Mortality Surveillance for the COVID-19 Pandemic: Review of the Centers for Disease Control and Prevention's Multiple System Strategy.

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).

Increased Deaths From Fungal Infections During the Coronavirus Disease 2019 Pandemic-National Vital Statistics System, United States, January 2020-December 2021.

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.

Drug-involved Infant Deaths in the United States, 2015-2017.

This report describes drug-involved infant deaths in the United States for 2015-2017 by type of drug involved and selected maternal and infant characteristics. Deaths are grouped according to whether drugs were the underlying or a contributing cause of death.

Maternal hepatitis C prevalence and trends by county, US: 2016-2020.

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.

Federal Housing Assistance and Chronic Disease Among US Adults, 2005-2018.

Introduction: Housing insecurity is associated with poor health outcomes. Characterization of chronic disease outcomes among adults with and without housing assistance would enable housing programs to better understand their population's health care needs. Methods: We used National Health and Nutrition Examination Survey (NHANES) data from 2005 through 2018 linked to US Department of Housing and Urban Development (HUD) administrative records to estimate the prevalence of obesity, diabetes, and hypertension and to assess the independent associations between housing assistance and chronic conditions among adults receiving HUD assistance and HUD-assistance-eligible adults not receiving HUD assistance at the time of their NHANES examination. We estimated propensity scores to adjust for potential confounders among linkage-eligible adults who had an income-to-poverty ratio less than 2 and were not receiving HUD assistance. Sensitivity analysis used 2013-2018 NHANES cycles to account for disability status. Results: Adults not receiving HUD assistance had a significantly lower adjusted prevalence of obesity (42.1%; 95% CI, 40.4%-43.8%) compared with adults receiving HUD assistance (47.5%; 95% CI, 44.8%-50.3%), but we found no differences for diabetes and hypertension. We found significant associations between housing assistance and obesity (adjusted odds ratio = 1.29; 95% CI, 1.12-1.47), but these were not significant in the sensitivity analysis with and without controlling for disability status. We found no significant associations between housing assistance and diabetes or hypertension. Conclusion: Based on data from a cross-sectional survey, we observed a higher prevalence of obesity among adults with HUD assistance compared with HUD-assistance-eligible adults without HUD assistance. Results from this study can help inform research on understanding the prevalence of chronic disease among adults with HUD assistance.

Rural-Urban Differences in Maternal Mortality Trends in the United States, 1999-2017: Accounting for the Impact of the Pregnancy Status Checkbox.

It has been difficult to measure rural-urban differences in maternal mortality ratios (MMRs) in the United States in recent years because of the incremental adoption of a pregnancy status checkbox on the standard US death certificate. Using 1999-2017 mortality and birth data, we examined the impact of the pregnancy checkbox on MMRs according to urbanicity of residence (large urban area, medium/small urban area, or rural area), using log-binomial regression models to predict trends that would have been observed if all states had adopted the checkbox as of 1999. Implementation of the checkbox resulted in an average estimated increase of 7.5 maternal deaths per 100,000 live births (95% confidence interval (CI): 6.3, 8.8) in large urban areas (a 76% increase), 11.6 (95% CI: 9.6, 13.6) in medium/small urban areas (a 113% increase), and 16.6 (95% CI: 12.9, 20.3) in rural areas (a 107% increase), compared with MMRs prior to the checkbox. Assuming that all states had the checkbox as of 1999, demographic-factor-adjusted predicted MMRs increased in rural areas, declined in large urban areas, and did not change in medium/small urban areas. However, trends and urban-rural differences were substantially attenuated when analyses were limited to direct/specific causes of maternal death, which are probably subject to less misclassification. Accurate ascertainment of maternal deaths, particularly in rural areas, is important for reducing disparities in maternal mortality.

Advancements in the National Vital Statistics System to Meet the Real-Time Data Needs of a Pandemic.

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133-2140. https://doi.org/10.2105/AJPH.2021.306519).

Disparities in Excess Mortality Associated with COVID-19 - United States, 2020.

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates.

Excess Deaths Associated with COVID-19, by Age and Race and Ethnicity - United States, January 26-October 3, 2020.

As of October 15, 216,025 deaths from coronavirus disease 2019 (COVID-19) have been reported in the United States*; however, this number might underestimate the total impact of the pandemic on mortality. Measures of excess deaths have been used to estimate the impact of public health pandemics or disasters, particularly when there are questions about underascertainment of deaths directly attributable to a given event or cause (1-6).† Excess deaths are defined as the number of persons who have died from all causes, in excess of the expected number of deaths for a given place and time. This report describes trends and demographic patterns in excess deaths during January 26-October 3, 2020. Expected numbers of deaths were estimated using overdispersed Poisson regression models with spline terms to account for seasonal patterns, using provisional mortality data from CDC's National Vital Statistics System (NVSS) (7). Weekly numbers of deaths by age group and race/ethnicity were assessed to examine the difference between the weekly number of deaths occurring in 2020 and the average number occurring in the same week during 2015-2019 and the percentage change in 2020. Overall, an estimated 299,028 excess deaths have occurred in the United States from late January through October 3, 2020, with two thirds of these attributed to COVID-19. The largest percentage increases were seen among adults aged 25-44 years and among Hispanic or Latino (Hispanic) persons. These results provide information about the degree to which COVID-19 deaths might be underascertained and inform efforts to prevent mortality directly or indirectly associated with the COVID-19 pandemic, such as efforts to minimize disruptions to health care.

Race, Ethnicity, and Age Trends in Persons Who Died from COVID-19 - United States, May-August 2020.

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System† (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.

Beyond birth outcomes: Interpregnancy interval and injury-related infant mortality.

BACKGROUND: Several studies have examined the association between IPI and birth outcomes, but few have explored the association between interpregnancy interval (IPI) and postnatal outcomes. OBJECTIVE: We examined the association between IPI and injury-related infant mortality, a leading cause of postneonatal mortality. METHODS: We used 2011-2015 US period-linked birth-infant death vital statistics data to generate a multiyear birth cohort of non-first-born singleton births (N = 9 782 029). IPI was defined as the number of months between a live birth and the start of the pregnancy leading to the next live birth. Causes of death in the first year of life were identified using ICD-10 codes. Hazard ratios (HR) for IPI categories were estimated using Cox proportional hazards models adjusted for birth order, county poverty level, and maternal characteristics (marital status, race/ethnicity, education, age at previous birth). RESULTS: After adjustment, overall infant mortality (48.1 per 10 000 births) was higher for short and long IPIs compared with IPI 18-23 months (reference): <6, aHR 1.61, 95% CI 1.54, 1.68; 6-11, aHR 1.22, 95% CI 1.17, 1.26; and 60+ months, aHR 1.12, 95% CI 1.08, 1.16. In comparison, the risk of injury-related infant mortality (4.4 per 10 000 births) decreased with longer IPIs: <6, aHR 1.77, 95% CI 1.55, 2.01; 6-11, aHR 1.41, 95% CI 1.25, 1.59; 12-17, aHR 1.25, 95% CI 1.10, 1.41; 24-59, aHR 0.78, 95% CI 0.69, 0.87; and 60+ months, aHR 0.55, 95% CI 0.48, 0.62. CONCLUSION: Unlike overall infant mortality, injury-related infant mortality decreased with IPI length. While injury-related deaths are rare, these patterns suggest that the timing between births may be a marker of risk for fatal infant injuries. The first year postpartum may be an ideal time for the delivery of evidence-based injury prevention programmes as well as family planning services.

Report of the Office of Population Affairs' expert work group meeting on short birth spacing and adverse pregnancy outcomes: Methodological quality of existing studies and future directions for research.

BACKGROUND: The World Health Organization (WHO) recommends that women wait at least 24 months after a livebirth before attempting a subsequent pregnancy to reduce the risk of adverse maternal, perinatal, and infant health outcomes. However, the applicability of the WHO recommendations for women in the United States is unclear, as breast feeding, nutrition, maternal age at first birth, and total fertility rate differs substantially between the United States and the low- and middle-resource countries upon which most of the evidence is based. METHODS: To inform guideline development for birth spacing specific to women in the United States, the Office of Population Affairs (OPA) convened an expert work group meeting in Washington, DC, on 14-15 September 2017 among reproductive, perinatal, paediatric, social, and public health epidemiologists; obstetrician-gynaecologists; biostatisticians; and experts in evidence synthesis related to women's health. RESULTS: Presentations and discussion topics included the methodological quality of existing studies, evaluation of the evidence for causal effects of short interpregnancy intervals on adverse perinatal and maternal health outcomes, good practices for future research, and identification of research gaps and priorities for future work. CONCLUSIONS: This report provides an overview of the presentations, discussions, and conclusions from the expert work group meeting.

Good practices for the design, analysis, and interpretation of observational studies on birth spacing and perinatal health outcomes.

BACKGROUND: Meta-analyses of observational studies have shown that women with a shorter interpregnancy interval (the time from delivery to start of a subsequent pregnancy) are more likely to experience adverse pregnancy outcomes, such as preterm delivery or small for gestational age birth, than women who space their births further apart. However, the studies used to inform these estimates have methodological shortcomings. METHODS: In this commentary, we summarise the discussions of an expert workgroup describing good practices for the design, analysis, and interpretation of observational studies of interpregnancy interval and adverse perinatal health outcomes. RESULTS: We argue that inferences drawn from research in this field will be improved by careful attention to elements such as: (a) refining the research question to clarify whether the goal is to estimate a causal effect vs describe patterns of association; (b) using directed acyclic graphs to represent potential causal networks and guide the analytic plan of studies seeking to estimate causal effects; (c) assessing how miscarriages and pregnancy terminations may have influenced interpregnancy interval classifications; (d) specifying how key factors such as previous pregnancy loss, pregnancy intention, and maternal socio-economic position will be considered; and (e) examining if the association between interpregnancy interval and perinatal outcome differs by factors such as maternal age. CONCLUSION: This commentary outlines the discussions of this recent expert workgroup, and describes several suggested principles for study design and analysis that could mitigate many potential sources of bias.

Estimating Usual Dietary In take From National Health and Nut rition Examination Survey Data Using the National Cancer Institute Method.

Dietary recommendations are intended to be met based on dietary intake over long periods, as associations between diet and health result from habitual intake, not a single eating occasion or day of intake. Measuring usual intake directly is impractical for large population-based surveys due to the respondent burden associated with reporting habitual intake over longer periods. Therefore, analytical techniques were developed to estimate usual intake using as few as 2 days of 24-hour dietary recall data. With National Health and Nutrition Examination Survey (NHANES) data, this report demonstrates how to estimate usual intake using the National Cancer Institute (NCI). This report demonstrates how to estimate the usual intake of nutrients consumed daily or episodically using NHANES data. Means, percentiles, and the percentages above or below specified Dietary Reference Intake (DRI) values for given day, within-person mean (WPM), and estimates of usual intake are presented. Consistent with previous analyses, mean intakes were similar across methods. However, the distributions estimated by nonusual intake methods were wider compared with the NCI Method, which can lead to misclassification of the percentage of the population above or below certain DRIs. Use of NHANES data to examine the proportion of the population at risk of insufficiency or excess of certain nutrients, with methods like given day and WPM that do not address within-person variation, may lead to biased estimates.

Trends in Risk of Pregnancy Loss Among US Women, 1990-2011.

BACKGROUND: Pregnancy loss can have physical and psychological consequences for women and their families. Though a previous study described an increase in the risk of self-reported pregnancy loss from 1970 to 2000, more recent examinations from population-based data of US women are lacking. METHODS: We used data from the 1995, 2002, 2006-2010, 2011-2015 National Survey of Family Growth on self-reported pregnancy loss (miscarriage, stillbirth, ectopic pregnancy) among US women (15-44 years) who reported at least one pregnancy conceived during 1990-2011 that did not result in induced termination (n = 20 012 women; n = 42 526 pregnancies). Trends in the risk of self-reported pregnancy loss and early pregnancy loss (<12 weeks) were estimated, separately, by year of pregnancy conception (limited to 1990-2011 to ensure a sufficient sample of pregnancies for each year and maternal age group) using log-Binomial and Poisson models, adjusted for maternal- and pregnancy-related factors. RESULTS: Among all self-reported pregnancies, excluding induced terminations, the risk of pregnancy loss was 19.7% and early pregnancy loss was 13.5% during 1990-2011. Risk of pregnancy loss increased by a relative 2% (rate ratio [RR] 1.02, 95% confidence interval [CI] 1.01, 1.02) per year in unadjusted models and 1% per year (RR 1.01, 95% CI 1.00, 1.02) during 1990-2011, after adjustment for maternal characteristics and pregnancy-related factors. In general, trends were similar for early pregnancy loss. CONCLUSION: From 1990 to 2011, risk of self-reported pregnancy loss increased among US women. Further work is needed to better understand the drivers of this increase in reported pregnancy loss in the US.

Plurality of Birth and Infant Mortality Due to External Causes in the United States, 2000-2010.

Risk of death during the first year of life due to external causes, such as unintentional injury and homicide, may be higher among twins and higher-order multiples than among singletons in the United States. We used national birth cohort linked birth-infant death data (2000-2010) to evaluate the risk of infant mortality due to external causes in multiples versus singletons in the United States. Risk of death from external causes during the study period was 3.6 per 10,000 live births in singletons and 5.1 per 10,000 live births in multiples. Using log-binomial regression, the corresponding unadjusted risk ratio was 1.40 (95% confidence interval (CI): 1.30, 1.50). After adjustment for maternal age, marital status, race/ethnicity, and education, the risk ratio was 1.68 (95% CI: 1.56, 1.81). Infant deaths due to external causes were most likely to occur between 2 and 7 months of age. Applying inverse probability weighting and assuming a hypothetical intervention where no infants were low birth weight, the adjusted controlled direct effect of plurality on infant mortality due to external causes was 1.64 (95% CI: 1.39, 1.97). Twins and higher-order multiples were at greater risk of infant mortality due to external causes, particularly between 2 and 7 months of age, and this risk appeared to be mediated largely by factors other than low-birth-weight status.

Housing Assistance Programs and Adult Health in the United States.

OBJECTIVES: To examine whether access to housing assistance is associated with better health among low-income adults. METHODS: We used National Health Interview Survey data (1999-2012) linked to US Department of Housing and Urban Development (HUD) administrative records (1999-2014) to examine differences in reported fair or poor health and psychological distress. We used multivariable models to compare those currently receiving HUD housing assistance (public housing, housing choice vouchers, and multifamily housing) with those who will receive housing assistance within 2 years (the average duration of HUD waitlists) to account for selection into HUD assistance. RESULTS: We found reduced odds of fair or poor health for current public housing (odds ratio [OR] = 0.77; 95% confidence interval [CI] = 0.57, 0.97) and multifamily housing (OR = 0.75; 95% CI = 0.60, 0.95) residents compared with future residents. Public housing residents also had reduced odds of psychological distress (OR = 0.59; 95% CI = 0.40, 0.86). These differences were not mediated by neighborhood-level characteristics, and we did not find any health benefits for current housing choice voucher recipients. CONCLUSIONS: Housing assistance is associated with improved health and psychological well-being for individuals entering public housing and multifamily housing programs.

Income Inequality and US Children's Secondhand Smoke Exposure: Distinct Associations by Race-Ethnicity.

INTRODUCTION: Prior 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. METHODS: We 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). RESULT: Non-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. CONCLUSIONS: We 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. IMPLICATIONS: In 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.

Mapping Geographic Variation in Infant Mortality and Related Black-White Disparities in the US.

BACKGROUND: In the US, black infants remain more than twice as likely as white infants to die in the first year of life. Previous studies of geographic variation in infant mortality disparities have been limited to large metropolitan areas where stable estimates of infant mortality rates by race can be determined, leaving much of the US unexplored. METHODS: The objective of this analysis was to describe geographic variation in county-level racial disparities in infant mortality rates across the 48 contiguous US states and District of Columbia using national linked birth and infant death period files (2004-2011). We implemented Bayesian shared component models in OpenBUGS, borrowing strength across both spatial units and racial groups. We mapped posterior estimates of mortality rates for black and white infants as well as relative and absolute disparities. RESULTS: Black infants had higher infant mortality rates than white infants in all counties, but there was geographic variation in the magnitude of both relative and absolute disparities. The mean difference between black and white rates was 5.9 per 1,000 (median: 5.8, interquartile range: 5.2 to 6.6 per 1,000), while those for black infants were 2.2 times higher than for white infants (median: 2.1, interquartile range: 1.9-2.3). One quarter of the county-level variation in rates for black infants was shared with white infants. CONCLUSIONS: Examining county-level variation in infant mortality rates among black and white infants and related racial disparities may inform efforts to redress inequities and reduce the burden of infant mortality in the US.