Impact of political partisanship on public interest in infection prevention measures in the United States: An infodemiological study
PREVENTIVE MEDICINE REPORTS(2021)
摘要
There has been conflicting public messaging from government and state officials about recommended health behaviours during the COVID-19 pandemic. We examined whether differences in political affiliation influences the public's interest in infection prevention measures in the United States. State-specific data on public search interest in four key infection prevention measures (Quarantine, Social distancing, Hand washing and Masks) were obtained from Google Trends for the period 1 January 2020 to 12 December 2020. Political affiliation was ascertained based on the 2020 U.S. Presidential election results and 2017 Cook Partisan Voting Index. Spearman's rank, partial correlation, and multiple regression analyses were conducted to compare political partisanship with public interest in infection prevention measures and overall case rate per 100 000 population. Statistical analysis was performed in R version 4.0.3. The COVID-19 pandemic has led to significantly increased public interest in infection prevention measures. The greater the support for the Democratic Party, the greater the search interest in all four measures analysed. Political partisanship was most highly correlated with searches relating to Quarantine (rho = 0.79, p < 0.001), followed by Social distancing (rho = 0.71, p < 0.001), Hand washing (rho = 0.69, p < 0.001), and Masks (rho = 0.66, p < 0.001). These findings were robust to using two different partisanship measures, controlling for state-level demographic variables, different pandemic onset dates, and using exact rather than Topic search methods. This partisan divide among the American people has important health implications that must be better addressed. We call for clear, bipartisan support of simple public health advice to combat the continued SARSCoV-2 spread across the USA.
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关键词
Public health,Infection prevention,Political partisanship,Covid-19,Infodemiology,Google Trends
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