scholarly journals County-level Predictors of Coronavirus Disease 2019 (COVID-19) Cases and Deaths in the United States: What Happened, and Where Do We Go from Here?

2020 ◽  
Author(s):  
John M McLaughlin ◽  
Farid Khan ◽  
Sarah Pugh ◽  
Frederick J Angulo ◽  
Heinz-Josef Schmitt ◽  
...  
Keyword(s):  
United States ◽  
Negative Binomial ◽  
Preventive Measures ◽  
Severe Disease ◽  
Multivariable Analysis ◽  
The United States ◽  
County Level ◽  
Residential Housing ◽  
Minority Communities ◽  
Racial Ethnic

Abstract Background The United States has been heavily impacted by the coronavirus disease 2019 (COVID-19) pandemic. Understanding microlevel patterns in US rates of COVID-19 can inform specific prevention strategies. Methods Using a negative binomial mixed-effects regression model, we evaluated the associations between a broad set of US county-level sociodemographic, economic, and health status–related characteristics and cumulative rates of laboratory-confirmed COVID-19 cases and deaths between 22 January 2020 and 31 August 2020. Results Rates of COVID-19 cases and deaths were higher in US counties that were more urban or densely populated or that had more crowded housing, air pollution, women, persons aged 20–49 years, racial/ethnic minorities, residential housing segregation, income inequality, uninsured persons, diabetics, or mobility outside the home during the pandemic. Conclusions To our knowledge, this study provides results from the most comprehensive multivariable analysis of county-level predictors of rates of COVID-19 cases and deaths conducted to date. Our findings make clear that ensuring that COVID-19 preventive measures, including vaccines when available, reach vulnerable and minority communities and are distributed in a manner that meaningfully disrupts transmission (in addition to protecting those at highest risk of severe disease) will likely be critical to stem the pandemic.

scholarly journals Trends in heart failure-related cardiovascular mortality in rural versus urban United States counties, 2011–2018: A cross-sectional study

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246813
Author(s):  
Jacob B. Pierce ◽  
Nilay S. Shah ◽  
Lucia C. Petito ◽  
Lindsay Pool ◽  
Donald M. Lloyd-Jones ◽  
...  
Keyword(s):  
United States ◽  
Heart Failure ◽  
Cause Of Death ◽  
Negative Binomial ◽  
The United States ◽  
Mortality Rates ◽  
County Level ◽  
Physician Density ◽  
Rural And Urban ◽  
Related Mortality

Background Adults in rural counties in the United States (US) experience higher rates broadly of cardiovascular disease (CVD) compared with adults in urban counties. Mortality rates specifically due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality have not been produced. The objectives of this study were 1) to quantify nationwide trends by rural-urban designation and 2) examine county-level factors associated with rural-urban differences in HF-related mortality rates. Methods and findings We queried CDC WONDER to identify HF deaths between 2011–2018 defined as CVD (I00-78) as the underlying cause of death and HF (I50) as a contributing cause of death. First, we calculated national age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35–64 and 65–84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011–2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for demographic and socioeconomic characteristics, risk factor prevalence, and physician density. Between 2011–2018, 162,314 and 580,305 HF-related deaths occurred in rural and urban counties, respectively. AAMRs were consistently higher for residents in rural compared with urban counties (73.2 [95% CI: 72.2–74.2] vs. 57.2 [56.8–57.6] in 2018, respectively). The highest AAMR was observed in rural Black men (131.1 [123.3–138.9] in 2018) with greatest increases in HF-related mortality in those 35–64 years (+6.1%/year). The rural-urban IRR persisted among both younger (1.10 [1.04–1.16]) and older adults (1.04 [1.02–1.07]) after adjustment for county-level factors. Main limitations included lack of individual-level data and county dropout due to low event rates (<20). Conclusions Differences in county-level factors may account for a significant amount of the observed variation in HF-related mortality between rural and urban counties. Efforts to reduce the rural-urban disparity in HF-related mortality rates will likely require diverse public health and clinical interventions targeting the underlying causes of this disparity.

scholarly journals Changing Spatiotemporal Trends in County‐Level Heart Failure Death Rates in the United States, 1999 to 2018

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Adam S. Vaughan ◽  
Mary G. George ◽  
Sandra L. Jackson ◽  
Linda Schieb ◽  
Michele Casper
Keyword(s):  
United States ◽  
Heart Failure ◽  
Ethnic Group ◽  
The United States ◽  
Local Context ◽  
County Level ◽  
Age Group ◽  
Death Rates ◽  
Spatiotemporal Trends ◽  
Racial Ethnic

Background Amid recently rising heart failure (HF) death rates in the United States, we describe county‐level trends in HF mortality from 1999 to 2018 by racial/ethnic group and sex for ages 35 to 64 years and 65 years and older. Methods and Results Applying a hierarchical Bayesian model to National Vital Statistics data representing all US deaths, ages 35 years and older, we estimated annual age‐standardized county‐level HF death rates and percent change by age group, racial/ethnic group, and sex from 1999 through 2018. During 1999 to 2011, ~30% of counties experienced increasing HF death rates among adults ages 35 to 64 years. However, during 2011 to 2018, 86.9% (95% CI, 85.2–88.2) of counties experienced increasing mortality. Likewise, for ages 65 years and older, during 1999 to 2005 and 2005 to 2011, 27.8% (95% CI, 25.8–29.8) and 12.6% (95% CI, 11.2–13.9) of counties, respectively, experienced increasing mortality. However, during 2011 to 2018, most counties (67.4% [95% CI, 65.4–69.5]) experienced increasing mortality. These temporal patterns by age group held across racial/ethnic group and sex. Conclusions These results provide local context to previously documented recent national increases in HF death rates. Although county‐level declines were most common before 2011, some counties and demographic groups experienced increasing HF death rates during this period of national declines. However, recent county‐level increases were pervasive, occurring across counties, racial/ethnic group, and sex, particularly among ages 35 to 64 years. These spatiotemporal patterns highlight the need to identify and address underlying clinical risk factors and social determinants of health contributing to these increasing trends.

scholarly journals Giardiasis in the United States – an epidemiologic and geospatial analysis of county-level drinking water and sanitation data, 1993–2010

2015 ◽  
Vol 14 (2) ◽  
pp. 267-279 ◽  
Author(s):  
Kerry Schnell ◽  
Sarah Collier ◽  
Gordana Derado ◽  
Jonathan Yoder ◽  
Julia Warner Gargano
Keyword(s):  
United States ◽  
Negative Binomial ◽  
Parasitic Infection ◽  
The United States ◽  
Incidence Rates ◽  
County Level ◽  
Septic System ◽  
Water And Sanitation ◽  
South Central ◽  
Private Wells

Giardiasis is the most commonly reported intestinal parasitic infection in the United States. Outbreak investigations have implicated poorly maintained private wells, and hypothesized a role for wastewater systems in giardiasis transmission. Surveillance data consistently show geographic variability in reported giardiasis incidence. We explored county-level associations between giardiasis cases, household water and sanitation (1990 census), and US Census division. Using 368,847 reported giardiasis cases (1993–2010), we mapped county-level giardiasis incidence rates, private well reliance, and septic system reliance, and assessed spatiotemporal clustering of giardiasis. We used negative binomial regression to evaluate county-level associations between giardiasis rates, region, and well and septic reliance, adjusted for demographics. Adjusted giardiasis incidence rate ratios (aIRRs) were highest (aIRR 1.3; 95% confidence interval 1.2–1.5) in counties with higher private well reliance. There was no significant association between giardiasis and septic system reliance in adjusted models. Consistent with visual geographic distributions, the aIRR of giardiasis was highest in New England (aIRR 3.3; 95% CI 2.9–3.9; reference West South Central region). Our results suggest that, in the USA, private wells are relevant to giardiasis transmission; giardiasis risk factors might vary regionally; and up-to-date, location-specific national data on water sources and sanitation methods are needed.

scholarly journals County-level exposures to greenness and associations with COVID-19 incidence and mortality in the United States

2020 ◽  
Author(s):  
Jochem O Klompmaker ◽  
Jaime E Hart ◽  
Isabel Holland ◽  
M Benjamin Sabath ◽  
Xiao Wu ◽  
...  
Keyword(s):  
United States ◽  
Population Density ◽  
Vegetation Index ◽  
Negative Binomial ◽  
The United States ◽  
Systems Science ◽  
County Level ◽  
Incidence And Mortality ◽  
The Us ◽  
At Home

AbstractBackgroundCOVID-19 is an infectious disease that has killed more than 246,000 people in the US. During a time of social distancing measures and increasing social isolation, green spaces may be a crucial factor to maintain a physically and socially active lifestyle while not increasing risk of infection.ObjectivesWe evaluated whether greenness is related to COVID-19 incidence and mortality in the United States.MethodsWe downloaded data on COVID-19 cases and deaths for each US county up through June 7, 2020, from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. We used April-May 2020 Normalized Difference Vegetation Index (NDVI) data, to represent the greenness exposure during the initial COVID-19 outbreak in the US. We fitted negative binomial mixed models to evaluate associations of NDVI with COVID-19 incidence and mortality, adjusting for potential confounders such as county-level demographics, epidemic stage, and other environmental factors. We evaluated whether the associations were modified by population density, proportion of Black residents, median home value, and issuance of stay-at-home order.ResultsAn increase of 0.1 in NDVI was associated with a 6% (95% Confidence Interval: 3%, 10%) decrease in COVID-19 incidence rate after adjustment for potential confounders. Associations with COVID-19 incidence were stronger in counties with high population density and in counties with stay-at-home orders. Greenness was not associated with COVID-19 mortality in all counties; however, it was protective in counties with higher population density.DiscussionExposures to NDVI had beneficial impacts on county-level incidence of COVID-19 in the US and may have reduced county-level COVID-19 mortality rates, especially in densely populated counties.

Neighborhood Deprivation and Racial/Ethnic Disparities in Human Immunodeficiency Virus Viral Suppression: A Single-center, Cross-sectional Study in the United States Midwest

2020 ◽  
Author(s):  
Rohan Khazanchi ◽  
Harlan Sayles ◽  
Sara H Bares ◽  
Susan Swindells ◽  
Jasmine R Marcelin
Keyword(s):  
United States ◽  
Human Immunodeficiency Virus ◽  
Low Income ◽  
Viral Suppression ◽  
Multivariable Analysis ◽  
Ethnic Disparities ◽  
The United States ◽  
Neighborhood Deprivation ◽  
Immunodeficiency Virus ◽  
Racial Ethnic

Abstract Combating disparities is a crucial goal of ongoing efforts to end the human immunodeficiency virus (HIV) epidemic. In a multivariable analysis of a cohort in the Midwestern United States, racial/ethnic disparities in HIV viral suppression were no longer robust after accounting for other sociodemographic factors. Neighborhood deprivation and low income were independently inversely associated with viral suppression.

scholarly journals An Approach to Achieving the Health Equity Goals of the National HIV/AIDS Strategy for the United States Among Racial/Ethnic Minority Communities

2016 ◽  
Vol 131 (4) ◽  
pp. 526-530 ◽  
Author(s):  
Donna Hubbard McCree ◽  
Linda Beer ◽  
Cynthia Prather ◽  
Zanetta Gant ◽  
Norma Harris ◽  
...  
Keyword(s):  
United States ◽  
Ethnic Minority ◽  
Health Equity ◽  
The United States ◽  
Minority Communities ◽  
Racial Ethnic ◽  
Hiv Aids

scholarly journals Risk factors associated with mortality of COVID-19 in 3125 counties of the United States

2020 ◽  
Author(s):  
Ting Tian ◽  
Jingwen Zhang ◽  
Liyuan Hu ◽  
Yukang Jiang ◽  
Congyuan Duan ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Negative Binomial ◽  
The United States ◽  
Outdoor Environment ◽  
Local Health ◽  
County Level ◽  
Factors Associated ◽  
High Prevalence ◽  
The Impact

Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. Methods To find out the risk factors associated with county-level mortality of COVID-19 with various levels of prevalence, a negative binomial design was applied to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Results 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P<0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median and high prevalence counties . The segregation between non-Whites and Whites and higher Hispanic population had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may lead to the reduction in the mortality of COVID-19.

scholarly journals The Magnitude of Black/Hispanic Disparity in COVID-19 Mortality Across United States Counties During the First Waves of the COVID-19 Pandemic

2021 ◽  
Vol 66 ◽  
Author(s):  
Cindy Im ◽  
Lalani L. Munasinghe ◽  
José M. Martínez ◽  
William Letsou ◽  
Farideh Bagherzadeh-Khiabani ◽  
...  
Keyword(s):  
United States ◽  
Ethnic Diversity ◽  
The United States ◽  
County Level ◽  
Urbanization Level ◽  
The Us ◽  
Disparity Gradient ◽  
Rate Ratios ◽  
Racial Ethnic ◽  
Death Count

Objectives: To quantify the Black/Hispanic disparity in COVID-19 mortality in the United States (US).Methods: COVID-19 deaths in all US counties nationwide were analyzed to estimate COVID-19 mortality rate ratios by county-level proportions of Black/Hispanic residents, using mixed-effects Poisson regression. Excess COVID-19 mortality counts, relative to predicted under a counterfactual scenario of no racial/ethnic disparity gradient, were estimated.Results: County-level COVID-19 mortality rates increased monotonically with county-level proportions of Black and Hispanic residents, up to 5.4-fold (≥43% Black) and 11.6-fold (≥55% Hispanic) higher compared to counties with &lt;5% Black and &lt;15% Hispanic residents, respectively, controlling for county-level poverty, age, and urbanization level. Had this disparity gradient not existed, the US COVID-19 death count would have been 92.1% lower (177,672 fewer deaths), making the rate comparable to other high-income countries with substantially lower COVID-19 death counts.Conclusion: During the first 8 months of the SARS-CoV-2 pandemic, the US experienced the highest number of COVID-19 deaths. This COVID-19 mortality burden is strongly associated with county-level racial/ethnic diversity, explaining most US COVID-19 deaths.

scholarly journals Risk factors associated with mortality of COVID-19 in 3125 counties of the United States

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ting Tian ◽  
Jingwen Zhang ◽  
Liyuan Hu ◽  
Yukang Jiang ◽  
Congyuan Duan ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Clustering Analysis ◽  
Negative Binomial ◽  
The United States ◽  
Outdoor Environment ◽  
Local Health ◽  
County Level ◽  
Factors Associated ◽  
The Impact

Abstract Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstract

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