Socio-economic disparities and COVID-19 in the USA

Paul, Ayan; Englert, Philipp; Varga, Melinda

doi:10.1088/2632-072x/ac0fc7

Cited by 30 publications

(32 citation statements)

References 26 publications

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“…Similar to the first wave, there was no pronounced urban/high density gradient or gradient associated with the connectedness of a region [8]. Population density per se did not appear to be a risk factor, which is supported by a regional analysis of COVID-19 prevalence in the United States [63] and Germany [9]. Cities have both the healthiest and unhealthiest populations.…”

Section: Urbanity/rurality and Connectednessmentioning

confidence: 73%

Regional Characteristics of the Second Wave of SARS-CoV-2 Infections and COVID-19 Deaths in Germany

Doblhammer

Kreft

Reinke

2021

IJERPH

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(1) Background: In the absence of individual level information, the aim of this study was to identify the regional key features explaining SARS-CoV-2 infections and COVID-19 deaths during the upswing of the second wave in Germany. (2) Methods: We used COVID-19 diagnoses and deaths from 1 October to 15 December 2020, on the county-level, differentiating five two-week time periods. For each period, we calculated the age-standardized COVID-19 incidence and death rates on the county level. We trained gradient boosting models to predict the incidence and death rates by 155 indicators and identified the top 20 associations using Shap values. (3) Results: Counties with low socioeconomic status (SES) had higher infection and death rates, as had those with high international migration, a high proportion of foreigners, and a large nursing home population. The importance of these characteristics changed over time. During the period of intense exponential increase in infections, the proportion of the population that voted for the Alternative for Germany (AfD) party in the last federal election was among the top characteristics correlated with high incidence and death rates. (4) Machine learning approaches can reveal regional characteristics that are associated with high rates of infection and mortality.

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Section: Urbanity/rurality and Connectednessmentioning

confidence: 73%

Regional Characteristics of the Second Wave of SARS-CoV-2 Infections and COVID-19 Deaths in Germany

Doblhammer

Kreft

Reinke

2021

IJERPH

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“…Local population dynamics and sociodemographic characteristics have proven influential on the prevalence of coronavirus disease 2019 (COVID-19) impacts and transmissibility. However, early mitigation measures did not account for place-based differences in exposure and outcomes at comparative and more localized spatial scales [1]. Unprecedented United States government mitigative policies led to drastic unemployment increases to prevent the spread of COVID-19, which did not occur equally across the country [2].…”

Section: Introductionmentioning

confidence: 99%

Spatial Disparities of COVID-19 Cases and Fatalities in United States Counties

Jackson

Derakhshan

Blackwood

et al. 2021

IJERPH

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This paper examines the spatial and temporal trends in county-level COVID-19 cases and fatalities in the United States during the first year of the pandemic (January 2020–January 2021). Statistical and geospatial analyses highlight greater impacts in the Great Plains, Southwestern and Southern regions based on cases and fatalities per 100,000 population. Significant case and fatality spatial clusters were most prevalent between November 2020 and January 2021. Distinct urban–rural differences in COVID-19 experiences uncovered higher rural cases and fatalities per 100,000 population and fewer government mitigation actions enacted in rural counties. High levels of social vulnerability and the absence of mitigation policies were significantly associated with higher fatalities, while existing community resilience had more influential spatial explanatory power. Using differences in percentage unemployment changes between 2019 and 2020 as a proxy for pre-emergent recovery revealed urban counties were hit harder in the early months of the pandemic, corresponding with imposed government mitigation policies. This longitudinal, place-based study confirms some early urban–rural patterns initially observed in the pandemic, as well as the disparate COVID-19 experiences among socially vulnerable populations. The results are critical in identifying geographic disparities in COVID-19 exposures and outcomes and providing the evidentiary basis for targeting pandemic recovery.

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“…Ref. [11] study the spread of COVID-19 at the county level for the United States using data from the US Census Bureau and find that the prevalence of the disease and the death rate are correlated with the local socio-economic conditions.…”

Section: Motivation and Literature Reviewmentioning

confidence: 99%

Impact of Economic Factors and Policy Interventions on the COVID-19 Pandemic

Kapri

2021

Sustainability

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This paper studies how policy interventions and economic factors affect COVID-19 infections and deaths, using generalized linear regression (GLM) models. We seek to explain the containment differences by countries’ inherent economic factors, especially the labor market structure, utilizing data from multiple sources. The results show that countries heavily relying on the service sector and international trade suffer more from the spreading, possibly due to the fact that COVID-19 is a communicable disease and spreads quickly through physical contact. Further, we find that these countries could benefit more from stringent policies compared to others.

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Socio-economic disparities and COVID-19 in the USA

Cited by 30 publications

References 26 publications

Regional Characteristics of the Second Wave of SARS-CoV-2 Infections and COVID-19 Deaths in Germany

Regional Characteristics of the Second Wave of SARS-CoV-2 Infections and COVID-19 Deaths in Germany

Spatial Disparities of COVID-19 Cases and Fatalities in United States Counties

Impact of Economic Factors and Policy Interventions on the COVID-19 Pandemic

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