Ronaldo Iachan

Background/Objectives: This study examined the impact of the COVID-19 pandemic on mental health among U.S. adults during its first year, using monthly surveys from March to November 2020. Methods: The primary outcome was the Patient Health Questionnaire four-item (PHQ-4) measure of anxiety and depressive symptoms. Univarite and bivariate analyses were used to provide foundational understanding of key variables. Parametric and non-parametric correlation analyses were conducted to observe the relationship between COVID-19 impacts or risk factors and the frequency of anxiety/depressive symptoms. A series of regression models were fit to assess the impact of pandemic stressors on PHQ-4 scores. Results: There was a statistically significant increase in mean PHQ-4 scores and the proportion of respondents with moderate to severe symptoms (PHQ-4 = 6+) between March–June and July–November 2020. Factors such as fear of contracting the virus, health concerns, and lifestyle disruptions had statistically significant impacts on mental health outcomes; however, these effects were more modest than estimates reported elsewhere. Financial strain, particularly among lower-income households and those experiencing job loss, showed stronger associations with increased anxiety and depressive symptoms, but the overall impact on population-level mental health was limited due to the small proportion severely affected financially. Using regression models, we found that demographic factors and pandemic stressors collectively explained about 21% of the variance in anxiety and depressive symptoms. Conclusions: This study provides a nuanced understanding of the pandemic’s mental health impact, suggesting that while certain subgroups were more affected, the overall population level increase in anxiety and depression was less pronounced than previously assumed.

Background/Objectives: Understanding attitudes and behaviors related to vaccination is critical for enhancing COVID-19 vaccination acceptance and reducing disparities in vaccination coverage. This study examines disparities in vaccine-related attitudes and COVID-19 vaccine hesitancy in the United States in relation to community-level social vulnerability. Methods: This study analyzed cross-sectional national surveys conducted repeatedly between July 2020 and August 2021 (n = 6716). We assessed the association between county-level social vulnerability and general vaccine-related attitudes, as well as COVID-19 vaccine hesitancy. We developed Poisson models with robust variance estimation. The analysis also included the association of county social vulnerability with parental COVID-19 vaccine hesitancy. Results: Living in counties with high Socioeconomic Status vulnerability was associated with less vaccine support (adjusted Prevalence Ratio (aPR) 1.10; 95% CI 1.05–1.14) and residing in counties with high Household Characteristics vulnerability was associated with higher likelihood of COVID-19 vaccine hesitancy (aPR 1.13; 95% CI 1.07–1.20). In contrast, high vulnerability in the Racial and Ethnic Minority was associated with more positive attitudes toward vaccines (aPR 0.91; 95% CI 0.88–0.94) and lower COVID-19 vaccine hesitancy for both themselves (aPR 0.81; 95% CI 0.76–0.87) and children (aPR 0.84; 95% CI 0.75–0.94), after adjusting for sociodemographic factors. Conclusions: Our study highlights the importance of addressing vulnerabilities related to socioeconomic status and household characteristics to reduce disparities in vaccine perceptions and hesitancy in socially vulnerable populations. The findings provide evidence for targeted public health interventions at the community level. They also demonstrate that the relationship between social vulnerability and vaccine attitudes varies across different vulnerability components.

Despite relatively high rates of population spread, morbidity and mortality, the adoption of COVID-19 vaccines among the eligible populations was relatively slow. Some of the reasons for vaccination hesitancy and refusals have been attributed to unique aspects of this pandemic, including attitudes toward COVID-19 vaccines. However, little attention has been paid to the role of underlying vaccine beliefs in the likelihood of early vaccine adoption for COVID-19. This study provides a more comprehensive assessment of factors influencing willingness to get an early vaccination, and the relative contribution of general vaccine attitudes, compared to demographics, perceived threat and institutional trust. Monthly national surveys were conducted between June and November 2020 using a national consumer panel of U.S. adults (n = 6185). By late November, only 24% of respondents said they were very likely to get a Food and Drug Administration (FDA)-approved COVID-19 vaccine as soon as it became available. While COVID-19 risk perceptions, confidence and trust in key institutions and information sources, and some demographic variables, were predictive of early vaccination intent, general beliefs regarding vaccines played a significant role, even compared to demographics, perceived risk and institutional trust. This lesson from the COVID-19 experience could help inform public health communications in future epidemics.

Published surveys in the United States provide much evidence that COVID-19 vaccination is influenced by disease and vaccine-related risk perceptions. However, there has been little examination of whether individual’s general beliefs about vaccines are also related to COVID-19 vaccination, especially among unvaccinated adults. This study used an August 2021 national survey of 1000 U.S. adults to examine whether general beliefs about vaccines were associated with COVID-19 vaccination status. In addition, it used multivariate analyses to assess the relative contribution of individual vaccine beliefs to current vaccine status independently of COVID-19-specific attitudes and experiences, and demographics. The findings indicated that, collectively, general vaccine beliefs mattered more than demographics, COVID-19-specific risk perceptions, confidence in government, or trust in public health agencies in COVID-19 vaccination status. Overall, the findings affirm the importance of vaccine education and communication efforts that help people understand why vaccines are needed, how vaccine safety is established and monitored, and how vaccines provide protection from infectious diseases. To achieve success among vaccine-hesitant individuals, communication strategies should target vaccine beliefs that most influence vaccination outcomes.

Objectives: The Medical Monitoring Project (MMP) is a public health surveillance system that provides representative estimates of the experiences and behaviors of adults with diagnosed HIV in the United States. In 2015, the sample design and frame of MMP changed from a system that only included HIV patients to one that captures the experiences of persons receiving and not receiving HIV care. We describe methods investigated for calculating survey weights, the approach chosen, and the benefits of using a dynamic surveillance registry as a sampling frame. Methods: MMP samples adults with diagnosed HIV from the National HIV Surveillance System, the HIV case surveillance registry for the United States. In the methodological study presented in this manuscript, we compared methods that account for sample design and nonresponse, including weighting class adjustment vs. propensity weighting and a single-stage nonresponse adjustment vs. sequential adjustments for noncontact and nonresponse. We investigated how best to adjust for non-coverage using surveillance data to post-stratify estimates. Results: After assessing these methods, we chose as our preferred procedure weighting class adjustments and a single-stage nonresponse adjustment. Classes were constructed using variables associated with respondents’ characteristics and important survey outcomes, chief among them laboratory results available from surveillance that served as a proxy for medical care. Conclusions: MMPs weighting procedures reduced sample bias by leveraging auxiliary information on medical care available from the surveillance registry sampling frame. Expanding MMPs population of focus provides important information on characteristics of persons with diagnosed HIV that complement the information provided by the surveillance registry. MMP methods can be applied to other disease registries or population-monitoring systems when more detailed information is needed for a population, with the detailed information obtained efficiently from a representative sample of the population covered by the registry.

Objectives: Internet-panel surveys are emerging as a means to quickly and cost-effectively collect health data, and because of their large memberships, they could be used for community-level surveys. To determine the feasibility of using an internet-panel survey to quickly provide community-level data, we conducted a pilot test of a health survey in 3 US metropolitan areas. Methods: We conducted internet-panel surveys in Cleveland, Ohio; New York, New York; and Seattle, Washington, in 2015. Slightly more than 500 people responded to the survey in each city. We compared weighted unadjusted prevalence estimates from the internet-panel data with estimates from the 2014 Health Information National Trends Survey (HINTS) for the following question in each survey: “Compared to smoking cigarettes, would you say that electronic cigarettes are…much less harmful, less harmful, just as harmful, more harmful, much more harmful, or I’ve never heard of electronic cigarettes.” We used multivariable logistic regression to compare associations of respondents’ demographic and health characteristics with perceived harm from e-cigarettes. Results: The prevalence of the perception that e-cigarettes are less harmful than smoking cigarettes ranged from 35.9% to 39.9% in the internet-panel sites and was 43.0% in HINTS. Most patterns of beliefs and respondent characteristics in the internet-panel data were consistent with patterns in HINTS. We found inconsistent patterns between internet-panel sites and HINTS by race/ethnicity and education. Conclusions: This feasibility study found that internet-panel surveys could quickly produce community-level data for targeted public health interventions and evaluation, but they may be limited in producing estimates among subgroups.

The Behavioral Risk Factor Surveillance System (BRFSS) is a network of health-related telephone surveys--conducted by all 50 states, the District of Columbia, and participating US territories—that receive technical assistance from CDC. Data users often aggregate BRFSS state samples for national estimates without accounting for state-level sampling, a practice that could introduce bias because the weighted distributions of the state samples do not always adhere to national demographic distributions. This article examines six methods of reweighting, which are then compared with key health indicator estimates from the National Health Interview Survey (NHIS) based on 2013 data. Compared to the usual stacking approach, all of the six new methods reduce the variance of weights and design effect at the national level, and some also reduce the estimated bias. This article also provides a comparison of the methods based on the variances induced by unequal weighting as well as the bias reduction induced by raking at the national level, and recommends a preferred method. The new method leads to weighted distributions that more accurately reproduce national demographic characteristics. While the empirical results for key estimates were limited to a few health indicators, they also suggest reduction in potential bias and mean squared error. To the extent that survey outcomes are associated with these demographic characteristics, matching the national distributions will reduce bias in estimates of these outcomes at the national level.