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.

Download Full-text

Evaluation of County-Level Heterogeneity in Excess Mortality in Colorado from March to September 2020

10.1101/2021.04.10.21255235 ◽

2021 ◽

Author(s):

Jay Chandra ◽

Marie Charpignon ◽

Mathew C Samuel ◽

Anushka Bhaskar ◽

Saketh Sundar ◽

...

Keyword(s):

Public Health ◽

Mortality Rate ◽

Excess Mortality ◽

Ethnic Disparities ◽

The United States ◽

The State ◽

Mortality Data ◽

County Level ◽

All Cause Mortality ◽

Excess Deaths

Importance: Tracking the direct and indirect impact of the coronavirus disease 2019 (COVID-19) pandemic on all-cause mortality in the United States has been hindered by the lack of testing and by reporting delays. Evaluating excess mortality, or the number of deaths above what is expected in a given time period, provides critical insights into the true burden of the COVID-19 pandemic caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Stratifying mortality data by demographics such as age, sex, race, ethnicity, and geography helps quantify how subgroups of the population have been differentially affected. Similarly, stratifying mortality data by cause of death reveals the public health effects of the pandemic in terms of other acute and chronic diseases. Objective: To provide stratified estimates of excess mortality in Colorado from March to September 2020. Design, Setting, and Population: This study evaluated the number of excess deaths both directly due to SARS-CoV-2 infection and from all other causes between March and September 2020 at the county level in Colorado. Data were obtained from the Vital Statistics Program at the Colorado Department of Public Health and Environment. These estimates of excess mortality were derived by comparing population- adjusted mortality rates in 2020 with rates in the same months from 2015 to 2019. Results: We found evidence of excess mortality in Colorado between March and September 2020. Two peaks in excess deaths from all causes were recorded in the state, one mid-April and the other at the end of June. Since the first documented SARS-CoV-2 infection on March 5th, we estimated that the excess mortality rate in Colorado was two times higher than the officially reported COVID-19 mortality rate. State-level cumulative excess mortality from all causes reached 71 excess deaths per 100k residents (~4000 excess deaths in the state); in contrast, 35 deaths per 100k directly due to SARS-CoV-2 were recorded in the same period (~1980 deaths. Excess mortality occurred in 52 of 64 counties, accounting for 99% of the state's population. Most excess deaths recorded from March to September 2020 were associated with acute events (estimated at 44 excess deaths per 100k residents and at 9 after excluding deaths directly due to SARS-CoV-2) rather than with chronic conditions (~21 excess deaths per 100k). Among Coloradans aged 14-44, 1.4 times more deaths occurred in those months than during the same period in the five previous years. Hispanic White males died of COVID-19 at the highest rate during this time (~90 deaths from COVID-19 per 100k residents); however, Non-Hispanic Black/African American males were the most affected in terms of overall excess mortality (~204 excess deaths per 100k). Beyond inequalities in COVID-19 mortality per se, these findings signal considerable regional and racial-ethnic disparities in excess all-cause mortality that need to be addressed for a just recovery and in future public health crises.

Download Full-text

Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study

10.1101/2020.04.05.20054502 ◽

2020 ◽

Cited By ~ 191

Author(s):

Xiao Wu ◽

Rachel C Nethery ◽

M Benjamin Sabath ◽

Danielle Braun ◽

Francesca Dominici

Keyword(s):

United States ◽

Air Pollution ◽

Death Rate ◽

The United States ◽

Sensitivity Analyses ◽

List Type ◽

County Level ◽

Cross Sectional ◽

Increased Risk

AbstractObjectivesUnited States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affected by long-term exposure to air pollution. We investigated whether long-term average exposure to fine particulate matter (PM2.5) is associated with an increased risk of COVID-19 death in the United States.DesignA nationwide, cross-sectional study using county-level data.Data sourcesCOVID-19 death counts were collected for more than 3,000 counties in the United States (representing 98% of the population) up to April 22, 2020 from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center.Main outcome measuresWe fit negative binomial mixed models using county-level COVID-19 deaths as the outcome and county-level long-term average of PM2.5 as the exposure. In the main analysis, we adjusted by 20 potential confounding factors including population size, age distribution, population density, time since the beginning of the outbreak, time since state’s issuance of stay-at-home order, hospital beds, number of individuals tested, weather, and socioeconomic and behavioral variables such as obesity and smoking. We included a random intercept by state to account for potential correlation in counties within the same state. We conducted more than 68 additional sensitivity analyses.ResultsWe found that an increase of only 1 μg/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%). The results were statistically significant and robust to secondary and sensitivity analyses.ConclusionsA small increase in long-term exposure to PM2.5 leads to a large increase in the COVID-19 death rate. Despite the inherent limitations of the ecological study design, our results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis. The data and code are publicly available so our analyses can be updated routinely.Summary BoxWhat is already known on this topicLong-term exposure to PM2.5 is linked to many of the comorbidities that have been associated with poor prognosis and death in COVID-19 patients, including cardiovascular and lung disease.PM2.5 exposure is associated with increased risk of severe outcomes in patients with certain infectious respiratory diseases, including influenza, pneumonia, and SARS.Air pollution exposure is known to cause inflammation and cellular damage, and evidence suggests that it may suppress early immune response to infection.What this study addsThis is the first nationwide study of the relationship between historical exposure to air pollution exposure and COVID-19 death rate, relying on data from more than 3,000 counties in the United States. The results suggest that long-term exposure to PM2.5 is associated with higher COVID-19 mortality rates, after adjustment for a wide range of socioeconomic, demographic, weather, behavioral, epidemic stage, and healthcare-related confounders.This study relies entirely on publicly available data and fully reproducible, public code to facilitate continued investigation of these relationships by the broader scientific community as the COVID-19 outbreak evolves and more data become available.A small increase in long-term PM2.5 exposure was associated with a substantial increase in the county’s COVID-19 mortality rate up to April 22, 2020.

Download Full-text

Correcting excess mortality for pandemic-associated population decreases

10.1101/2021.02.10.21251461 ◽

2021 ◽

Author(s):

Jeremy Samuel Faust ◽

Chengan Du ◽

Shu-Xia Li ◽

Zhenqiu Lin ◽

Harlan M. Krumholz

Keyword(s):

United States ◽

Excess Mortality ◽

Herd Immunity ◽

The United States ◽

Population Changes ◽

Cross Sectional ◽

Point Estimates ◽

Public Health Officials ◽

Sectional Analysis ◽

Measurement Period

AbstractObjectivesWe identify a correction for excess mortality that takes the sudden unexpected changes in the size of the United States population into account.DesignThis is a weekly cross-sectional analysis of all-cause mortality since week 5, 2020. We describe and apply a simple correction that takes population changes into account in order to provide corrected weekly estimates of expected deaths for 2020 and 2021.SettingThe United States.ParticipantsAll United States residents.InterventionsThe covid-19 pandemic.Main outcome measuresExpected and excess mortality for the United States during the covid-19 period.ResultsAs of week 53, 2020 (ending January 2, 2021), approximately >10,200 more excess deaths have occurred in the United States than could be detected if expected deaths projections were not amended to reflect population decreases during 2020. The figure is projected to rise to >12,600 (>600 weekly) by week 5, 2021. Assuming recent excess mortality and pandemic-associated visa reductions continue until the earliest time herd immunity could be approached resulting from a combination of infections and vaccinations (week 17, 2021), if point estimates of expected deaths are not corrected, expected deaths will be overestimated (and therefore potential excess mortality underestimated) by ∼43,000 during 2021, or >53,300 since the outbreak of the pandemic measurement period (beginning week 5, 2020). By late December 2021, weekly expected death differences are projected to approach 1,000 per week.ConclusionsCurrent models measuring excess mortality should be revised immediately so that public health officials do not lose the ability to detect ongoing excess mortality as the population changes continue to compound, lowering the number of weekly expected deaths. A similar approach should be used in the middle and late phases of all future pandemics.

Download Full-text

Exploring the Power of County-Level Regional Classifications on Predicting Sex-Specific All-Cause Mortality in the United States

10.33915/etd.6968 ◽

2017 ◽

Author(s):

Julia Kay Wolf

Keyword(s):

United States ◽

The United States ◽

County Level ◽

All Cause Mortality

Download Full-text

On the Relationship between Development and Fertility: The Case of the United States

Comparative Population Studies ◽

10.12765/cpos-2015-13 ◽

2015 ◽

Vol 40 (4) ◽

Author(s):

Igor Ryabov

Keyword(s):

United States ◽

Human Development ◽

Negative Relationship ◽

The United States ◽

Median Income ◽

County Level ◽

Cross Sectional ◽

Development Indicators ◽

Rural Counties ◽

The Relationship

The present article addresses the question of whether there is a link between the spatial patterns of human development and period fertility in the United States at the county level. Using cross-sectional analyses of the relationship between Total Fertility Rate (TFR) and an array of human development indicators (pertaining to three components of the Human Development Index (HDI) – wealth, health, and education), this study sheds light on the relationship between fertility and human development. The analyses were conducted separately for urban, suburban and rural counties. According to the multivariate results, a negative association between selected human development indicators and TFR exists in suburban and rural counties, as well as in the United States as a whole. However, this is not the case for urban counties, where the results were inconclusive. Some indicators (e.g., median income per capita) were found to be positively, and some (e.g., the share of adults with at least bachelor’s degree) negatively, associated with TFR in urban counties. All in all, our results provide evidence of a negative relationship between human development indicators and period fertility in the United States at the county level, a finding which is consistent with the basic tenets of classic demographic transition theory.

Download Full-text

Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis

10.1101/2020.08.31.20184036 ◽

2020 ◽

Author(s):

Andrew C Stokes ◽

Dielle J Lundberg ◽

Katherine Hempstead ◽

Irma T Elo ◽

Samuel H Preston

Keyword(s):

Causes Of Death ◽

Excess Mortality ◽

Structural Characteristics ◽

County Level ◽

Structural Racism ◽

All Cause Mortality ◽

Black Residents ◽

The Impact ◽

Level Analysis ◽

Excess Deaths

Covid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. In this study, we take advantage of spatial variation in Covid-19 mortality across US counties to estimate its relationship with all-cause mortality. We then examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by demographic and structural characteristics. We estimate that 26.3% [95% CI, 20.1% to 32.5%] of excess deaths between February 1 and September 23, 2020 were ascribed to causes of death other than Covid-19 itself. Excess deaths not assigned to Covid-19 were even higher than predicted by our model in counties with high income inequality, low homeownership, and high percentages of Black residents, showing a pattern related to socioeconomic disadvantage and structural racism. The standard deviation of mortality across counties increased by 9.5% as a result of excess deaths directly assigned to Covid-19 and an additional 5.3% as a result of excess deaths not assigned to Covid-19. Our work suggests that inequities in excess deaths attributable to Covid-19 may be even greater than revealed by data reporting deaths assigned to Covid-19 alone.

Download Full-text

Abstract 16562: Association of County-Level Social Vulnerability Index and Cardiovascular Disease in the United States, 1999-2018

Circulation ◽

10.1161/circ.142.suppl_3.16562 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Quentin R Youmans ◽

Megan E McCabe ◽

Clyde W Yancy ◽

Lucia Petito ◽

Kiarri N Kershaw ◽

...

Keyword(s):

United States ◽

Cardiovascular Disease ◽

Social Vulnerability ◽

Cardiovascular Health ◽

Vulnerability Index ◽

The United States ◽

County Level ◽

Social Vulnerability Index ◽

Cross Sectional ◽

Cvd Mortality

Introduction: Social determinants of health are multi-dimensional and span various interrelated domains. In order to inform community-engaged clinical and policy efforts, we sought to examine the association between a national social vulnerability index (SVI) and age-adjusted mortality rate (AAMR) of CVD. Hypothesis: Higher county-level SVI or greater vulnerability will be associated with higher AAMR of CVD between 1999-2018 in the United States. Methods: In this serial, cross-sectional analysis, we queried CDC WONDER for age-adjusted mortality rates (AAMRs) per 100,000 population for cardiovascular disease (I00-78) at the county-level between 1999-2018. We quantified the association of county-level SVI and CVD AAMR using Spearman correlation coefficients and examined trends in CVD AAMR stratified by median SVI at the county-level. Finally, we performed geospatial county-level analysis stratified by combined median SVI and CVD AAMR (high/high, high/low, low/high, and low/low). Results: We included data from 2766 counties (representing 95% of counties in the US) with median SVI 0.53 (IQR 0.28, 0.76). Overall SVI and the household and socioeconomic subcomponents were strongly correlated with 2018 CVD AAMR (0.47, 0.50, and 0.56, respectively with p<0.001 for all). CVD mortality declined between 1999-2011 and was stagnant between 2011-2018 with similar patterns in high and low SVI counties (FIGURE). Counties with high SVI and CVD AAMR were clustered in the South and Midwest (n=977, 35%). Conclusion: County-level social vulnerability is associated with higher CVD mortality. High SVI and CVD AAMR coexist in more than 1 in 3 US counties and have persisted over the past 2 decades. Identifying counties that are disproportionately vulnerable may inform targeted and community-based strategies to equitably improve cardiovascular health across the country.

Download Full-text

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

SSM - Population Health ◽

10.1016/j.ssmph.2021.101021 ◽

2022 ◽

pp. 101021

Author(s):

Calvin A. Ackley ◽

Dielle J. Lundberg ◽

Lei Ma ◽

Irma T. Elo ◽

Samuel H. Preston ◽

...

Keyword(s):

United States ◽

Excess Mortality ◽

The United States ◽

County Level

Download Full-text

Changes in Excess Mortality from End Stage Renal Disease in the United States from 1995 to 2013

Clinical Journal of the American Society of Nephrology ◽

10.2215/cjn.04330417 ◽

2017 ◽

Vol 13 (1) ◽

pp. 91-99 ◽

Cited By ~ 27

Author(s):

Bethany J. Foster ◽

Mark M. Mitsnefes ◽

Mourad Dahhou ◽

Xun Zhang ◽

Benjamin L. Laskin

Keyword(s):

United States ◽

General Population ◽

Excess Mortality ◽

The United States ◽

Mortality Rates ◽

Excess Risk ◽

Calendar Time ◽

Risk Of Death ◽

All Cause Mortality ◽

Functioning Kidney

Background and objectivesIndividuals with ESRD have a very high risk of death. Although mortality rates have decreased over time in ESRD, it is unknown if improvements merely reflect parallel increases in general population survival. We, therefore, examined changes in the excess risk of all-cause mortality—over and above the risk in the general population—among people treated for ESRD in the United States from 1995 to 2013. We hypothesized that the magnitude of change in the excess risk of death would differ by age and RRT modality.Design, setting, participants, & measurementsWe used time-dependent relative survival models including data from persons with incident ESRD as recorded in the US Renal Data System and age-, sex-, race-, and calendar year–specific general population mortality rates from the Centers for Disease Control and Prevention. We calculated relative excess risks (analogous to hazard ratios) to examine the association between advancing calendar time and the primary outcome of all-cause mortality.ResultsWe included 1,938,148 children and adults with incident ESRD from 1995 to 2013. Adjusted relative excess risk per 5-year increment in calendar time ranged from 0.73 (95% confidence interval, 0.69 to 0.77) for 0–14 year olds to 0.88 (95% confidence interval, 0.88 to 0.88) for ≥65 year olds, meaning that the excess risk of ESRD-related death decreased by 12%–27% over any 5-year interval between 1995 and 2013. Decreases in excess mortality over time were observed for all ages and both during treatment with dialysis and during time with a functioning kidney transplant (year by age and year by renal replacement modality interactions were both P<0.001), with the largest relative improvements observed for the youngest persons with a functioning kidney transplant. Absolute decreases in excess ESRD-related mortality were greatest for the oldest persons.ConclusionsThe excess risk of all-cause mortality among people with ESRD, over and above the risk in the general population, decreased significantly between 1995 and 2013 in the United States.

Download Full-text