Effectiveness of Community-Engaged Research Strategies in Increasing COVID-19 Vaccinations in Targeted Communities: The Community Engagement Alliance (CEAL) Regional Teams.

Objectives. To explore a key outcome of interest for the Community Engagement Alliance (CEAL) Regional Teams by examining COVID-19 vaccinations over time in US counties where CEAL teams operated and comparing them to demographically similar counties in the same state. Methods. Our evaluation used a nonequivalent control group design. Each county where a CEAL team operated was matched to a unique non-CEAL county in the same state. Components of the Centers for Disease Control and Prevention's Social Vulnerability Index were used as the matching criteria. COVID-19 vaccinations (county-level percentage of residents aged 18 years or older who are fully vaccinated) for CEAL and matched counties were analyzed over time. Results. The mean percentage of vaccinated adults was significantly higher in CEAL counties than in matched non-CEAL counties. Sensitivity analyses confirmed conclusions did not change depending on the CEAL cohort or closeness of matches. Conclusions. Our findings support CEAL team efforts to increase COVID-19 vaccinations in target communities and employ community-engaged research more broadly within public health contexts. (Am J Public Health. 2024;114(S1):S124-S127. https://doi.org/10.2105/AJPH.2023.307517).

Who Gets Sick From COVID-19? Sociodemographic Correlates of Severe Adult Health Outcomes During Alpha- and Delta-Variant Predominant Periods: September 2020-November 2021.

BACKGROUND: Because COVID-19 case data do not capture most SARS-CoV-2 infections, the actual risk of severe disease and death per infection is unknown. Integrating sociodemographic data into analysis can show consequential health disparities. METHODS: Data were merged from September 2020 to November 2021 from 6 national surveillance systems in matched geographic areas and analyzed to estimate numbers of COVID-19-associated cases, emergency department visits, and deaths per 100 000 infections. Relative risks of outcomes per infection were compared by sociodemographic factors in a data set including 1490 counties from 50 states and the District of Columbia, covering 71% of the US population. RESULTS: Per infection with SARS-CoV-2, COVID-19-related morbidity and mortality were higher among non-Hispanic American Indian and Alaska Native persons, non-Hispanic Black persons, and Hispanic or Latino persons vs non-Hispanic White persons; males vs females; older people vs younger; residents in more socially vulnerable counties vs less; those in large central metro areas vs rural; and people in the South vs the Northeast. DISCUSSION: Meaningful disparities in COVID-19 morbidity and mortality per infection were associated with sociodemography and geography. Addressing these disparities could have helped prevent the loss of tens of thousands of lives.

Effects of Aircraft Noise on Sleep: Federal Aviation Administration National Sleep Study Protocol.

Aircraft noise can disrupt sleep and impair recuperation. The last U.S. investigation into the effects of aircraft noise on sleep dates back more than 20 years. Since then, traffic patterns and the noise levels produced by single aircraft have changed substantially. It is therefore important to acquire current data on sleep disturbance relative to varying degrees of aircraft noise exposure in the U.S. that can be used to check and potentially update the existing noise policy. This manuscript describes the design, procedures, and analytical approaches of the FAA's National Sleep Study. Seventy-seven U.S. airports with relevant nighttime air traffic from 39 states are included in the sampling frame. Based on simulation-based power calculations, the field study aims to recruit 400 participants from four noise strata and record an electrocardiogram (ECG), body movement, and sound pressure levels in the bedroom for five consecutive nights. The primary outcome of the study is an exposure-response function between the instantaneous, maximum A-weighted sound pressure levels (dBA) of individual aircraft measured in the bedroom and awakening probability inferred from changes in heart rate and body movement. Self-reported sleep disturbance due to aircraft noise is the secondary outcome that will be associated with long-term average noise exposure metrics such as the Day-Night Average Sound Level (DNL) and the Nighttime Equivalent Sound Level (Lnight). The effect of aircraft noise on several other physiological and self-report outcomes will also be investigated. This study will provide key insights into the effects of aircraft noise on objectively and subjectively assessed sleep disturbance.

Update to the design and methods of the PATH Study, Wave 4 (2016-2017).

The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative study of the US population on tobacco use and its effects on health, with four waves of data collection between 2013 and 2017. Prior work described the methods of the first three waves. In this paper, we describe the methods of Wave 4, during which a replenishment sample was added to the ongoing cohort. We describe the design and estimation methods of the continuing Wave 1 cohort (with four waves of data) and the Wave 4 cohort (the new cohort created at Wave 4). We provide survey quality metrics, including response rates for both cohorts and a panel conditioning analysis, and guidance on understanding the target populations for both cohorts.

Population-Weighted Seroprevalence From Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection, Vaccination, and Hybrid Immunity Among US Blood Donations From January to December 2021.

BACKGROUND: Previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination, independently and combined ("hybrid immunity"), result in partial protection from subsequent infection and strong protection from severe disease. Proportions of the US population who have been infected, vaccinated, or have hybrid immunity remain unclear, posing a challenge for assessing effective pandemic mitigation strategies. METHODS: In this serial cross-sectional study, nationwide blood donor specimens collected during January-December 2021 were tested for anti-spike and anti-nucleocapsid antibodies, and donor COVID-19 vaccination history of ≥1 dose was collected. Monthly seroprevalence induced from SARS-CoV-2 infection, COVID-19 vaccination, or both, were estimated. Estimates were weighted to account for demographic differences from the general population and were compared temporally and by demographic factors. RESULTS: Overall, 1 123 855 blood samples were assayed. From January to December 2021, the weighted percentage of donations with seropositivity changed as follows: seropositivity due to vaccination without previous infection, increase from 3.5% (95% confidence interval, 3.4%-3.7%) to 64.0%, (63.5%-64.5%); seropositivity due to previous infection without vaccination, decrease from 15.6% (15.2%-16.0%) to 11.7% (11.4%-12.0%); and seropositivity due to hybrid immunity, increase from 0.7% (0.6%-0.7%) to 18.9% (18.5%-19.3%). Combined seroprevalence from infection, vaccination, or both increased from 19.8% (19.3%-20.2%) to 94.5% (93.5%-94.0%). Infection- and vaccination-induced antibody responses varied significantly by age, race-ethnicity, and region, but not by sex. CONCLUSIONS: Our results indicate substantial increases in population humoral immunity from SARS-CoV-2 infection, COVID-19 vaccination, and hybrid immunity during 2021. These findings are important to consider in future COVID-19 studies and long-term pandemic mitigation efforts.

Association of Trends in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seroprevalence and State-Issued Nonpharmaceutical Interventions: United States, 1 August 2020 to 30 March 2021.

BACKGROUND: We assess if state-issued nonpharmaceutical interventions (NPIs) are associated with reduced rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection as measured through anti-nucleocapsid (anti-N) seroprevalence, a proxy for cumulative prior infection that distinguishes seropositivity from vaccination. METHODS: Monthly anti-N seroprevalence during 1 August 2020 to 30 March 2021 was estimated using a nationwide blood donor serosurvey. Using multivariable logistic regression models, we measured the association of seropositivity and state-issued, county-specific NPIs for mask mandates, gathering bans, and bar closures. RESULTS: Compared with individuals living in a county with all three NPIs in place, the odds of having anti-N antibodies were 2.2 (95% confidence interval [CI]: 2.0-2.3) times higher for people living in a county that did not have any of the 3 NPIs, 1.6 (95% CI: 1.5-1.7) times higher for people living in a county that only had a mask mandate and gathering ban policy, and 1.4 (95% CI: 1.3-1.5) times higher for people living in a county that had only a mask mandate. CONCLUSIONS: Consistent with studies assessing NPIs relative to COVID-19 incidence and mortality, the presence of NPIs were associated with lower SARS-CoV-2 seroprevalence indicating lower rates of cumulative infections. Multiple NPIs are likely more effective than single NPIs.

Social Vulnerability and Rurality Associated With Higher Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection-Induced Seroprevalence: A Nationwide Blood Donor Study-United States, July 2020-June 2021.

BACKGROUND: Most studies on health disparities during the coronavirus disease 2019 (COVID-19) pandemic focused on reported cases and deaths, which are influenced by testing availability and access to care. This study aimed to examine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody seroprevalence in the United States and its associations with race/ethnicity, rurality, and social vulnerability over time. METHODS: This repeated cross-sectional study used data from blood donations in 50 states and Washington, DC, from July 2020 through June 2021. Donor zip codes were matched to counties and linked with Social Vulnerability Index (SVI) and urban-rural classification. SARS-CoV-2 antibody seroprevalences induced by infection and infection-vaccination combined were estimated. Association of infection-induced seropositivity with demographics, rurality, SVI, and its 4 themes were quantified using multivariate regression models. RESULTS: Weighted seroprevalence differed significantly by race/ethnicity and rurality, and increased with increasing social vulnerability. During the study period, infection-induced seroprevalence increased from 1.6% to 27.2% and 3.7% to 20.0% in rural and urban counties, respectively, while rural counties had lower combined infection- and vaccination-induced seroprevalence (80.0% vs 88.1%) in June 2021. Infection-induced seropositivity was associated with being Hispanic, non-Hispanic Black, and living in rural or more socially vulnerable counties, after adjusting for demographic and geographic covariates. CONCLUSIONS: The findings demonstrated increasing SARS-CoV-2 seroprevalence in the United States across all geographic, demographic, and social sectors. The study illustrated disparities by race-ethnicity, rurality, and social vulnerability. The findings identified areas for targeted vaccination strategies and can inform efforts to reduce inequities and prepare for future outbreaks.

Generating Health Estimates by Zip Code: A Semiparametric Small Area Estimation Approach Using the California Health Interview Survey.

OBJECTIVES: We propose a method to meet challenges in generating health estimates for granular geographic areas in which the survey sample size is extremely small. METHODS: Our generalized linear mixed model predicts health outcomes using both individual-level and neighborhood-level predictors. The model's feature of nonparametric smoothing function on neighborhood-level variables better captures the association between neighborhood environment and the outcome. Using 2011 to 2012 data from the California Health Interview Survey, we demonstrate an empirical application of this method to estimate the fraction of residents without health insurance for Zip Code Tabulation Areas (ZCTAs). RESULTS: Our method generated stable estimates of uninsurance for 1519 of 1765 ZCTAs (86%) in California. For some areas with great socioeconomic diversity across adjacent neighborhoods, such as Los Angeles County, the modeled uninsured estimates revealed much heterogeneity among geographically adjacent ZCTAs. CONCLUSIONS: The proposed method can increase the value of health surveys by providing modeled estimates for health data at a granular geographic level. It can account for variations in health outcomes at the neighborhood level as a result of both socioeconomic characteristics and geographic locations.

Methane Emissions from the Natural Gas Transmission and Storage System in the United States.

The recent growth in production and utilization of natural gas offers potential climate benefits, but those benefits depend on lifecycle emissions of methane, the primary component of natural gas and a potent greenhouse gas. This study estimates methane emissions from the transmission and storage (T&S) sector of the United States natural gas industry using new data collected during 2012, including 2,292 onsite measurements, additional emissions data from 677 facilities and activity data from 922 facilities. The largest emission sources were fugitive emissions from certain compressor-related equipment and "super-emitter" facilities. We estimate total methane emissions from the T&S sector at 1,503 [1,220 to 1,950] Gg/yr (95% confidence interval) compared to the 2012 Environmental Protection Agency's Greenhouse Gas Inventory (GHGI) estimate of 2,071 [1,680 to 2,690] Gg/yr. While the overlap in confidence intervals indicates that the difference is not statistically significant, this is the result of several significant, but offsetting, factors. Factors which reduce the study estimate include a lower estimated facility count, a shift away from engines toward lower-emitting turbine and electric compressor drivers, and reductions in the usage of gas-driven pneumatic devices. Factors that increase the study estimate relative to the GHGI include updated emission rates in certain emission categories and explicit treatment of skewed emissions at both component and facility levels. For T&S stations that are required to report to the EPA's Greenhouse Gas Reporting Program (GHGRP), this study estimates total emissions to be 260% [215% to 330%] of the reportable emissions for these stations, primarily due to the inclusion of emission sources that are not reported under the GHGRP rules, updated emission factors, and super-emitter emissions.

An evaluation of the U.S. Department of Agriculture food security measure with generalized linear mixed models.

Over the last decade, new information has been developed and collected to measure the extent of food insecurity and hunger in the United States. Common measurement of the phenomenon of hunger and food insecurity has become possible through efforts of the U.S. Department of Agriculture (USDA) to develop a set of survey questions that can be used to obtain estimates of the prevalence and severity of food insecurity. We evaluated the measurement of food insecurity and the effect of household variables on measured food insecurity. The effects of demographic and survey-specific variables on the food insecurity/hunger scale were evaluated using a generalized linear model with mixed effects. Data came from the 1995, 1997 and 1999 Food Security Module of the Current Population Survey. The results generally validated the model currently used by the USDA. In addition, our approach made it possible to consider the effect of demographics and several survey design variables on food security among measurably food-insecure households, as well as interactions between these factors and the food security questions. The analysis of the expanded model with the 1995 data found results similar to those reported based on the Rasch model used by the USDA. Even though the sample size was reduced and a number of screening and questionnaire changes were introduced in 1997 and 1999, the results for those years appear mostly unchanged and confirm the robustness of the scale in measuring food insecurity. There is some evidence that interpretation of questions may vary among different demographic groups.