Gender Discrepancies in SARS-CoV-2 Pandemic Related Beliefs, Attitudes, and Practices.

Objectives: International studies suggest that males may be less likely to adhere to SARS-CoV-2 transmission mitigation efforts than females. However, there is a paucity of research in this field in the United States. The primary aim of this study was to explore the relationship of binary gender identity (female/male) with beliefs, attitudes, and pandemic-related practices in the early stages of the pandemic. Methods: This study is based on a cross-sectional, voluntary response survey. Patients who were tested for SARS-CoV-2 between March 5 and June 7, 2020 were invited to participate. All patients were tested within a large community healthcare system that serves patients through eight hospitals and hundreds of clinics across Washington State. Bivariate associations between gender and various demographics were tested using Chi-squared and Student's t-tests. We examined associations between gender and pandemic-related beliefs, attitudes, and practices using multivariable logistic regression, accounting for potential confounding factors. Results: Females were more likely than males to agree that they (aOR = 1.51, 95% CI 1.14-2.00) or their families (aOR = 1.75, 95% CI 1.31-2.33) were threatened by SARS-CoV-2, or that their own behavior could impact transmission (aOR = 2.17, 95% CI 1.49-3.15). Similarly, females were more likely to agree that social distancing (aOR = 1.72, 95% CI 1.19-2.46), handwashing (aOR = 3.27, 95% CI 2.06-5.21), and masking (aOR = 1.41, 95% CI 1.02-1.94) were necessary to slow SARS-CoV-2 spread. Females were significantly less likely to visit outside of their social distancing circle (aOR = 0.62, 95% CI 0.47-0.81), but among those who did, practices of social distancing (aOR = 1.41, 95% CI 0.89-2.23), remaining outdoors (aOR = 0.89, 95% CI 0.56-1.40), and masking (aOR = 1.19, 95% CI 0.74-1.93) were comparable to males, while females practiced handwashing more than males (aOR = 2.11, 95% CI 1.33-3.34). Conclusions: Our study suggests that gender disparate beliefs, attitudes, and practices existed in the early stages of the SARS-CoV-2 pandemic. Efforts should be tailored to encourage males to engage with mitigation efforts in ongoing pandemic-related public health campaigns.

Empiric evidence of ethnic disparities in coronavirus positivity in Washington State.

OBJECTIVES: Early reports from the initial months of the coronavirus pandemic reveal ethnic disparities in coronavirus incidence, severity, and mortality. This study aimed to evaluate the relationship between ethnicity and outcomes of coronavirus positivity and hospitalization. DESIGN: An observational cohort study using electronic health record (EHR) data from a large community healthcare system in Washington State across the first phase of the pandemic (March 5 - June 7, 2020). RESULTS: A total of 18,667 patients (65.9% of all tested) with EHR-documented ethnicity were included. Overall, 6.4% of patients tested positive for coronavirus. Among Latinx patients, 18.6% of those tested were positive, compared to only 4.0% of tested White patients. Multivariable logistic regression revealed significantly higher odds of positivity for Latinxs (aOR = 4.96, 95% CI 4.19-5.87), Asians (aOR = 2.33, 95% CI 1.74-3.08), Blacks (aOR = 1.82, 95% CI 1.43-2.31), and members of other ethnic minority groups (aOR = 2.34, 95% CI 1.80-2.95), compared to Whites in models adjusting for relevant confounders. Latinxs had a higher percentage of self-pay insurance (22.2%) compared to other ethnic groups (7.9-15.8%) and, among those who tested positive, were the only ethnic subpopulation with significantly higher odds than Whites to be hospitalized for COVID-19 (aOR = 2.19, 95% CI 1.45-3.33). We observed a positive correlation between infection and the percentage of Latinxs (r = 0.61, 95% CI 0.45-0.74), Blacks (r = 0.51, 95% CI 0.32-0.66), or Asians (r = 0.64, 95% CI 0.49-0.76) in a given zip-code. This correlationwas negative for Whites (r = -0.63, 95% CI -0.75, -0.45). CONCLUSIONS: We present empirical evidence of higher rates of coronavirus positivity among People of Color compared to White people in Washington State. Social determinants of health, such as occupation, housing, healthcare access, and community structure, may contribute to health disparities in the coronavirus pandemic. Targeted capture of these variables in electronic health records is warranted to inform health equity analyses.