Objective. In this research note, we examine the role scientific knowledge and gender plays in citizen responses to governmental social distancing recommendations. Methods. Using two waves of the American Trends Panel Survey and a measure of latent scientific knowledge, we test whether scientific knowledge is associated with comfort in participating in social activities during the COVID-19 pandemic within both the full U.S. population and the two major political parties. Results. In both the general population and within the Democratic Party, we find that women are generally more likely to use their scientific knowledge to inform their level of comfort with social activities during the COVID-19 pandemic. Conclusion. These findings shed light on how knowledge and gender intersect to drive compliance with government recommendations and policies during a public health crisis in a deeply partisan America.

Pundits and academics across disciplines note that the human toll brought forth by the novel coronavirus (COVID-19) pandemic in the United States (U.S.) is fundamentally unequal for communities of color. Standing literature on public health posits that one of the chief predictors of racial disparity in health outcomes is a lack of institutional trust among minority communities. Furthermore, in our own county-level analysis from the U.S., we find that counties with higher percentages of Black and Hispanic residents have had vastly higher cumulative deaths from COVID-19. In light of this standing literature and our own analysis, it is critical to better understand how to mitigate or prevent these unequal outcomes for any future pandemic or public health emergency. Therefore, we assess the claim that raising institutional trust, primarily scientific trust, is key to mitigating these racial inequities. Leveraging a new, pre-pandemic measure of scientific trust, we find that trust in science, unlike trust in politicians or the media, significantly raises support for COVID-19 social distancing policies across racial lines. Our findings suggest that increasing scientific trust is essential to garnering support for public health policies that lessen the severity of the current, and potentially a future, pandemic.

From the onset of the first confirmed case of COVID-19 in January 2020 to Election Day in November, the United States experienced over 9,400,000 cases and 232,000 deaths. This crisis largely defined the campaign between former Vice President Joe Biden and President Donald Trump, centering on the Trump administration′s efforts in mitigating the number of cases and deaths. While conventional wisdom suggested that Trump and his party would lose support due to the severity of COVID-19 across the country, such an effect is hotly debated empirically and theoretically. In this research, we evaluate the extent to which the severity of the COVID-19 pandemic influenced support for President Trump in the 2020 election. Across differing modeling strategies and a variety of data sources, we find evidence that President Trump gained support in counties with higher COVID-19 deaths. We provide an explanation for this finding by showing that voters concerned about the economic impacts of pandemic-related restrictions on activity were more likely to support Trump and that local COVID-19 severity was predictive of these economic concerns. While COVID-19 likely contributed to Trump’s loss in 2020, our analysis demonstrates that he gained support among voters in localities worst affected by the pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s11109-022-09826-x.

Vaccines are the most effective means at combating sickness and death caused by COVID-19. Yet, there are significant populations within the United States who are vaccine-hesitant, some due to ideological or pseudo-scientific motivations, others due to significant perceived and real costs from vaccination. Given this vaccine hesitancy, twenty state governors from May 12th to July 21st 2021 implemented some form of vaccination lottery aiming to increase low vaccination rates. In the aftermath of these programs, however, the critical question of whether these lotteries had a direct effect on vaccination remains. Previous literature on financial incentives for public health behaviors is consistent: Financial incentives significantly increase incentivized behaviors. Yet, work done specifically on state vaccine lotteries is both limited in scope and mixed in its conclusions. To help fill this gap in the literature, we use synthetic control methods to analyze all 20 states and causally identify, for eighteen states, the effects of their lotteries on both first-dose and complete vaccination rates. Within those eighteen states, we find strong evidence that all but three states’ lotteries had positive effects on first-dose vaccination. We find for complete vaccinations, however, over half the states analyzed had negative or null effects. We explore possibilities related to these mixed results including the states’ overall partisanship, vaccine hesitancy, and the size of their lotteries finding null effects for each of these explanations. Therefore, we conclude that the design of these programs is likely to blame: Every state lottery only incentivized first-doses with no additional or contingent incentive based on a second dose. Our findings suggest that the design of financial incentives is critical to their success, or failure, but generally, these programs can induce an uptake in vaccination across diverse demographic, ideological, and geographic contexts in the United States.

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