Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths.

In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.

Excess mortality in the United States in the 21st century.

We use three indexes to identify how age-specific mortality rates in the United States compare to those in a composite of five large European countries since 2000. First, we examine the ratio of age-specific death rates in the United States to those in Europe. These show a sharp deterioration in the US position since 2000. Applying European age-specific death rates in 2017 to the US population, we then show that adverse mortality conditions in the United States resulted in 400,700 excess deaths that year. Finally, we show that these excess deaths entailed a loss of 13.0 My of life. In 2017, excess deaths and years of life lost in the United States represent a larger annual loss of life than that associated with the COVID-19 epidemic in 2020.

COVID-19 and excess mortality in the United States: A county-level analysis.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics. METHODS AND FINDINGS: In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics. CONCLUSIONS: In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

The role of obesity in exceptionally slow US mortality improvement.

Recent studies have described a reduction in the rate of improvement in American mortality. The pace of improvement is also slow by international standards. This paper attempts to identify the extent to which rising body mass index (BMI) is responsible for reductions in the rate of mortality improvement in the United States. The data for this study were obtained from subsequent cohorts of the National Health and Nutrition Examination Survey (NHANES III, 1988-1994; NHANES continuous, 1999-2010) and from the NHANES linked mortality files, which include follow-up into death records through December 2011. The role of BMI was estimated using Cox models comparing mortality trends in the presence and absence of adjustment for maximum lifetime BMI (Max BMI). Introducing Max BMI into a Cox model controlling for age and sex raised the annual rate of mortality decline by 0.54% (95% confidence interval 0.45-0.64%). Results were robust to the inclusion of other variables in the model, to differences in how Max BMI was measured, and to how trends were evaluated. The effect of rising Max BMI is large relative to international mortality trends and to alternative mortality futures simulated by the Social Security Administration. The increase in Max BMI over the period 1988-2011 is estimated to have reduced life expectancy at age 40 by 0.9 years in 2011 (95% confidence interval 0.7-1.1 years) and accounted for 186,000 excess deaths that year. Rising levels of BMI have prevented the United States from enjoying the full benefits of factors working to improve mortality.

Ecological factors associated with suicide mortality among non-Hispanic whites.

BACKGROUND: In this paper, we examine the ecological factors associated with death rates from suicide in the United States in 1999 and 2017, a period when suicide mortality increased in the United States. We focus on Non-Hispanic Whites, who experienced the largest increase in suicide mortality. We ask whether variation in suicide mortality among commuting zones can be explained by measures of the social and economic environment and access to lethal means used to kill oneself in one's area of residence. METHODS: We use vital statistics data on deaths and Census Bureau population estimates and define area of residence as one of 704 commuting zones. We estimate separate models for men and women at ages 20-64 and 65 and above. We measure economic environment by percent of the workforce in manufacturing and the unemployment rate and social environment by marital status, educational attainment, and religious participation. We use gun sellers and opioid prescriptions as measures of access to lethal means. RESULTS: We find that the strongest contextual predictors of higher suicide mortality are lower rates of manufacturing employment and higher rates of opiate prescriptions for all age/sex groups, increased gun accessibility for men, and religious participation for older people. CONCLUSIONS: Socioeconomic characteristic and access to lethal means explain much of the variation in suicide mortality rates across commuting zones, but do not account for the pervasive national-level increase in suicide mortality between 1999 and 2017.

Revealing the burden of obesity using weight histories.

Analyses of the relation between obesity and mortality typically evaluate risk with respect to weight recorded at a single point in time. As a consequence, there is generally no distinction made between nonobese individuals who were never obese and nonobese individuals who were formerly obese and lost weight. We introduce additional data on an individual's maximum attained weight and investigate four models that represent different combinations of weight at survey and maximum weight. We use data from the 1988-2010 National Health and Nutrition Examination Survey, linked to death records through 2011, to estimate parameters of these models. We find that the most successful models use data on maximum weight, and the worst-performing model uses only data on weight at survey. We show that the disparity in predictive power between these models is related to exceptionally high mortality among those who have lost weight, with the normal-weight category being particularly susceptible to distortions arising from weight loss. These distortions make overweight and obesity appear less harmful by obscuring the benefits of remaining never obese. Because most previous studies are based on body mass index at survey, it is likely that the effects of excess weight on US mortality have been consistently underestimated.

The contribution of rising adiposity to the increasing prevalence of diabetes in the United States.

OBJECTIVE: We assessed the contribution of increasing adiposity to the rising prevalence of diabetes in the United States over the period 1988-2014. RESEARCH DESIGN AND METHODS: Data from NHANES III (1988-1994) and continuous waves (1999-2014) were pooled for the current study. Diabetes status was assessed using data on Hemoglobin A1c. We estimated a multivariable logistic regression model that predicted the odds of having diabetes as a function of age, sex, racial/ethnic group, educational attainment, and period of observation. At a second stage, we introduced measures of general and abdominal adiposity into the model. Changes in coefficients pertaining to period of observation between the first and second models were interpreted as indicating the extent to which adiposity can account for trends in the prevalence of diabetes. Sensitivity analyses were conducted to investigate how alternative definitions of adiposity and diabetes status would affect results. RESULTS: The predicted prevalence of diabetes rose by 2.59%/yr between 1988 and 2014 after adjusting for changes in population composition. Increasing adiposity explained 72% of the rise in diabetes. Results were consistent for men and women. CONCLUSIONS: Rising levels of adiposity explained the large majority of the rise in diabetes prevalence between 1988 and 2014.

The contribution of a history of heavy smoking to Scotland's mortality disadvantage.

Scotland has a lower life expectancy than any country in Western Europe or North America, and this disadvantage is concentrated above age 50. According to the Human Mortality Database, life expectancy at age 50 has been lower in Scotland than in any other developed country since 1980. Relative to 15 developed countries that we have chosen for comparison, Scotland's life expectancy in 2009 at age 50 was lower by an average of 2.5 years for women and 1.6 years for men. We estimate that Scottish women lost 3.6 years of life expectancy at age 50 as a result of smoking, compared to 1.4 years for the comparison countries. The equivalent figures among men are 3.1 and 2.1 years. These differences are large enough for the history of heavy smoking in Scotland to account both for most of the shortfall in life expectancy for both sexes and for the country's unusually narrow sex differences in life expectancy.

Obesity paradox: conditioning on disease enhances biases in estimating the mortality risks of obesity.

BACKGROUND: Many studies have documented an obesity paradox-a survival advantage of being obese-in populations diagnosed with a medical condition. Whether obesity is causally associated with improved mortality in these conditions is unresolved. METHODS: We develop the logic of collider bias as it pertains to the association between smoking and obesity in a diseased population. Data from the National Health and Nutrition Examination Survey (NHANES) are used to investigate this bias empirically among persons with diabetes and prediabetes (dysglycemia). We also use NHANES to investigate whether reverse causal pathways are more prominent among people with dysglycemia than in the source population. Cox regression analysis is used to examine the extent of the obesity paradox among those with dysglycemia. In the regression analysis, we explore interactions between obesity and smoking, and we implement a variety of data restrictions designed to reduce the extent of reverse causality. RESULTS: We find an obesity paradox among persons with dysglycemia. In this population, the inverse association between obesity and smoking is much stronger than in the source population, and the extent of illness and weight loss is greater. The obesity paradox is absent among never-smokers. Among smokers, the paradox is eliminated through successive efforts to reduce the extent of reverse causality. CONCLUSION: Higher mortality among normal-weight people with dysglycemia is not causal but is rather a product of the closer inverse association between obesity and smoking in this subpopulation.

Modeling obesity histories in cohort analyses of health and mortality.

There is great interest in understanding the role of weight dynamics over the life cycle in predicting the incidence of disease and death. Beginning with a Medline search, we identify, classify, and evaluate the major approaches that have been used to study these dynamics. We identify four types of models: additive models, duration-of-obesity models, additive-weight-change models, and interactive models. We develop a framework that integrates the major approaches and shows that they are often nested in one another, a property that facilitates statistical comparisons. Our criteria for evaluating models are two-fold: the model's interpretability and its ability to account for observed variation in health outcomes. We apply two sets of nested models to data on adults age 50-74 years at baseline in two national probability samples drawn from National Health and Nutrition Examination Survey. One set of models treats obesity as a dichotomous variable and the other treats it as a continuous variable. In three of four applications, a fully interactive model does not add significant explanatory power to the simple additive model. In all four applications, little explanatory power is lost by simplifying the additive model to a duration model in which the coefficients of weight at different ages are set equal to one another. Other versions of a duration-of-obesity model also perform well, underscoring the importance of obesity at early adult ages for mortality at older ages.

Associations between mortality from COVID-19 and other causes: A state-level analysis.

BACKGROUND: During the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states. METHODS: We use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state's population. RESULTS: We estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes. CONCLUSIONS: States with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.

COVID-19 and All-Cause Mortality by Race, Ethnicity, and Age Across Five Periods of the Pandemic in the United States.

Racial/ethnic and age disparities in COVID-19 and all-cause mortality during 2020 are well documented, but less is known about their evolution over time. We examine changes in age-specific mortality across five pandemic periods in the United States from March 2020 to December 2022 among four racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian) for ages 35+. We fit Gompertz models to all-cause and COVID-19 death rates by 5-year age groups and construct age-specific racial/ethnic mortality ratios across an Initial peak (Mar-Aug 2020), Winter peak (Nov 2020-Feb 2021), Delta peak (Aug-Oct 2021), Omicron peak (Nov 2021-Feb 2022), and Endemic period (Mar-Dec 2022). We then compare to all-cause patterns observed in 2019. The steep age gradients in COVID-19 mortality in the Initial and Winter peak shifted during the Delta peak, with substantial increases in mortality at working ages, before gradually returning to an older age pattern in the subsequent periods. We find a disproportionate COVID-19 mortality burden on racial and ethnic minority populations early in the pandemic, which led to an increase in all-cause mortality disparities and a temporary elimination of the Hispanic mortality advantage at certain age groups. Mortality disparities narrowed over time, with racial/ethnic all-cause inequalities during the Endemic period generally returning to pre-pandemic levels. Black and Hispanic populations, however, faced a younger age gradient in all-cause mortality in the Endemic period relative to 2019, with younger Hispanic and Black adults in a slightly disadvantageous position and older Black adults in a slightly advantageous position, relative to before the pandemic.

Differences Between Reported COVID-19 Deaths and Estimated Excess Deaths in Counties Across the United States, March 2020 to February 2022.

Accurate and timely tracking of COVID-19 deaths is essential to a well-functioning public health surveillance system. The extent to which official COVID-19 death tallies have captured the true toll of the pandemic in the United States is unknown. In the current study, we develop a Bayesian hierarchical model to estimate monthly excess mortality in each county over the first two years of the pandemic and compare these estimates to the number of deaths officially attributed to Covid-19 on death certificates. Overall, we estimated that 268,176 excess deaths were not reported as Covid-19 deaths during the first two years of the Covid-19 pandemic, which represented 23.7% of all excess deaths that occurred. Differences between excess deaths and reported COVID-19 deaths were substantial in both the first and second year of the pandemic. Excess deaths were less likely to be reported as COVID-19 deaths in the Mountain division, in the South, and in nonmetro counties. The number of excess deaths exceeded COVID-19 deaths in all Census divisions except for the New England and Middle Atlantic divisions where there were more COVID-19 deaths than excess deaths in large metro areas and medium or small metro areas. Increases in excess deaths not assigned to COVID-19 followed similar patterns over time to increases in reported COVID-19 deaths and typically preceded or occurred concurrently with increases in reported COVID-19 deaths. Estimates from this study can be used to inform targeting of resources to areas in which the true toll of the COVID-19 pandemic has been underestimated.

Monthly excess mortality across counties in the United States during the COVID-19 pandemic, March 2020 to February 2022.

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the COVID-19 pandemic's mortality impact. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating factors, and inform response efforts. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,179,024 excess deaths occurred during the first 2 years of the pandemic (first: 634,830; second: 544,194). Overall, excess mortality decreased in large metropolitan counties but increased in nonmetropolitan counties. Despite the initial concentration of mortality in large metropolitan Northeastern counties, nonmetropolitan Southern counties had the highest cumulative relative excess mortality by July 2021. These results highlight the need for investments in rural health as the pandemic's rural impact grows.

COVID-19 Mortality by Race and Ethnicity in US Metropolitan and Nonmetropolitan Areas, March 2020 to February 2022.

Importance: Prior research has established that Hispanic and non-Hispanic Black residents in the US experienced substantially higher COVID-19 mortality rates in 2020 than non-Hispanic White residents owing to structural racism. In 2021, these disparities decreased. Objective: To assess to what extent national decreases in racial and ethnic disparities in COVID-19 mortality between the initial pandemic wave and subsequent Omicron wave reflect reductions in mortality vs other factors, such as the pandemic's changing geography. Design, Setting, and Participants: This cross-sectional study was conducted using data from the US Centers for Disease Control and Prevention for COVID-19 deaths from March 1, 2020, through February 28, 2022, among adults aged 25 years and older residing in the US. Deaths were examined by race and ethnicity across metropolitan and nonmetropolitan areas, and the national decrease in racial and ethnic disparities between initial and Omicron waves was decomposed. Data were analyzed from June 2021 through March 2023. Exposures: Metropolitan vs nonmetropolitan areas and race and ethnicity. Main Outcomes and Measures: Age-standardized death rates. Results: There were death certificates for 977 018 US adults aged 25 years and older (mean [SD] age, 73.6 [14.6] years; 435 943 female [44.6%]; 156 948 Hispanic [16.1%], 140 513 non-Hispanic Black [14.4%], and 629 578 non-Hispanic White [64.4%]) that included a mention of COVID-19. The proportion of COVID-19 deaths among adults residing in nonmetropolitan areas increased from 5944 of 110 526 deaths (5.4%) during the initial wave to a peak of 40 360 of 172 515 deaths (23.4%) during the Delta wave; the proportion was 45 183 of 210 554 deaths (21.5%) during the Omicron wave. The national disparity in age-standardized COVID-19 death rates per 100 000 person-years for non-Hispanic Black compared with non-Hispanic White adults decreased from 339 to 45 deaths from the initial to Omicron wave, or by 293 deaths. After standardizing for age and racial and ethnic differences by metropolitan vs nonmetropolitan residence, increases in death rates among non-Hispanic White adults explained 120 deaths/100 000 person-years of the decrease (40.7%); 58 deaths/100 000 person-years in the decrease (19.6%) were explained by shifts in mortality to nonmetropolitan areas, where a disproportionate share of non-Hispanic White adults reside. The remaining 116 deaths/100 000 person-years in the decrease (39.6%) were explained by decreases in death rates in non-Hispanic Black adults. Conclusions and Relevance: This study found that most of the national decrease in racial and ethnic disparities in COVID-19 mortality between the initial and Omicron waves was explained by increased mortality among non-Hispanic White adults and changes in the geographic spread of the pandemic. These findings suggest that despite media reports of a decline in disparities, there is a continued need to prioritize racial health equity in the pandemic response.

Forecasting United States mortality using cohort smoking histories.

In this paper, we introduce a recently established relationship between cohort smoking patterns and adult mortality into mortality projections for the United States. In particular, we incorporate a variable representing the intensity of smoking within a cohort into the original Lee-Carter projection model. The introduction of this variable accounts for important anomalies in the recent age/sex pattern of mortality change and enables the use of a common temporal trend of mortality change for the 2 sexes. We project age-specific mortality rates for men and women at ages 50-84 between 2004 and 2034 in the United States. Because of reductions in smoking that have already occurred or can be reliably projected, mortality is projected to decline much faster when smoking is introduced into the model.

The unequal burden of the Covid-19 pandemic: Capturing racial/ethnic disparities in US cause-specific mortality.

Despite a growing body of literature focused on racial/ethnic disparities in Covid-19 mortality, few previous studies have examined the pandemic's impact on 2020 cause-specific mortality by race and ethnicity. This paper documents changes in mortality by underlying cause of death and race/ethnicity between 2019 and 2020. Using age-standardized death rates, we attribute changes for Black, Hispanic, and White populations to various underlying causes of death and show how these racial and ethnic patterns vary by age and sex. We find that although Covid-19 death rates in 2020 were highest in the Hispanic community, Black individuals faced the largest increase in all-cause mortality between 2019 and 2020. Exceptionally large increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population. Within Black and White populations, percentage increases in all-cause mortality were similar for men and women, as well as for ages 25-64 and 65+. Among the Hispanic population, however, percentage increases in mortality were greatest for working-aged men. These findings reveal that the overall impact of the pandemic on racial/ethnic disparities in mortality was much larger than that captured by official Covid-19 death counts alone.

County-level estimates of excess mortality associated with COVID-19 in the United States.

The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.

Monthly excess mortality across counties in the United States during the Covid-19 pandemic, March 2020 to February 2022.

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemic's disproportionate impact on rural areas continues to grow.