We characterized vulnerable populations located in areas at higher risk of COVID-19-related mortality and low critical healthcare capacity during the early stage of the epidemic in the United States. We analyze data obtained from a Johns Hopkins University COVID-19 database to assess the county-level spatial variation of COVID-19-related mortality risk during the early stage of the epidemic in relation to health determinants and health infrastructure. Overall, we identified highly populated and polluted areas, regional air hub areas, race minorities (non-white population), and Hispanic or Latino population with an increased risk of COVID-19-related death during the first phase of the epidemic. The 10 highest COVID-19 mortality risk areas in highly populated counties had on average a lower proportion of white population (48.0%) and higher proportions of black population (18.7%) and other races (33.3%) compared to the national averages of 83.0%, 9.1%, and 7.9%, respectively. The Hispanic and Latino population proportion was higher in these 10 counties (29.3%, compared to the national average of 9.3%). Counties with major air hubs had a 31% increase in mortality risk compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19-related mortality risk also had lower critical care capacity than the national average. The disparity in health and environmental risk factors might have exacerbated the COVID-19-related mortality risk in vulnerable groups during the early stage of the epidemic.

Background: The role of health-related disparities including sociodemographic, environmental, and critical care capacity in the COVID-19 pandemic are poorly understood. In the present study, we characterized vulnerable populations located in areas at higher risk of COVID-19 related mortality and low critical healthcare capacity in the U.S. Methods: Using Bayesian multilevel analysis and small area disease risk mapping, we assessed the spatial variation of COVID-19 related mortality risk for the U.S. in relation with healthcare disparities including race, ethnicity, poverty, air quality, and critical healthcare capacity. Results: Overall, highly populated, regional air hub areas, and minorities had an increased risk of COVID-19 related mortality. We found that with an increase of only 1 ug/m3 in long term PM2.5 exposure, the COVID-19 mortality rate increased by 13%. Counties with major air hubs had 18% increase in COVID-19 related death compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19 related mortality risk were also counties with lower critical care capacity than national average. These counties were primary located at the North- and South-Eastern regions of the country. Conclusion: The existing disparity in health and environmental risk factors that exacerbate the COVID-19 related mortality, along with the regional healthcare capacity, determine the vulnerability of populations to COVID-19 related mortality. The results from this study can be used to guide the development of strategies for the identification and targeting preventive strategies in vulnerable populations with a higher proportion of minority groups living in areas with poor air quality and low healthcare capacity. KEY POINTS: Question: What are the sociodemographic and environmental drivers of the heterogeneous distribution of the COVID-19 related mortality in the U.S., and what are the vulnerable areas at higher risk of COVID-19 related mortality and low critical healthcare capacity? Findings: Higher proportions of African American and Latino populations, as well as high levels of air pollution and airport connectivity were linked to higher risk of COVID-19 related mortality. Over 68% of the counties with high COVID-19 related mortality risk were also counties with lower critical care capacity than national average. Meaning: In a time-limited response, the identification and targeting prevention efforts should focus in vulnerable populations located in high risk areas in which sociodemographic and environmental factors are exacerbating the burden of COVID-19 related deaths.

Background: This study addresses the limited research on racial disparities in asthma hospitalization outcomes, specifically length of stay (LOS) and readmission, across the U.S. Methods: We analyzed in-patient and emergency department visits from the All of Us Research Program, identifying various risk factors (demographic, comorbid, temporal, and place-based) associated with asthma LOS and 30-day readmission using Bayesian mixed-effects models. Results: Of 17,233 patients (48.0% White, 30.7% Black, 19.7% Hispanic/Latino, 1.3% Asian, and 0.3% Middle Eastern and North African) with 82,188 asthma visits, Black participants had 20% shorter LOS and 12% higher odds of readmission, compared to White participants in multivariate analyses. Public-insured patients had 14% longer LOS and 39% higher readmission odds than commercially insured patients. Weekend admissions resulted in a 12% shorter LOS but 10% higher readmission odds. Asthmatics with chronic diseases had a longer LOS (range: 6–39%) and higher readmission odds (range: 9–32%) except for those with allergic rhinitis, who had a 23% shorter LOS. Conclusions: A comprehensive understanding of the factors influencing asthma hospitalization, in conjunction with diverse datasets and clinical-community partnerships, can help physicians and policymakers to systematically address racial disparities, healthcare utilization and equitable outcomes in asthma care.

Background: The novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic. Methods: This study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe. Findings: We found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data. Interpretation: Physical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions. RESEARCH IN CONTEXT: Evidence before this study: The SARS-CoV-2 is a new virus identified in December 2019 in the province of Wuhan, China and as never before, a remarkable number of studies and reports have been released since the start of the pandemic. Several studies have used confirmed COVID-19 cases to estimate the growth rate of the pandemic. However, many studies have discussed limitations of including only confirmed cases attributable to the lack of information about testing protocols and testing rates among different countries. Finally, some researchers proposed the analysis of reported deaths by COVID-19 as a potential solution. However, this metric results in biased estimates because deaths by COVID-19 are known to be underreported. Added value of this study: We designed and implemented analytic methods based on our previous research applied to different infectious disease epidemics, to add evidence related to the impact of non-pharmaceutical containment strategies on the temporal progression of the COVID-19 pandemic. Specifically, this study adds quantitative evidence about the effects of physical distance measures on limiting the propagation of COVID-19 pandemics in different countries. Additionally, we included testing data in the analysis to assess intra- and inter-country variation in testing growth rates. We hypothesized that the test-positivity rate is an approximation to the incidence of the COVID-19 pandemics in countries with high testing rates. Additionally, we hypothesize that a significant decrease in the pandemic over time could be identified by a significant decrease in the confirmed cases along with a significant decrease in the test-positivity rate. Our results quantified the potential effects of physical distance interventions on the COVID-19 pandemic progression under different levels of testing and enforcement of mitigation policies. Implications of all the available evidence: Our analysis could lead to better approaches for estimating the effects of physical distance measures on the time course of infectious diseases. In addition, our analysis highlights the potential bias of estimated COVID-19 growth rates based only on confirmed cases. The results from our study could inform strategies for mitigating the COVID-19 or other future pandemics, especially in countries in an earlier stage of a pandemic.

Rationale: Previous studies have identified risk factors for coronavirus disease (COVID-19) hospitalization in children. However, these studies have been limited in their ability to disentangle the contribution of racial disparities, allergic comorbidities, and environmental exposures to the development of severe COVID-19 in at-risk children with allergies. Objectives: To examine racial and ethnic disparities in COVID-19 hospitalization and their links to potentially underlying allergic comorbidities and individual and place-based factors in children with allergies. Methods: This is an electronic health record-based retrospective study of children in 2020. The outcome was COVID-19 hospitalization categorized as no hospital care for patients with asymptomatic/mild illness, short stay for patients admitted and discharged within 24 hours, and prolonged stay for patients requiring additional time to discharge (more than 24 h). Mixed-effects and mediation models were used to determine relationships among independent variables, mediators, and COVID-19 hospitalization. Results: Among the 5,258 children with COVID-19 positive test or diagnosis, 10% required a short stay, and 3.7% required a prolonged stay. Black and Hispanic children had higher odds of longer stays than non-Hispanic White children (both P < 0.001). Children with obesity and eosinophilic esophagitis diagnoses had higher odds of short and prolonged stay (all P < 0.05). Area-level deprivation was associated with short stay (adjusted odds ratio [AOR], 15.49; 95% confidence interval [CI], 5.16–45.47 for every 0.1-unit increase) and prolonged stay (AOR, 11.82; 95% CI, 2.25–62.01 for every 0.1-unit increase). Associations between race/ethnicity and COVID-19 hospitalization were primarily mediated by insurance and area-level deprivation, altogether accounting for 99% of the variation in COVID-19 hospitalization. Conclusions: There were racial and ethnic differences in children with allergies and individual and place-based factors related to COVID-19 hospitalization. Differences were primarily mediated by insurance and area-level deprivation, altogether accounting for 99% of the variation in COVID-19 hospitalization. A better understanding of COVID-related morbidity in children and the link to place-based factors is key to developing prevention strategies capable of equitably improving outcomes.