitudes, and policy opinions about COVID-19 in the earliest weeks of the national health crisis (March 20–23, 2020).

          Method

          We designed and fielded an original representative survey of 3,000 American adults between March 20–23, 2020 to collect data on a battery of 38 health-related behaviors, government policy preferences on COVID-19 response and worries about the pandemic. We test for partisan differences COVID-19 related policy attitudes and behaviors, measured in three different ways: party affiliation, intended 2020 Presidential vote, and self-placed ideological positioning. Our multivariate approach adjusts for a wide range of individual demographic and geographic characteristics that might confound the relationship between partisanship and health behaviors, attitudes, and preferences.

          Results

          We find that partisanship—measured as party identification, support for President Trump, or left-right ideological positioning—explains differences in Americans across a wide range of health behaviors and policy preferences. We find no consistent evidence that controlling for individual news consumption, the local policy environment, and local pandemic-related deaths erases the observed partisan differences in health behaviors, beliefs, and attitudes. In further analyses, we use a LASSO regression approach to select predictors, and find that a partisanship indicator is the most commonly selected predictor across the 38 dependent variables that we study.

          Conclusion

          Our analysis of individual self-reported behavior, attitudes, and policy preferences in response to COVID-19 reveals that partisanship played a central role in shaping individual responses in the earliest months of the COVID-19 pandemic. These results indicate that partisan differences in responding to a national public health emergency were entrenched from the earliest days of the pandemic.

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          Most cited references45

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          Regression Shrinkage and Selection Via the Lasso

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            Fear and Loathing across Party Lines: New Evidence on Group Polarization

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              Mitigation strategies for pandemic influenza in the United States.

              Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                7 April 2021
                2021
                7 April 2021
                : 16
                : 4
                : e0249596
                Affiliations
                [1 ] Department of Political Science, Syracuse University, Syracuse, NY, United States of America
                [2 ] Department of Political Science, University of California, Irvine, CA, United States of America
                [3 ] Department of Government, Cornell University, Ithaca, NY, United States of America
                Vanderbilt University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-0211-985X
                https://orcid.org/0000-0002-4000-217X
                Article
                PONE-D-20-38771
                10.1371/journal.pone.0249596
                8026027
                33826646
                22900300-c51e-4254-9196-fe45d02bdc55
                © 2021 Gadarian et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 December 2020
                : 19 March 2021
                Page count
                Figures: 2, Tables: 3, Pages: 13
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: 2026737
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: 2026737
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: 2026737
                Award Recipient :
                Funded by: Cornell Center for the Social Sciences
                Award Recipient :
                SKG, SWG, TBP: National Science Foundation (Award # 2026737), https://nsf.gov TBP: the Cornell Center for the Social Sciences (No grant number), https://socialsciences.cornell.edu The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Medicine and Health Sciences
                Public and Occupational Health
                Behavioral and Social Aspects of Health
                Medicine and Health Sciences
                Epidemiology
                Pandemics
                Biology and Life Sciences
                Psychology
                Psychological Attitudes
                Social Sciences
                Psychology
                Psychological Attitudes
                Medicine and Health Sciences
                Public and Occupational Health
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Infectious Disease Control
                Social Distancing
                Social Sciences
                Political Science
                Governments
                Custom metadata
                Data and full replication materials to recreate all analyses in this manuscript are available in the Open Science Framework database ( osf.io/qu492/).
                COVID-19

                Uncategorized
                Uncategorized

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