The novelty of COVID-19 has created unique challenges to successful public health efforts because it has required the public to quickly learn and formulate knowledge and attitudes about the virus as information becomes available. The need to stay apprised of new information has also created a critical role for mass media and public institutions in shaping the public's knowledge of, attitudes about, and responses to the unfolding pandemic. In this study, we examine how media consumption and reliance on specific institutions for information shapes three critical outcomes associated with public health epidemics: the accumulation of knowledge and the endorsement of misinformation about COVID-19, and prejudicial responses to the virus. We surveyed 1,141 adults residing across the United States in March 2020. Using multivariate regression and t-tests, we found that participants had greater knowledge, were less likely to endorse misinformation, and reported less bias toward Asian Americans when they had higher trust in the CDC and lower trust in President Trump. Reliance on certain news formats and sources was also associated with knowledge, misinformation, and prejudice. Our findings suggest that trust and news consumption can pose critical barriers to health literacy and foster negative prejudicial responses that further undermine public health efforts surrounding the COVID-19 pandemic.

Objectives This paper empirically examines whether and how COVID-19 may be activating bias and discrimination toward individuals of Asian descent. Methods In March 2020, we used a national online survey to collect data from 1141 US residents. Using descriptive statistics and multivariate regression, we estimated the prevalence and COVID-19-related predictors of bias toward people of Asian descent. Results We found over 40% of our sample reported they would engage in at least one discriminatory behavior toward people of Asian descent. Respondents who were fearful of COVID-19 ( b = .09, p < 0.001) and had less accurate knowledge about the virus ( b = − .07, p < 0.001) reported more negative attitudes toward Asians as did respondents with less trust in science ( b = − .06, p < 0.001) and more trust in President Trump ( b = .04, p < 0.001). Conclusions Public health leaders must confront fear of the virus, improve knowledge, and bolster trust in science as these factors may evoke negative attitudes toward Asians and increase prejudice and discrimination. Specifically, our findings warrant the adoption of public health campaigns that provide health information and build trust in scientific knowledge.

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Context: Virtually all nonprofit hospitals are in compliance with the Affordable Care Act's new Community Health Needs Assessments requirements. Objective: To assess what needs have emerged in the Community Health Needs Assessments hospitals complete nationally, the degree to which identified needs reflect the most pressing community health issues, and the extent to which hospitals address identified needs. Design: Using both bivariate and logistic regressions, we analyzed the Community Health Needs Assessments and implementation strategies of nonprofit hospitals to determine whether identified needs overlapped with county health-ranking indicators of need and whether institutional or community-level factors predicted hospital willingness to address identified needs. Participants: We included a 20% random sample of US nonprofit hospitals (n = 496). Main Outcome Measures: Our main outcome measures were whether nonprofit hospitals addressed each of the most common needs. Results: Mental health, access to care, obesity, substance abuse, diabetes, cancer, and the social determinants of health were the most commonly identified needs across the sample. The rate at which hospitals chose to address each of these needs in their implementation strategies, however, varied considerably, ranging from 56% (cancer) to 85% (obesity). We found that several institutional and community characteristics predicted hospital willingness to address each need; whether the community ranked a need as number 1 was a better predictor of hospital investment than the severity of the need, as measured by county health-rankings data. Conclusions: These findings may help inform local, state, and federal policy makers as they consider interventions aimed at encouraging hospitals to invest in improving the health of their communities.

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