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Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response—line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System—to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. 2024;114(10):1071–1080. https://doi.org/10.2105/AJPH.2024.307743) [ABSTRACT FROM AUTHOR]

IntroductionPrior studies have found considerable racial and ethnic disparities in secondhand smoke (SHS) exposure. Although a number of individual-level determinants of this disparity have been identified, contextual determinants of racial and ethnic disparities in SHS exposure remain unexamined. The objective of this study was to examine disparities in serum cotinine in relation to area-level income inequality among 14 649 children from the National Health and Nutrition Examination Survey.MethodsWe fit log-normal regression models to examine disparities in serum cotinine in relation to Metropolitan Statistical Areas level income inequality among 14 649 nonsmoking children aged 3-15 from the National Health and Nutrition Examination Survey (1999-2012).ResultNon-Hispanic black children had significantly lower serum cotinine than non-Hispanic white children (-0.26; 95% CI: -0.38, -0.15) in low income inequality areas, but this difference was attenuated in areas with high income inequality (0.01; 95% CI: -0.16, 0.18). Serum cotinine declined for non-Hispanic white and Mexican American children with increasing income inequality. Serum cotinine did not change as a function of the level of income inequality among non-Hispanic black children.ConclusionsWe have found evidence of differential associations between SHS exposure and income inequality by race and ethnicity. Further examination of environments which engender SHS exposure among children across various racial/ethnic subgroups can foster a better understanding of how area-level income inequality relates to health outcomes such as levels of SHS exposure and how those associations differ by race/ethnicity.ImplicationsIn the United States, the association between children's risk of SHS exposure and income inequality is modified by race/ethnicity in a manner that is inconsistent with theories of income inequality. In overall analysis this association appears to be as predicted by theory. However, race-specific analyses reveal that higher levels of income inequality are associated with lower levels of SHS exposure among white children, while levels of SHS exposure among non-Hispanic black children are largely invariant to area-level income inequality. Future examination of the link between income inequality and smoking-related health outcomes should consider differential associations across racial and ethnic subpopulations.

Purpose: To estimate percent excess deaths during the COVID‐19 pandemic by rural‐urban residence in the United States and to describe rural‐urban disparities by age, sex, and race/ethnicity. Methods: Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6‐month time periods. Findings: There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non‐Hispanic Black persons (28% [27.5, 27.9]) and non‐Hispanic White persons (12% [11.6, 11.8]). The 6‐month time periods with the highest percent excess deaths for large central metro areas were March 2020‐August 2020 and September 2020‐February 2021; for all other areas, these time periods were September 2020‐February 2021 and September 2021‐February 2022. Conclusion: Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural‐urban patterns appear to differ. [ABSTRACT FROM AUTHOR]

Background: Trends in the prevalence of hepatitis C virus (HCV) infection among women delivering live births may differ in rural vs. urban areas of the United States, but estimation of trends based on observed counts may lead to unstable estimates in rural counties due to small numbers. Objectives: The objective of the study was to use small area estimation methods to provide updated county‐level prevalence estimates and, for the first time, trends in maternal HCV infection among live births by county‐level rurality. Methods: Cross‐sectional natality data from 2016 to 2020 were used to estimate maternal hepatitis C prevalence using hierarchical Bayesian models with spatiotemporal random effects to produce annual county‐level estimates of maternal HCV infection and trends over time. Models included a 6‐level rural–urban county classification, year, maternal characteristics and county‐specific covariates. Data were analysed in 2022. Results: There were 90,764/18,905,314 live births (4.8 per 1000) with HCV infection reported on the birth certificate. Hepatitis C prevalence was higher among rural counties as compared to urban counties. Rural counties had the largest annual increases in maternal hepatitis C prevalence (per 1000 births) from 2016 to 2020 (micropolitan: 0.39; noncore: 0.40), with smaller increases among less densely populated urban counties (medium metro: 0.28; small metro: 0.28) and urban counties (large central metro:0.11; large fringe metro: 0.14). Conclusions: The prevalence of maternal HCV infection was the highest in rural counties, and rural counties saw the greatest average prevalence increase during 2016–2020. County‐level data can help in monitoring rural–urban trends in maternal HCV infection to reduce geographic disparities. [ABSTRACT FROM AUTHOR]

Background Coronavirus disease 2019 (COVID-19)–associated fungal infections cause severe illness, but comprehensive data on disease burden are lacking. We analyzed US National Vital Statistics System (NVSS) data to characterize disease burden, temporal trends, and demographic characteristics of persons dying of fungal infections during the COVID-19 pandemic. Methods Using NVSS's January 2018–December 2021 Multiple Cause of Death Database, we examined numbers and age-adjusted rates (per 100 000 population) of deaths due to fungal infection by fungal pathogen, COVID-19 association, demographic characteristics, and year. Results Numbers and age-adjusted rates of deaths due to fungal infection increased from 2019 (n = 4833; rate, 1.2 [95% confidence interval, 1.2–1.3]) to 2021 (n = 7199; rate, 1.8 [1.8–1.8] per 100 000); of 13 121 such deaths during 2020–2021, 2868 (21.9%) were COVID-19 associated. Compared with non–COVID-19–associated deaths (n = 10 253), COVID-19–associated deaths more frequently involved Candida (n = 776 [27.1%] vs n = 2432 [23.7%], respectively) and Aspergillus (n = 668 [23.3%] vs n = 1486 [14.5%]) and less frequently involved other specific fungal pathogens. Rates of death due to fungal infection were generally highest in nonwhite and non-Asian populations. Death rates from Aspergillus infections were approximately 2 times higher in the Pacific US census division compared with most other divisions. Conclusions Deaths from fungal infection increased during 2020–2021 compared with previous years, primarily driven by COVID-19–associated deaths, particularly those involving Aspergillus and Candida. Our findings may inform efforts to prevent, identify, and treat severe fungal infections in patients with COVID-19, especially in certain racial/ethnic groups and geographic areas. [ABSTRACT FROM AUTHOR]