Vaccination and Voting Patterns in the U.S.: Analysis of COVID-19 and Flu Surveys From 2010 to 2022.

INTRODUCTION: The study assessed the relationship between COVID-19 and influenza (flu) vaccination and voting patterns during the pandemic and the time trends between flu vaccination and voting patterns. METHODS: Flu and COVID-19 vaccination coverage were analyzed using National Immunization Surveys for flu (Years 2010-2022) and COVID-19 (National Immunization Surveys Adult COVID-19 Module 2021-2022), Centers for Disease Control and Prevention surveillance of COVID-19 vaccination coverage (2021-2022) and U.S. COVID-19 Trends and Impact Survey (2021-2022). The study described the correlations between state-level COVID-19 and flu vaccination coverage, examined individual-level characteristics of vaccination for COVID-19 and for flu using logistic regression (COVID-19 Trends and Impact Survey May-June 2022), and analyzed flu vaccination coverage by age (National Immunization Surveys for flu 2010-2022) and its relationship with voting patterns. RESULTS: There was a strong correlation between state-level COVID-19 vaccination coverage and voting share for the Democratic candidate in the 2020 presidential elections. COVID-19 vaccination coverage in June 2022 was higher than flu vaccination coverage, and it had a stronger correlation with voting patterns (R=0.90 vs R=0.60 in COVID-19 Trends and Impact Survey). Vaccinated people were more likely to be living in a county where the majority voted for the Democratic candidate in 2020 elections both for COVID-19 (adjusted OR=1.77, 95% CI=1.71, 1.84) and for flu (adjusted OR=1.27, 95% CI=1.23, 1.31). There is a longstanding correlation between voting patterns and flu vaccination coverage, which varies by age, with the strongest correlation in the youngest ages. CONCLUSIONS: There are existing prepandemic patterns between vaccination coverage and voting patterns. The findings align with research that has identified an association between adverse health outcomes and the political environment in the U.S.

The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination.

The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems.

Assessing the Potential Impact of Disruptions Due to COVID-19 on HIV Among Key and Lower-Risk Populations in the Largest Cities of Cameroon and Benin.

BACKGROUND: The COVID-19 pandemic indirectly impacts HIV epidemiology in Central/West Africa. We estimated the potential impact of COVID-19-related disruptions to HIV prevention/treatment services and sexual partnerships on HIV incidence and HIV-related deaths among key populations including female sex workers (FSW), their clients, men who have sex with men, and overall. SETTING: Yaoundé (Cameroon) and Cotonou (Benin). METHODS: We used mathematical models of HIV calibrated to city population-specific and risk population-specific demographic/behavioral/epidemic data. We estimated the relative change in 1-year HIV incidence and HIV-related deaths for various disruption scenarios of HIV prevention/treatment services and decreased casual/commercial partnerships, compared with a scenario without COVID-19. RESULTS: A 50% reduction in condom use in all partnerships over 6 months would increase 1-year HIV incidence by 39%, 42%, 31%, and 23% among men who have sex with men, FSW, clients, and overall in Yaoundé, respectively, and 69%, 49%, and 23% among FSW, clients, and overall, respectively, in Cotonou. Combining a 6-month interruption of ART initiation and 50% reduction in HIV prevention/treatment use would increase HIV incidence by 50% and HIV-related deaths by 20%. This increase in HIV infections would be halved by a simultaneous 50% reduction in casual and commercial partnerships. CONCLUSIONS: Reductions in condom use after COVID-19 would increase infections among key populations disproportionately, particularly FSW in Cotonou, who need uninterrupted condom provision. Disruptions in HIV prevention/treatment services have the biggest impacts on HIV infections and deaths overall, only partially mitigated by equal reductions in casual/commercial sexual partnerships. Maintaining ART provision must be prioritized to minimize short-term excess HIV-related deaths.