Browse
Submit Data
Databases
API
Help

Dataset Information

26 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dynamics of the COVID-19 epidemic in urban and rural areas in the United States.

ABSTRACT:

Purpose

There is a growing concern about the COVID-19 epidemic intensifying in rural areas in the United States (U.S.). In this study, we described the dynamics of COVID-19 cases and deaths in rural and urban counties in the U.S.

Methods

Using data from April 1 to November 12, 2020, from Johns Hopkins University, we estimated COVID-19 incidence and mortality rates and conducted comparisons between urban and rural areas in three time periods at the national level, and in states with higher and lower COVID-19 incidence rates.

Results

Results at the national level showed greater COVID-19 incidence rates in urban compared to rural counties in the Northeast and Mid-Atlantic regions of the U.S. at the beginning of the epidemic. However, the intensity of the epidemic has shifted to a rapid surge in rural areas. In particular, high incidence states located in the Mid-west of the country had more than 3,400 COVID-19 cases per 100,000 people compared to 1,284 cases per 100,000 people in urban counties nationwide during the third period (August 30 to November 12).

Conclusions

Overall, the current epicenter of the epidemic is located in states with higher infection rates and mortality in rural areas. Infection prevention and control efforts including healthcare capacity should be scaled up in these vulnerable rural areas.

SUBMITTER: Cuadros DF

PROVIDER: S-EPMC8061094 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

COVID-19 Hospitalization Trends in Rural Versus Urban Areas in the United States.

Project description:Since the summer of 2020, the rate of coronavirus cases in the United States has been higher in rural areas than in urban areas, raising concerns that patients with coronavirus disease 2019 (COVID-19) will overwhelm under-resourced rural hospitals. Using data from the University of Minnesota COVID-19 Hospitalization Tracking Project and the U.S. Department of Health and Human Services, we document disparities in COVID-19 hospitalization rates between rural and urban areas. We show that rural-urban differences in COVID-19 admission rates were minimal in the summer of 2020 but began to diverge in fall 2020. Rural areas had statistically higher hospitalization rates from September 2020 through early 2021, after which rural-urban admission rates re-converged. The insights in this article are relevant to policymakers as they consider the adequacy of hospital resources across rural and urban areas during the COVID-19 pandemic.

| S-EPMC10011918 | biostudies-literature

Progression of COVID-19 From Urban to Rural Areas in the United States: A Spatiotemporal Analysis of Prevalence Rates.

Project description:PURPOSE:There are growing signs that the COVID-19 virus has started to spread to rural areas and can impact the rural health care system that is already stretched and lacks resources. To aid in the legislative decision process and proper channelizing of resources, we estimated and compared the county-level change in prevalence rates of COVID-19 by rural-urban status over 3 weeks. Additionally, we identified hotspots based on estimated prevalence rates. METHODS:We used crowdsourced data on COVID-19 and linked them to county-level demographics, smoking rates, and chronic diseases. We fitted a Bayesian hierarchical spatiotemporal model using the Markov Chain Monte Carlo algorithm in R-studio. We mapped the estimated prevalence rates using ArcGIS 10.8, and identified hotspots using Gettis-Ord local statistics. FINDINGS:In the rural counties, the mean prevalence of COVID-19 increased from 3.6 per 100,000 population to 43.6 per 100,000 within 3 weeks from April 3 to April 22, 2020. In the urban counties, the median prevalence of COVID-19 increased from 10.1 per 100,000 population to 107.6 per 100,000 within the same period. The COVID-19 adjusted prevalence rates in rural counties were substantially elevated in counties with higher black populations, smoking rates, and obesity rates. Counties with high rates of people aged 25-49 years had increased COVID-19 prevalence rates. CONCLUSIONS:Our findings show a rapid spread of COVID-19 across urban and rural areas in 21 days. Studies based on quality data are needed to explain further the role of social determinants of health on COVID-19 prevalence.

| S-EPMC7361905 | biostudies-literature

The Impact of the COVID-19 Epidemic on Older Adults in Rural and Urban Areas in Mexico.

Project description:ObjectivesMexico is among the countries in Latin America hit hardest by coronavirus disease 2019 (COVID-19). A large proportion of older adults in Mexico have high prevalence of multimorbidity and live in poverty with limited access to health care services. These statistics are even higher among adults living in rural areas, which suggest that older adults in rural communities may be more susceptible to COVID-19. The objectives of the article were to compare clinical and demographic characteristics for people diagnosed with COVID-19 by age group, and to describe cases and mortality in rural and urban communities.MethodWe linked publicly available data from the Mexican Ministry of Health and the Census. Municipalities were classified based on population as rural (<2,500), semirural (≥2,500 and <15,000), semiurban (≥15,000 and <100,000), and urban (≥100,000). Zero-inflated negative binomial models were performed to calculate the total number of COVID-19 cases, and deaths per 1,000,000 persons using the population of each municipality as a denominator.ResultsOlder adults were more likely to be hospitalized and reported severe cases, with higher mortality rates. In addition, rural municipalities reported a higher number of COVID-19 cases and mortality related to COVID-19 per million than urban municipalities. The adjusted absolute difference in COVID-19 cases was 912.7 per million (95% confidence interval [CI]: 79.0-1746.4) and mortality related to COVID-19 was 390.6 per million (95% CI: 204.5-576.7).DiscussionUrgent policy efforts are needed to mandate the use of face masks, encourage handwashing, and improve specialty care for Mexicans in rural areas.

| S-EPMC7798580 | biostudies-literature

Modeling of the Long-Term Epidemic Dynamics of COVID-19 in the United States.

Project description:Coronavirus 2019 (COVID-19) is causing a severe pandemic that has resulted in millions of confirmed cases and deaths around the world. In the absence of effective drugs for treatment, non-pharmaceutical interventions are the most effective approaches to control the disease. Although some countries have the pandemic under control, all countries around the world, including the United States (US), are still in the process of controlling COVID-19, which calls for an effective epidemic model to describe the transmission dynamics of COVID-19. Meeting this need, we have extensively investigated the transmission dynamics of COVID-19 from 22 January 2020 to 14 February 2021 for the 50 states of the United States, which revealed the general principles underlying the spread of the virus in terms of intervention measures and demographic properties. We further proposed a time-dependent epidemic model, named T-SIR, to model the long-term transmission dynamics of COVID-19 in the US. It was shown in this paper that our T-SIR model could effectively model the epidemic dynamics of COVID-19 for all 50 states, which provided insights into the transmission dynamics of COVID-19 in the US. The present study will be valuable to help understand the epidemic dynamics of COVID-19 and thus help governments determine and implement effective intervention measures or vaccine prioritization to control the pandemic.

| S-EPMC8305610 | biostudies-literature

Pre-Pregnancy Hypertension Among Women in Rural and Urban Areas of the United States.

Project description:BackgroundRates of maternal mortality are increasing in the United States with significant rural-urban disparities. Pre-pregnancy hypertension is a well-established risk factor for adverse maternal and offspring outcomes.ObjectivesThe purpose of this study was to describe trends in maternal pre-pregnancy hypertension among women in rural and urban areas in 2007 to 2018 in order to inform community-engaged prevention and policy strategies.MethodsWe performed a nationwide, serial cross-sectional study using maternal data from all live births in women age 15 to 44 years between 2007 and 2018 (CDC Natality Database). Rates of pre-pregnancy hypertension were calculated per 1,000 live births overall and by urbanization status. Subgroup analysis in standard 5-year age categories was performed. We quantified average annual percentage change using Joinpoint Regression and rate ratios (95% confidence intervals [CIs]) to compare yearly rates between rural and urban areas.ResultsAmong 47,949,381 live births to women between 2007 and 2018, rates of pre-pregnancy hypertension per 1,000 live births increased among both rural (13.7 to 23.7) and urban women (10.5 to 20.0). Two significant inflection points were identified in 2010 and 2016, with highest annual percentage changes between 2016 and 2018 in rural and urban areas. Although absolute rates were lower in younger compared with older women in both rural and urban areas, all age groups experienced similar increases. The rate ratios of pre-pregnancy hypertension in rural compared with urban women ranged from 1.18 (95% CI: 1.04 to 1.35) for ages 15 to 19 years to 1.51 (95% CI: 1.39 to 1.64) for ages 40 to 44 years in 2018.ConclusionsMaternal burden of pre-pregnancy hypertension has nearly doubled in the past decade and the rural-urban gap has persisted.

| S-EPMC7704760 | biostudies-literature

Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States.

Project description:PurposeThis study creates a COVID-19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural-urban continuum.MethodsFactor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC.ResultsAbout 33% of rural counties are highly susceptible to COVID-19, driven by older and health-compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress.ConclusionsThere is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter-in-place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities.

| S-EPMC7323251 | biostudies-literature

Rural tobacco use across the United States: How rural and urban areas differ, broken down by census regions and divisions.

Project description:This project compared urban/rural differences in tobacco use, and examined how such differences vary across regions/divisions of the U.S. Using pooled 2012-2013 data from the National Survey on Drug Use and Health (NSDUH), we obtained weighted prevalence estimates for the use of cigarettes, menthol cigarettes, chewing tobacco, snuff, cigars, and pipes. NSDUH also provides information on participants' residence: rural vs. urban, and Census region and division. Overall, use of cigarettes, chew, and snuff were higher in rural, compared to urban areas. Across all tobacco products, urban/rural differences were particularly pronounced in certain divisions (e.g., the South Atlantic). Effects did not appear to be fully explained by differences in poverty. Going beyond previous research, these findings show that urban/rural differences vary across different types of tobacco products, as well as by division of the country. Results underscore the need for regulatory efforts that will reduce health disparities.

| S-EPMC4874850 | biostudies-literature

Spatiotemporal Characteristics of the COVID-19 Epidemic in the United States.

Project description:BackgroundA range of near-real-time online/mobile mapping dashboards and applications have been used to track the coronavirus disease 2019 (COVID-19) pandemic worldwide; however, small area-based spatiotemporal patterns of COVID-19 in the United States remain unknown.MethodsWe obtained county-based counts of COVID-19 cases confirmed in the United States from 22 January to 13 May 2020 (N = 1 386 050). We characterized the dynamics of the COVID-19 epidemic through detecting weekly hotspots of newly confirmed cases using Spatial and Space-Time Scan Statistics and quantifying the trends of incidence of COVID-19 by county characteristics using the Joinpoint analysis.ResultsAlong with the national plateau reached in early April, COVID-19 incidence significantly decreased in the Northeast (estimated weekly percentage change [EWPC]: -16.6%) but continued increasing in the Midwest, South, and West (EWPCs: 13.2%, 5.6%, and 5.7%, respectively). Higher risks of clustering and incidence of COVID-19 were consistently observed in metropolitan versus rural counties, counties closest to core airports, the most populous counties, and counties with the highest proportion of racial/ethnic minorities. However, geographic differences in incidence have shrunk since early April, driven by a significant decrease in the incidence in these counties (EWPC range: -2.0%, -4.2%) and a consistent increase in other areas (EWPC range: 1.5-20.3%).ConclusionsTo substantially decrease the nationwide incidence of COVID-19, strict social-distancing measures should be continuously implemented, especially in geographic areas with increasing risks, including rural areas. Spatiotemporal characteristics and trends of COVID-19 should be considered in decision making on the timeline of re-opening for states and localities.

| S-EPMC7454424 | biostudies-literature

Urban Flight Seeded the COVID-19 Pandemic Across the United States.

Project description:We document large-scale urban flight in the United States during the COVID-19 pandemic. Regions that saw migrant influx experienced greater subsequent new COVID-19 cases, linking urban flight (as a disease vector) and coronavirus spread in destination areas. Urban residents fled to socially connected areas, consistent with the theory that individuals sheltered with friends and family, or in second homes. Populations that fled were disproportionately younger, whiter, and wealthier. The association between migration and subsequent new cases persists when instrumenting for migration with social networks.

| S-EPMC9344811 | biostudies-literature

Robustness of estimated access to opioid use disorder treatment providers in rural vs. urban areas of the United States.

Project description:BackgroundEffective, evidence-based treatments for opioid use disorder are not equally accessible to Americans. Recent studies have found urban/rural disparities in the driving times to the nearest opioid treatment providers. These disparities may be even worse than currently reported in the literature because patients may not be able to obtain appointments with their nearest provider. We examine the robustness of the opioid treatment infrastructure by estimating how driving times to treatment change as provider availability decreases.MethodsWe used public data from the federal government to estimate the driving time from each census tract centroid to the nearest 15 treatment providers. We summarized the median and interquartile range of driving times to increasingly distant providers (i.e., nearest, second nearest, etc.), stratified by urban/rural classification.ResultsThe median driving time to the nearest provider was greater in rural areas than urban areas for both opioid treatment programs (12 min vs 61 min) and buprenorphine-waivered prescribers (5 min vs 21 min). Importantly, driving times in rural areas increased more steeply as nearer providers became unavailable. For example, the increase in driving time between the nearest provider and the fifth nearest provider was much greater in rural areas than in urban areas for both buprenorphine-waivered prescribers (23 min vs 4 min) and for opioid treatment programs (54 min vs 22 min).ConclusionsAccess to treatment for opioid use disorder is more robust in urban areas compared with rural areas. This disparity must be eliminated if the opioid overdose crisis is to be resolved.

| S-EPMC8595811 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data