Amplified effect of social vulnerability on health inequality regarding COVID-19 mortality in the USA: the mediating role of vaccination allocation DOI Creative Commons
Ying Chen, Lanwei Zhang, Tenglong Li

и другие.

BMC Public Health, Год журнала: 2022, Номер 22(1)

Опубликована: Ноя. 19, 2022

Vaccination reduces the overall burden of COVID-19, while its allocation procedure may introduce additional health inequality, since populations characterized with certain social vulnerabilities have received less vaccination and been affected more by COVID-19. We used structural equation modeling to quantitatively evaluate extent which disparity would amplify where it functioned as a mediator in effect pathways from COVID-19 mortality.We USA nationwide county (n = 3112, 99% total) level data during 2021 an ecological study design. Theme-specific rankings vulnerability index published CDC (latest 2018, including socioeconomic status, household composition & disability, minority status language, housing type transportation) were exposure variables. coverage rate (VCR) was variable, case fatality (CFR) John Hopkinson University, outcome variable.Greater language inversely associated VCR, together explaining 11.3% variance VCR. Greater disability positively CFR, VCR 10.4% CFR. Our mediation analysis, based on mid-year (30th June 2021), found that 37.6% (mediation/total effect, 0.0014/0.0037), 10% (0.0003/0.0030) 100% (0.0005/0.0005) effects involving respectively, mediated As whole, significantly counted for 30.6% CFR disparity. Such seen throughout 2021, proportions ranging 12 32%.Allocation led inequality respect mortality. Viable public interventions should be taken guarantee equitable deployment healthcare recourses across different population groups.

Язык: Английский

Geographic disparities in COVID-19 testing and outcomes in Florida DOI Creative Commons
Md Marufuzzaman Khan, Agricola Odoi, Evah W. Odoi

и другие.

BMC Public Health, Год журнала: 2023, Номер 23(1)

Опубликована: Янв. 11, 2023

Abstract Background Understanding geographic disparities in Coronavirus Disease 2019 (COVID-19) testing and outcomes at the local level during early stages of pandemic can guide policies, inform allocation control prevention resources, provide valuable baseline data to evaluate effectiveness interventions for mitigating health, economic social impacts. Therefore, objective this study was identify COVID-19 testing, incidence, hospitalizations, deaths first five months Florida. Methods Florida county-level time period March-July 2020 were used compute various metrics including rates, positivity incidence risks, percent hospitalized cases, hospitalization case-fatality mortality risks. High or low risk clusters identified using either Kulldorff’s circular spatial scan statistics Tango’s flexible their locations visually displayed QGIS. Results Visual examination patterns showed high estimates all Southern Similar patterns, high-risk rates (i.e. hospitalizations deaths) concentrated The distributions these other parts more heterogeneous. For instance, Northwest well below state median (11,697 tests/100,000 persons) but they above North Central risks equal (878 cases/100,000 persons), converse true Consequently, a cluster Florida, while rate 1–3 case fatality had low-rate it cases. Conclusions Substantial distribution exist with counties generally having higher severe compared Northern These findings that is useful assessing preventive interventions, such as vaccinations, state. Future studies will need assess changes over lower geographical scales determinants any patterns.

Язык: Английский

Процитировано

21

Associations Between Built Environment Factors and SARS-CoV-2 Infections at the Neighbourhood Level in a Metropolitan Area in Germany DOI Creative Commons
Dennis Schmiege, Timo Haselhoff, Salman Ahmed

и другие.

Journal of Urban Health, Год журнала: 2023, Номер 100(1), С. 40 - 50

Опубликована: Янв. 12, 2023

COVID-19-related health outcomes displayed distinct geographical patterns within countries. The transmission of SARS-CoV-2 requires close spatial proximity people, which can be influenced by the built environment. Only few studies have analysed infections related to environment urban areas at a high resolution. This study examined association between factors and in metropolitan area Germany. Polymerase chain reaction (PCR)-confirmed 7866 citizens Essen March 2020 May 2021 were analysed, aggregated neighbourhood level. We performed regression analyses investigate associations cumulative number per 1000 inhabitants (cum. infections) up 31.05.2021 factors. cum. neighbourhoods (median: 11.5, IQR: 8.1-16.9) followed marked socially determined north-south gradient. effect estimates adjusted models showed negative with greenness, i.e. normalized difference vegetation index (NDVI) (adjusted β = - 35.36, 95% CI: 57.68; 13.04), rooms person (- 10.40, 13.79; 7.01), living space 0.51, 0.66; 0.36), residential 0.07, 0.16; 0.01) commercial 0.15, 0.25; 0.05). Residential multi-storey buildings 0.03, 0.12; 0.06) green (0.03, 0.05; 0.11) did not show substantial association. Our results suggest that matters for spread infections, such as more spacious apartments or higher levels greenness are associated lower infection rates unequal intra-urban distribution these emphasizes prevailing environmental inequalities regarding COVID-19 pandemic.

Язык: Английский

Процитировано

17

County-Level Social Vulnerability is Associated With In-Hospital Death and Major Adverse Cardiovascular Events in Patients Hospitalized With COVID-19: An Analysis of the American Heart Association COVID-19 Cardiovascular Disease Registry DOI
Shabatun Islam, Gargya Malla, Robert W. Yeh

и другие.

Circulation Cardiovascular Quality and Outcomes, Год журнала: 2022, Номер 15(8)

Опубликована: Июль 18, 2022

Background: The COVID-19 pandemic has disproportionately affected low-income and racial/ethnic minority populations in the United States. However, it is unknown whether hospitalized patients with from socially vulnerable communities experience higher rates of death and/or major adverse cardiovascular events (MACEs). Thus, we evaluated association between county-level social vulnerability in-hospital mortality MACE a national cohort patients. Methods: Our study population included American Heart Association Cardiovascular Disease Registry across 107 US hospitals January 14, 2020 to November 30, 2020. Social Vulnerability Index (SVI), composite measure community developed by Centers for Control Prevention, was used classify patients’ place residence. We fit hierarchical logistic regression model hospital-level random intercepts evaluate SVI MACE. Results: Among 16 939 registry, 5065 (29.9%) resided most (highest quartile SVI). Compared those lowest SVI, highest were younger (age 60.2 versus 62.3 years) more likely be Black adults (36.7% 12.2%) Medicaid-insured (31.1% 23.0%). After adjustment demographics (age, sex, race/ethnicity) insurance status, (compared lowest) associated likelihood (OR, 1.25 [1.03–1.53]; P =0.03) 1.26 [95% CI, 1.05–1.50]; =0.01). These findings not attenuated after accounting clinical comorbidities acuity illness on admission. Conclusions: Patients residing experienced MACE, independent race, ethnicity, several factors. Clinical health system strategies are needed improve outcomes

Язык: Английский

Процитировано

24

The Association Between Neighborhood Social Vulnerability and COVID-19 Testing, Positivity, and Incidence in Alabama and Louisiana DOI Creative Commons
Gabriela R. Oates, Lucia Juarez, Ronald Horswell

и другие.

Journal of Community Health, Год журнала: 2021, Номер 46(6), С. 1115 - 1123

Опубликована: Май 9, 2021

Язык: Английский

Процитировано

30

Spatiotemporal Associations Between Social Vulnerability, Environmental Measurements, and COVID‐19 in the Conterminous United States DOI Creative Commons
Daniel P. Johnson, Niranjan Ravi, Christian Braneon

и другие.

GeoHealth, Год журнала: 2021, Номер 5(8)

Опубликована: Июль 21, 2021

This study summarizes the results from fitting a Bayesian hierarchical spatiotemporal model to coronavirus disease 2019 (COVID-19) cases and deaths at county level in United States for year 2020. Two models were created, one deaths, utilizing scaled Besag, York, Mollié with Type I spatial-temporal interaction. Each accounts 16 social vulnerability 7 environmental variables as fixed effects. The spatial pattern between COVID-19 is significantly different many ways. trend of pandemic illustrates shift out major metropolitan areas into Southeast Southwest during summer months upper Midwest beginning autumn. Analysis predictors infection death found that counties higher percentages those not having high school diploma, non-White status being Age 65 over be significant. Among variables, above ground temperature had strongest effect on relative risk both deaths. Hot cold spots, statistically significant low respectively, derived convolutional show probability average have Social Vulnerability Index composite scores. same analysis interaction term exemplifies more complex relationship vulnerability, measurements, cases,

Язык: Английский

Процитировано

29

Pre-COVID-19 Social Determinants of Health Among Mexican Migrants in Los Angeles and New York City and Their Increased Vulnerability to Unfavorable Health Outcomes During the COVID-19 Pandemic DOI Creative Commons
Mireya Vilar‐Compte,

Pablo Gaitán‐Rossi,

Lucía Félix‐Beltrán

и другие.

Journal of Immigrant and Minority Health, Год журнала: 2021, Номер 24(1), С. 65 - 77

Опубликована: Окт. 1, 2021

Язык: Английский

Процитировано

29

A Review of Bayesian Spatiotemporal Models in Spatial Epidemiology DOI Creative Commons
Yufeng Wang, Xue Chen, Feng Xue

и другие.

ISPRS International Journal of Geo-Information, Год журнала: 2024, Номер 13(3), С. 97 - 97

Опубликована: Март 18, 2024

Spatial epidemiology investigates the patterns and determinants of health outcomes over both space time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity incorporate spatial temporal dependencies, uncertainties, intricate interactions. However, complexity modelling computations associated with vary across different diseases. Presently, there is a limited comprehensive overview applications in epidemiology. This article aims address gap through thorough review. The review commences by delving into historical development concerning disease mapping, prediction, regression analysis. Subsequently, compares these terms data distribution, general models, environmental covariates, parameter estimation methods, model fitting standards. Following this, essential preparatory processes are outlined, encompassing acquisition, preprocessing, available statistical software. further categorizes summarizes application Lastly, critical examination advantages disadvantages along considerations for application, provided. enhance comprehension dynamic distribution prediction epidemics. By facilitating effective scrutiny, especially context global COVID-19 pandemic, holds significant academic merit practical value. It also contribute improved ecological epidemiological prevention control strategies.

Язык: Английский

Процитировано

5

Social Vulnerability and Location of Death in Heart Failure in the United States DOI
Richard Pham, Eiran Z. Gorodeski, Sadeer Al‐Kindi

и другие.

Current Problems in Cardiology, Год журнала: 2023, Номер 48(7), С. 101689 - 101689

Опубликована: Март 9, 2023

Язык: Английский

Процитировано

11

Social determinants of health and disparate disability accumulation in a cohort of Black, Hispanic, and White patients with multiple sclerosis DOI Creative Commons
Christopher Orlando, Carlos A. Pérez,

Paunel Agyei

и другие.

Multiple Sclerosis Journal, Год журнала: 2023, Номер 29(10), С. 1304 - 1315

Опубликована: Июль 12, 2023

Black and Hispanic patients with multiple sclerosis (MS) have been shown to accumulate greater sclerosis-associated disability (MSAD) than White patients. Disparities in social determinants of health (SDOH) among these groups also reported.To determine the extent which associations race ethnicity MSAD may be attributable differences SDOH.Retrospective chart analysis at an academic MS center grouped by self-identified (n = 95), 93), 98) race/ethnicity. Individual patient addresses were geocoded matched neighborhood-level area deprivation index (ADI) vulnerability (SVI).Average Expanded Disability Status Scale (EDSS) scores last-recorded evaluations (1.7 ± 2.0) significantly lower (2.8 2.4, p 0.001) (2.6 2.6, 0.020) Neither nor was associated EDSS multivariable linear regression models that included individual-level SDOH indicators either ADI or SVI.Black are not include individual indicators. Further research should elucidate mechanisms structural inequities affect disease course.

Язык: Английский

Процитировано

10

The association of the four social vulnerability themes and COVID-19 mortality rates in U.S. Counties DOI
Baksun Sung

International Journal of Environmental Health Research, Год журнала: 2025, Номер unknown, С. 1 - 10

Опубликована: Янв. 20, 2025

The purpose of this study was to examine the relationship between social vulnerability and COVID-19 mortality rates during whole outbreak in U.S. counties. deaths were gleaned from USA Facts. Independent variables CDC's Social Vulnerability Index. Spatial autoregressive models used for data analysis. Results show that counties with more (socioeconomic) positively associated higher rates. Counties (household composition & disability) (minority status language) negatively (housing type transportation) In conclusion, county-level provides an useful framework identifying unequal distribution United States.

Язык: Английский

Процитировано

0