Geographic disparities in COVID-19 infections and deaths: The role of transportation.
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ABSTRACT:
SUBMITTER: Gaskin DJ
PROVIDER: S-EPMC7714661 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
Geographic disparities in COVID-19 infections and deaths: The role of transportation.
Gaskin Darrell J DJ Zare Hossein H Delarmente Benjo A BA
Transport policy 20201204
The US government imposed two travel restriction policies to prevent the spread of the COVID-19 but may have funneled asymptomatic air travelers to selected major airports and transportation hubs. Using the most recent JHU COVID-19 database, American Community Survey, Airport and Amtrak data form Bureau of Transportation Statistics from 3132 US counties we ran negative binomial regressions and Cox regression models to explore the associations between COVID-19 cases and death rates and proximity ...[more]
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Project description:Background/objectivesTo determine racial/ethnic disparities in weekly counts of new COVID-19 cases and deaths among nursing home residents or staff.DesignCross-sectional analysis of national nursing home COVID-19 reports linked to other data. Multivariable two-part models modeled disparities in count of cases or deaths, and logistic regressions modeled disparities in self-reported shortages in staff and personal protective equipment (PPE), across nursing home groups with varying proportions of racial/ethnic minority residents, defined as low-, medium-, medium-high-, and high-proportion groups.SettingA total of 12,576 nursing homes nationally.ParticipantsNone.InterventionNone.MeasurementsNumbers of incident COVID-19 confirmed cases among residents and staff, and incident COVID-19 related deaths among residents (primary outcomes); and nursing home reported shortages in staff and PPE (secondary outcomes). All outcomes were reported for the week of May 25, 2020.ResultsThe number of weekly new COVID-19 confirmed cases among residents ranged from an average of 0.4 cases per facility (standard deviation (SD) = 2.5) for the low-proportion group (93.0% had zero new cases) to 1.5 cases per facility (SD = 6.3) for the high-proportion group (78.9% had zero new cases). Multivariable regression estimated that compared with the low-proportion group, the likelihood of having at least one new resident case was 76% higher (odds ratio = 1.76; 95% confidence interval = 1.38-2.25; P = .000) for the high-proportion group. Similar across-facility disparities were found for the weekly count of new COVID-19 deaths among residents (ranging from 0.1 deaths per facility (SD = 1.1) for the low-proportion group to 0.4 deaths (SD = 2.0) for the high-proportion group) and in the weekly count of new COVID-19 confirmed cases among staff (ranging from 0.3 cases (SD = 1.4] to 1.3 cases (SD = 4.4) per facility). No substantial disparities in self-reported shortages of staff or PPE were found.ConclusionNursing homes caring for disproportionately more racial/ethnic minority residents reported more weekly new COVID-19 confirmed cases and/or deaths. Immediate actions are needed to address these system-level disparities.
| S-EPMC7537079 | biostudies-literature
Project description:BackgroundData suggest that the effects of coronavirus disease 2019 (COVID-19) differ among U.S. racial/ethnic groups.PurposeTo evaluate racial/ethnic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and COVID-19 outcomes, factors contributing to disparities, and interventions to reduce them. (PROSPERO: CRD42020187078).Data sourcesEnglish-language articles in MEDLINE, PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus, searched from inception through 31 August 2020. Gray literature sources were searched through 2 November 2020.Study selectionObservational studies examining SARS-CoV-2 infections, hospitalizations, or deaths by race/ethnicity in U.S. settings.Data extractionSingle-reviewer abstraction confirmed by a second reviewer; independent dual-reviewer assessment of quality and strength of evidence.Data synthesis37 mostly fair-quality cohort and cross-sectional studies, 15 mostly good-quality ecological studies, and data from the Centers for Disease Control and Prevention and APM Research Lab were included. African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection, hospitalization, and COVID-19-related mortality compared with non-Hispanic White populations, but not higher case-fatality rates (mostly reported as in-hospital mortality) (moderate- to high-strength evidence). Asian populations experience similar outcomes to non-Hispanic White populations (low-strength evidence). Outcomes for other racial/ethnic groups have been insufficiently studied. Health care access and exposure factors may underlie the observed disparities more than susceptibility due to comorbid conditions (low-strength evidence).LimitationsSelection bias, missing race/ethnicity data, and incomplete outcome assessments in cohort and cross-sectional studies must be considered. In addition, adjustment for key demographic covariates was lacking in ecological studies.ConclusionAfrican American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection and COVID-19-related mortality but similar rates of case fatality. Differences in health care access and exposure risk may be driving higher infection and mortality rates.Primary funding sourceDepartment of Veterans Affairs, Veterans Health Administration, Health Services Research & Development.
| S-EPMC7772883 | biostudies-literature
Project description:BackgroundUnderstanding geographic disparities in Coronavirus Disease 2019 (COVID-19) testing and outcomes at the local level during the early stages of the pandemic can guide policies, inform allocation of control and prevention resources, and provide valuable baseline data to evaluate the effectiveness of interventions for mitigating health, economic and social impacts. Therefore, the objective of this study was to identify geographic disparities in COVID-19 testing, incidence, hospitalizations, and deaths during the first five months of the pandemic in Florida. METHODS: Florida county-level COVID-19 data for the time period March-July 2020 were used to compute various COVID-19 metrics including testing rates, positivity rates, incidence risks, percent of hospitalized cases, hospitalization risks, case-fatality rates, and mortality risks. High or low risk clusters were identified using either Kulldorff's circular spatial scan statistics or Tango's flexible spatial scan statistics and their locations were visually displayed using QGIS.ResultsVisual examination of spatial patterns showed high estimates of all COVID-19 metrics for Southern Florida. Similar to the spatial patterns, high-risk clusters for testing and positivity rates and all COVID-19 outcomes (i.e. hospitalizations and deaths) were concentrated in Southern Florida. The distributions of these metrics in the other parts of Florida were more heterogeneous. For instance, testing rates for parts of Northwest Florida were well below the state median (11,697 tests/100,000 persons) but they were above the state median for North Central Florida. The incidence risks for Northwest Florida were equal to or above the state median incidence risk (878 cases/100,000 persons), but the converse was true for parts of North Central Florida. Consequently, a cluster of high testing rates was identified in North Central Florida, while a cluster of low testing rate and 1-3 clusters of high incidence risks, percent of hospitalized cases, hospitalization risks, and case fatality rates were identified in Northwest Florida. Central Florida had low-rate clusters of testing and positivity rates but it had a high-risk cluster of percent of hospitalized cases.ConclusionsSubstantial disparities in the spatial distribution of COVID-19 outcomes and testing and positivity rates exist in Florida, with Southern Florida counties generally having higher testing and positivity rates and more severe outcomes (i.e. hospitalizations and deaths) compared to Northern Florida. These findings provide valuable baseline data that is useful for assessing the effectiveness of preventive interventions, such as vaccinations, in various geographic locations in the state. Future studies will need to assess changes in spatial patterns over time at lower geographical scales and determinants of any identified patterns.
| S-EPMC9832260 | biostudies-literature
Project description:The authors examine how two state-level coronavirus disease 2019 (COVID-19) policy indices (one capturing economic support and one capturing stringency measures such as stay-at-home orders) were associated with county-level COVID-19 mortality from April through December 2020 and whether the policies were more beneficial for certain counties. Using multilevel negative binominal regression models, the authors found that high scores on both policy indices were associated with lower county-level COVID-19 mortality. However, the policies appeared to be most beneficial for counties with fewer physicians and larger shares of older adults, low-educated residents, and Trump voters. They appeared to be less effective in counties with larger shares of non-Hispanic Black and Hispanic residents. These findings underscore the importance of examining how state and local factors jointly shape COVID-19 mortality and indicate that the unequal benefits of pandemic policies may have contributed to county-level disparities in COVID-19 mortality.
| S-EPMC9902801 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has shown a continuously increasing trend with a large variation in the number of COVID-19 deaths across countries. In response, many countries have implemented non pharmaceutical methods of intervention, such as social distancing and lockdowns. This study aims to investigate the relationship of four dimensions of social capital (community attachment, social trust, family bond, and security) and several control variables with COVID-19 deaths.MethodsWe retrieved data from open access databases and a survey. COVID-19 death-related data were collected from the website "Centre for Systems Science and Engineering (CSSE) at Johns Hopkins University". Social capital-related data were collected from a large-scale survey that included web-based and face-to-face surveys covering 100,956 respondents across all regions/provinces/states of 37 countries in 2017. Data regarding population density, number of hospital beds, and population aged 65 or older were retrieved from the World Development Indicators (WDIs). Data on country lockdowns were obtained from the website "National responses to the 2019-20 coronavirus pandemic". Linear regressions were applied to identify the relationship between social capital and COVID-19 deaths.ResultsWe found that COVID-19 deaths were associated with social capital both positively and negatively. Community attachment and social trust were associated with more COVID-19 deaths, and family bond and security were associated with fewer deaths. COVID-19 deaths were positively associated with population density, ageing population, and interactions between four dimensions of social capital-related factors and the ageing population. Furthermore, the number of hospital beds and early lockdown policy were negatively associated with COVID-19 deaths.ConclusionsThe results indicate that the role of social capital in dynamically evolving threats, such as the current COVID-19 pandemic, is not always negative or positive. Therefore, people's behaviour should be changed to support countries' response to the COVID-19 threat.
| S-EPMC7928173 | biostudies-literature
Project description:BackgroundThe actual human cost of the pandemic cannot be viewed through the COVID-19 mortality rates alone, especially when the pandemic is widening the existing health disparities among different subpopulations within the same society. In Kuwait, migrant workers were already disproportionately impacted by COVID-19 and its unintended consequences. The totality of that effect on mortality is yet to be fully understood.ObjectiveTo estimate excess deaths in the pandemic year of 2020 among the Kuwaiti and non-Kuwaiti migrant populations.MethodsWe analyzed publicly available retrospective data in Kuwait on total annual mortality historically (from 2005 to 2019) and in 2020. We fitted a quasi-poisson generalized linear model adjusted for yearly trend and nationality to estimate the expected deaths in 2020 in the absence of the pandemic. We calculated excess deaths as the difference between observed and expected mortality for the year of the pandemic in both Kuwaitis and non-Kuwaitis.ResultsIn the absence of the pandemic, we expected the total mortality in Kuwait to be 6629 (95% CI: 6472 to 6789) deaths. However, the observed total mortality in 2020 was 9975 deaths; about 3346 (3186 to 3503) more deaths above the expected historical trend. Deaths among migrant workers would have been approximately 71.9% (67.8 to 76.0) lower in the absence of the pandemic. On the other hand, deaths among Kuwaitis would have been 32.4% (29.3 to 35.6) lower if the country had not been hit by the pandemic.ConclusionThe burden of mortality brought on by the COVID-19 pandemic is substantially higher than what the official tally might suggest. Systematically disadvantaged migrant workers shouldered a larger burden of deaths in the pandemic year. Public health interventions must consider structural and societal determinants that give rise to the health disparities seen among migrant workers.
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Project description:Aim Racial disparities in COVID-19 death rates have largely been driven by structural racism in health, housing, and labor systems that place Black, Brown, and Indigenous populations at greater risk for COVID-19 exposure, transmission, and severe illness, compared to non-Hispanic White populations. Here we examine the association between taxable property values per capita, an indicator influenced by historical and contemporary housing policies that have disproportionately impacted people of color, and COVID-19 deaths. Methods Taxable values serve as a proxy for fiscal health providing insight on the county’s ability to address imminent needs, including COVID-19 responses. Therefore, higher taxable values indicate local governments that are better equipped to deliver these public services. We used county-level data from the American Community Survey, the Michigan Community Financial Dashboard, The Atlantic’s COVID Tracking Project, and the Community Health Rankings and Roadmap for this cross-sectional study. Maps were created to examine the geographic distribution of cumulative death rates and taxable values per capita, and regression models were used to examine the association between the two while controlling for population density, age, education, race, income, obesity, diabetes, and smoking rates. Results Seventy-five counties were included. The mean taxable value per capita was $43,764.50 and the mean cumulative death rate was 171.86. Findings from the regression analysis showed that counties with higher taxable values were associated with lower COVID-19 death rates (B = –2.45, P < 0.001) Conclusion Our findings reveal a need to reevaluate current policies surrounding taxable property values in the state of Michigan, not solely for their inequitable impact on local governments' financial solvency and service quality, but also for their negative consequences for population health and racial health equity. Supplementary Information The online version contains supplementary material available at 10.1007/s10389-022-01817-w.
| S-EPMC9818051 | biostudies-literature
Project description:ObjectivesTo evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes COVID-19.MethodsWe created an agent-based stochastic network simulation using a variant of the standard SEIR dynamic infectious disease model. We considered a mask order that was initiated 3.5 months after the first confirmed COVID-19 case. We varied the likelihood of individuals wearing masks from 0-100% in steps of 20% (mask adherence) and considered 25% to 90% mask-related reduction in viral transmission (mask efficacy). Sensitivity analyses assessed early (by week 13) versus late (by week 42) adoption of masks and geographic differences in adherence (highest in urban and lowest in rural areas).ResultsIntroduction of mask use with 50% efficacy worn by 50% of individuals reduces the cumulative infection attack rate (IAR) by 27%, the peak prevalence by 49%, and population-wide mortality by 29%. If 90% of individuals wear 50% efficacious masks, this decreases IAR by 54%, peak prevalence by 75%, and population-wide mortality by 55%; similar improvements hold if 70% of individuals wear 75% efficacious masks. Late adoption reduces IAR and deaths by 18% or more compared to no adoption. Lower adoption in rural areas than urban would lead to rural areas having the highest IAR.ConclusionsEven after community transmission of SARS-CoV-2 has been established, adoption of mask-wearing by a majority of community-dwelling individuals can meaningfully reduce the number and outcome of COVID-19 infections over and above physical distancing interventions.HighlightsThis paper shows the impact of widespread adoption of masks in response to the COVID-19 pandemic, with varying levels of population adherence, mask efficacy, and timing of mask adoption.The paper's findings help inform messaging to policymakers at the state or local level considering adding or keeping mask mandates, and to communities to promote widespread adoption of high-quality masks.Adoption of masks by at least half of the population can reduce cumulative infections and population deaths by more than 25%, while decreasing peak prevalence by about 50%. Even greater marginal improvements arise with adoption rates above 70%. The benefits of adopting high-quality masks is above that achieved by mobility changes and distancing alone.Rural and suburban areas are at higher relative risk than urban areas, due to less distancing and lower adoption of masks.
| S-EPMC7852241 | biostudies-literature
Project description:ObjectiveTo evaluate the race-stratified state-level prevalence of health determinants and the racial disparities in coronavirus disease 2019 (COVID-19) cumulative incidence and mortality in the United States.Patients and methodsThe age-adjusted race-stratified prevalence of comorbidities (hypertension, diabetes, dyslipidemia, and obesity), preexisting medical conditions (pulmonary disease, heart disease, stroke, kidney disease, and malignant neoplasm), poor health behaviors (smoking, alcohol abuse, and physical inactivity), and adverse socioeconomic factors (education, household income, and health insurance) was computed in 435,139 American adult participants from the 2017 Behavioral Risk Factor Surveillance System survey. Correlation was assessed between health determinants and the race-stratified COVID-19 crude mortality rate and infection-fatality ratio computed from respective state public health departments in 47 states.ResultsBlacks had a higher prevalence of comorbidities (63.3%; 95% CI, 62.4% to 64.2% vs 55.1%; 95% CI, 54.7% to 55.5%) and adverse socioeconomic factors (47.0%; 95% CI, 46.0% to 47.9% vs 30.9%; 95% CI, 30.6% to 31.3%) than did whites. The prevalence of preexisting medical conditions was similar in blacks (30.4%; 95% CI, 28.8% to 32.1%) and whites (30.8%; 95% CI, 30.2% to 31.4%). The prevalence of poor health behaviors was higher in whites (57.2%; 95% CI, 56.3% to 58.0%) than in blacks (50.2%; 95% CI,46.2% to 54.2%). Comorbidities and adverse socioeconomic factors were highest in the southern region, and poor health behaviors were highest in the western region. The cumulative incidence rate (per 100,000 persons) was 3-fold higher in blacks (1546.4) than in whites (540.4). The crude mortality rate (per 100,000 persons) was 2-fold higher in blacks (83.2) than in whites (33.2). However, the infection-fatality ratio (per 100 cases) was similar in whites (6.2) and blacks (5.4). Within racial groups, the geographic distribution of health determinants did not correlate with the state-level COVID-19 mortality and infection-fatality ratio (P>.05 for all).ConclusionRacial disparities in COVID-19 are largely driven by the higher cumulative incidence of infection in blacks. There is a discordance between the geographic dispersion of COVID-19 mortality and the regional distribution of health determinants.
| S-EPMC7538135 | biostudies-literature
Project description:As of mid-August 2020, Brazil was the country with the second-highest number of cases and deaths by the COVID-19 pandemic, but with large regional and social differences. In this study, using data from the Brazilian Ministry of Health, we analyze the spatial patterns of infection and mortality from Covid-19 across small areas of Brazil. We apply spatial autoregressive Bayesian models and estimate the risks of infection and mortality, taking into account age, sex composition of the population and other variables that describe the health situation of the spatial units. We also perform a decomposition analysis to study how age composition impacts the differences in mortality and infection rates across regions. Our results indicate that death and infections are spatially distributed, forming clusters and hotspots, especially in the Northern Amazon, Northeast coast and Southeast of the country. The high mortality risk in the Southeast part of the country, where the major cities are located, can be explained by the high proportion of the elderly in the population. In the less developed areas of the North and Northeast, there are high rates of infection among young adults, people of lower socioeconomic status, and people without access to health care, resulting in more deaths.
| S-EPMC7877657 | biostudies-literature