Racial Disparities in Coronavirus Disease 2019 (COVID-19) Mortality Are Driven by Unequal Infection Risks

A Socio-Ecological Approach to Addressing Digital Redlining in the United States: A Call to Action for Health Equity

Physical distancing requirements due to the coronavirus (COVID-19) pandemic has increased the need for broadband internet access. The World Health Organization defines social determinants of health as non-medical factors that impact health outcomes by affecting the conditions in which people are born, grow, work, live, and age. By this definition broadband internet access is a social determinant of health. Digital redlining-the systematic process by which specific groups are deprived of equal access to digital tools such as the internet-creates inequities in access to educational and employment opportunities, as well as healthcare and health information. Although it is known that internet service providers systematically exclude low-income communities from broadband service, little has been done to stop this discriminatory practice. In this paper, we seek to amplify the call to action against the practice of digital redlining in the United States, describe how it contributes to health disparities broadly and within the context of the COVID-19 pandemic, and use a socio-ecological framework to propose short- and long-term actions to address this inequity.

Racial and Ethnic Disparities in the Observed COVID-19 Case Fatality Rate Among the U.S. Population

Purpose

During the initial 12 months of the pandemic, racial and ethnic disparities in COVID-19 death rates received considerable attention but it has been unclear whether disparities in death rates were due to disparities in case fatality rates (CFRs), incidence rates or both. We examined differences in observed COVID-19 CFRs between U.S. White, Black/African American, and Latinx individuals during this period.

Methods

Using data from the COVID Tracking Project and the Centers for Disease Control and Prevention COVID-19 Case Surveillance Public Use dataset, we calculated CFR ratios comparing Black and Latinx to White individuals, both overall and separately by age group. We also used a model of monthly COVID-19 deaths to estimate CFR ratios, adjusting for age, gender, and differences across states and time.

Results

Overall Black and Latinx individuals had lower CFRs than their White counterparts. However, when adjusting for age, Black and Latinx had higher CFRs than White individuals among those younger than 65. CFRs varied substantially across states and time.

Conclusions

Disparities in COVID-19 case fatality among U.S. Black and Latinx individuals under age 65 were evident during the first year of the pandemic. Understanding racial and ethnic differences in COVID-19 CFRs is challenging due to limitations in available data.

Advanced age, comorbidity and the risk of mortality in COVID-19 infection

Background

Objective

Methods

Results

Conclusions

Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis synthesized the evidence on the impacts of demographics and comorbidities on the clinical outcomes of COVID-19, as well as the sources of the heterogeneity and publication bias of the relevant studies. Two authors independently searched the literature from PubMed, Embase, Cochrane library, and CINAHL on 18 May 2021; removed duplicates; screened the titles, abstracts, and full texts by using criteria; and extracted data from the eligible articles. The variations among the studies were examined by using Cochrane, Q.; I2, and meta-regression. Out of 11,975 articles that were obtained from the databases and screened, 559 studies were abstracted, and then, where appropriate, were analyzed by meta-analysis (n = 542). COVID-19-related severe illness, admission to the ICU, and death were significantly correlated with comorbidities, male sex, and an age older than 60 or 65 years, although high heterogeneity was present in the pooled estimates. The study design, the study country, the sample size, and the year of publication contributed to this. There was publication bias among the studies that compared the odds of COVID-19-related deaths, severe illness, and admission to the ICU on the basis of the comorbidity status. While an older age and chronic diseases were shown to increase the risk of developing severe illness, admission to the ICU, and death among the COVID-19 patients in our analysis, a marked heterogeneity was present when linking the specific risks with the outcomes.

Using sero-epidemiology to monitor disparities in vaccination and infection with SARS-CoV-2

As SARS-CoV-2 continues to spread and vaccines are rolled-out, the "double burden" of disparities in exposure and vaccination intersect to determine patterns of infection, immunity, and mortality. Serology provides a unique opportunity to measure prior infection and vaccination simultaneously. Leveraging algorithmically-selected residual sera from two hospital networks in the city of San Francisco, cross-sectional samples from 1,014 individuals from February 4-17, 2021 were each tested on two assays (Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 and Roche Elecsys Anti-SARS-CoV-2), capturing the first year of the epidemic and early roll-out of vaccination. We estimated, using Bayesian estimation of infection and vaccination, that infection risk of Hispanic/Latinx residents was five times greater than of White residents aged 18-64 (95% Credible Interval (CrI): 3.2-10.3), and that White residents over 65 were twice as likely to be vaccinated as Black/African American residents (95% CrI: 1.1-4.6). We found that socioeconomically-deprived zipcodes had higher infection probabilities and lower vaccination coverage than wealthier zipcodes. While vaccination has created a 'light at the end of the tunnel' for this pandemic, ongoing challenges in achieving and maintaining equity must also be considered.

Environmental Factors Influencing COVID-19 Incidence and Severity

Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.

Racial/ethnic and neighbourhood social vulnerability disparities in COVID-19 testing positivity, hospitalization, and in-hospital mortality in a large hospital system in Pennsylvania: A prospective study of electronic health records

Background

Disparities in COVID-19 mortality by race/ethnicity or neighborhood have been documented using surveillance data. We aimed to describe disparities by race/ethnicity and neighbourhood social vulnerability in COVID-19 positivity, hospitalization, and mortality.

Methods

We obtained data from the electronic health records of all individuals who tested positive for COVID-19 in the University of Pennsylvania Health System (UPHS) or were hospitalized with confirmed COVID-19 infection in five UPHS hospitals from March 1, 2020, to March 31, 2021. The main predictors were race/ethnicity and neighbourhood-level social vulnerability. The main outcomes were COVID-19 test positivity, hospitalization with COVID-19, and 30-day in-hospital mortality following hospitalization with COVID-19.

Findings

A total of 225,129 unique individuals received COVID-19 testing and 18,995 had a positive test result. A total of 5,794 unique patients were hospitalized with COVID-19 and 511 died in-hospital within 30 days. Racial/ethnic minority groups and residents of higher social vulnerability neighbourhoods had higher test positivity and risk of hospitalization. We did not see in-hospital mortality disparities during the first wave but observed 75% and 68% higher odds of death among Hispanic and Asians compared to Whites during subsequent waves.

Interpretation

We observed significant racial/ethnic and neighbourhood disparities in COVID-19 outcomes, especially test positivity and odds of hospitalization, highlighting the importance of equitably improving access to preventive measures to reduce SARS-CoV-2 infection, including reducing exposure to the virus and ensuring equity in vaccination.

Funding

National Institutes of Health.

Fair and diverse allocation of scarce resources

We aim to design a fairness-aware allocation approach to maximize the geographical diversity and avoid unfairness in the sense of demographic disparity. During the development of this work, the COVID-19 pandemic is still spreading in the U.S. and other parts of the world on large scale. Many poor communities and minority groups are much more vulnerable than the rest. To provide sufficient vaccine and medical resources to all residents and effectively stop the further spreading of the pandemic, the average medical resources per capita of a community should be independent of the community's demographic features but only conditional on the exposure rate to the disease. In this article, we integrate different aspects of resource allocation and create a synergistic intervention strategy that gives vulnerable populations higher priority in medical resource distribution. This prevention-centered strategy seeks a balance between geographical coverage and social group fairness. The proposed principle can be applied to other scarce resources and social benefits allocation.

Paediatric pneumonia research priorities in the context of COVID-19: A eDelphi study

Background

Pneumonia remains the leading cause of infectious deaths in children under-five globally. We update the research priorities for childhood pneumonia in the context of the COVID-19 pandemic and explore whether previous priorities have been addressed.

Methods

We conducted an eDelphi study from November 2019 to June 2021. Experts were invited to take part, targeting balance by: gender, profession, and high (HIC) and low- and middle-income countries (LMIC). We followed a three-stage approach: 1. Collating questions, using a list published in 2011 and adding newly posed topics; 2. Narrowing down, through participant scoring on importance and whether they had been answered; 3. Ranking of retained topics. Topics were categorized into: prevent and protect, diagnosis, treatment and cross-cutting.

Results

Overall 379 experts were identified, and 108 took part. We started with 83 topics, and 81 further general and 40 COVID-19 specific topics were proposed. In the final ranking 101 topics were retained, and the highest ranked was to "explore interventions to prevent neonatal pneumonia". Among the top 20 topics, epidemiological research and intervention evaluation was commonly prioritized, followed by the operational and implementation research. Two COVID-19 related questions were ranked within the top 20. There were clear differences in priorities between HIC and LMIC respondents, and academics vs non-academics.

Conclusions

Operational research on health system capacities, and evaluating optimized delivery of existing treatments, diagnostics and case management approaches are needed. This list should act as a catalyst for collaborative research, especially to meet the top priority in preventing neonatal pneumonia, and encourage multi-disciplinary partnerships.

Real-time pandemic surveillance using hospital admissions and mobility data

Forecasting COVID-19 healthcare demand has been hindered by poor data throughout the pandemic. We introduce a robust model for predicting COVID-19 transmission and hospitalizations based on COVID-19 hospital admissions and cell phone mobility data. This approach was developed by a municipal COVID-19 task force in Austin, TX, which includes civic leaders, public health officials, healthcare executives, and scientists. The model was incorporated into a dashboard providing daily healthcare forecasts that have raised public awareness, guided the city’s staged alert system to prevent unmanageable ICU surges, and triggered the launch of an alternative care site to accommodate hospital overflow.

Forecasting the burden of COVID-19 has been impeded by limitations in data, with case reporting biased by testing practices, death counts lagging far behind infections, and hospital census reflecting time-varying patient access, admission criteria, and demographics. Here, we show that hospital admissions coupled with mobility data can reliably predict severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission rates and healthcare demand. Using a forecasting model that has guided mitigation policies in Austin, TX, we estimate that the local reproduction number had an initial 7-d average of 5.8 (95% credible interval [CrI]: 3.6 to 7.9) and reached a low of 0.65 (95% CrI: 0.52 to 0.77) after the summer 2020 surge. Estimated case detection rates ranged from 17.2% (95% CrI: 11.8 to 22.1%) at the outset to a high of 70% (95% CrI: 64 to 80%) in January 2021, and infection prevalence remained above 0.1% between April 2020 and March 1, 2021, peaking at 0.8% (0.7-0.9%) in early January 2021. As precautionary behaviors increased safety in public spaces, the relationship between mobility and transmission weakened. We estimate that mobility-associated transmission was 62% (95% CrI: 52 to 68%) lower in February 2021 compared to March 2020. In a retrospective comparison, the 95% CrIs of our 1, 2, and 3 wk ahead forecasts contained 93.6%, 89.9%, and 87.7% of reported data, respectively. Developed by a task force including scientists, public health officials, policy makers, and hospital executives, this model can reliably project COVID-19 healthcare needs in US cities.

Structural racism and COVID-19 response: higher risk of exposure drives disparate COVID-19 deaths among Black and Hispanic/Latinx residents of Illinois, USA

Background

Structural racism has driven and continues to drive policies that create the social, economic, and community factors resulting in residential segregation, lack of access to adequate healthcare, and lack of employment opportunities that would allow economic mobility. This results in overall poorer population health for minoritized people. In 2020, Black and Hispanic/Latinx communities throughout the United States, including the state of Illinois, experienced disproportionately high rates of COVID-19 cases and deaths. Public health officials in Illinois implemented targeted programs at state and local levels to increase intervention access and reduce disparities.

Methods

To quantify how disparities in COVID outcomes evolved through the epidemic, data on SARS-CoV-2 diagnostic tests, COVID-19 cases, and COVID-19 deaths were obtained from the Illinois National Electronic Disease Surveillance System for the period from March 1 to December 31, 2020. Relative risks of COVID-19 cases and deaths were calculated for Black and Hispanic/Latinx vs. White residents, stratified by age group and epidemic interval. Deaths attributable to racial/ethnic disparities in incidence and case fatality were estimated with counterfactual simulations.

Results

Disparities in case and death rates became less drastic after May 2020, but did not disappear, and were more pronounced at younger ages. From March to May of 2020, the risk of a COVID-19 case for Black and Hispanic/Latinx populations was more than twice that of Whites across all age groups. The relative risk of COVID-19 death reached above 10 for Black and Hispanic/Latinx individuals under 50 years of age compared to age-matched Whites in the early epidemic. In all Illinois counties, relative risk of a COVID-19 case was the same or significantly increased for minoritized populations compared to the White population. 79.3 and 86.7% of disparities in deaths among Black and Hispanic/Latinx populations, respectively, were attributable to differences in age-adjusted incidence compared to White populations rather than differences in case fatality ratios.

Conclusions

Racial and ethnic disparities in the COVID-19 pandemic are products of society, not biology. Considering age and geography in addition to race/ethnicity can help to identify the structural factors driving poorer outcomes for certain groups. Studies and policies aimed at reducing inequalities in disease exposure may reduce disparities in mortality more than those focused on drivers of case fatality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12698-9.

A Programmatic Response, Including Bamlanivimab or Casirivimab-imdevimab Administration, Reduces Hospitalization and Death in COVID-19 Positive Abdominal Transplant Recipients

BACKGROUND

(COVID-19) has resulted in significant morbidity and mortality in solid organ transplant recipients. In December 2020, at the peak of the Los Angeles outbreak, our center rapidly implemented a protocol to improve outpatient management and provide bamlanivimab or casirivimab-imdevimab [COVID monoclonal antibody (mAb) therapies] to all eligible COVID-19 positive liver and kidney transplant recipients.

METHODS

A retrospective review of all abdominal organ transplant recipients who were COVID-19 polymerase chain reaction positive between February 2020 and February 2021 from our center was performed. Patient demographics, COVID-19 treatments, hospitalizations, and survival were reviewed. Patients were considered eligible for COVID mAb therapy if they met outpatient criteria at the time of diagnosis.

RESULTS

In the study period, 121 patients in the kidney transplant recipients group (KG) and 105 patients in the liver or combined liver/kidney transplant recipients group (LG) were COVID-19 polymerase chain reaction positive. Hospitalization rates were similar for the KG (45%) versus LG (35%) (P = 0.20), but mortality was higher for the KG (22%) when compared to LG (10%) (P = 0.02). Our programmatic response, including outpatient COVID mAb therapies, reduced hospitalizations (P = 0.01) and deaths (P = 0.01). Ninety-four KG and 87 LG patients were identified as potentially eligible for COVID mAb therapy, and 17 KG and 17 LG patients were treated. COVID mAb therapies reduced hospitalization from 32% to 15% (P = 0.045) and eliminated mortality (13% versus 0%, P = 0.04).

CONCLUSIONS

An aggressive approach including outpatient COVID mAb therapy in the COVID positive abdominal organ transplant recipients significantly decreased hospitalization and death. Early outpatient intervention for COVID-19 disease in transplant patients should be considered where possible.

The Impact of Health Disparities on COVID-19 Outcomes: Early Findings from a High-Income Country and Two Middle-Income Countries

The SARS-CoV-2 infection, which causes the coronavirus disease (COVID-19), has affected lives, with very adverse outcomes in specific populations in the United States of America (USA), a high-income country, and two middle-income countries, Brazil and South Africa. This paper aims to discuss the relationship of race/ethnicity with COVID-19-associated factors in the three countries. The information is based on data collected from infectious disease/epidemiological centers in the USA, Brazil, and South Africa. Adverse COVID-19 outcomes have been associated with the burden of exposure and disease, linked to socioeconomic determinants, among specific ethnicities in all three countries. The prevalence of comorbidities before and the likelihood of work-related exposure in the context of COVID-19 infection puts ethnic minorities in the USA and some ethnic majorities and minorities in Brazil and South Africa at greater risk. We envisage that this work will contribute to ongoing discussions related to addressing socioeconomic determinants of health, and the need for stakeholders in various sectors to work on addressing observed health disparities for overall improvement in health and healthcare given the current pandemic.

There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk

Mathematical models have come to play a key role in global pandemic preparedness and outbreak response: helping to plan for disease burden, hospital capacity, and inform nonpharmaceutical interventions. Such models have played a pivotal role in the COVID-19 pandemic, with transmission models—and, by consequence, modelers—guiding global, national, and local responses to SARS-CoV-2. However, these models have largely not accounted for the social and structural factors, which lead to socioeconomic, racial, and geographic health disparities. In this piece, we raise and attempt to clarify several questions relating to this important gap in the research and practice of infectious disease modeling: Why do epidemiologic models of emerging infections typically ignore known structural drivers of disparate health outcomes? What have been the consequences of a framework focused primarily on aggregate outcomes on infection equity? What should be done to develop a more holistic approach to modeling-based decision-making during pandemics? In this review, we evaluate potential historical and political explanations for the exclusion of drivers of disparity in infectious disease models for emerging infections, which have often been characterized as “equal opportunity infectors” despite ample evidence to the contrary. We look to examples from other disease systems (HIV, STIs) and successes in including social inequity in models of acute infection transmission as a blueprint for how social connections, environmental, and structural factors can be integrated into a coherent, rigorous, and interpretable modeling framework. We conclude by outlining principles to guide modeling of emerging infections in ways that represent the causes of inequity in infection as central rather than peripheral mechanisms.

Comprehensive Immune Profiling Reveals CD56+ Monocytes and CD31+ Endothelial Cells Are Increased in Severe COVID-19 Disease

Immune response dysregulation plays a key role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenesis. In this study, we evaluated immune and endothelial blood cell profiles of patients with coronavirus disease 2019 (COVID-19) to determine critical differences between those with mild, moderate, or severe COVID-19 using spectral flow cytometry. We examined a suite of immune phenotypes, including monocytes, T cells, NK cells, B cells, endothelial cells, and neutrophils, alongside surface and intracellular markers of activation. Our results showed progressive lymphopenia and depletion of T cell subsets (CD3⁺, CD4⁺, and CD8⁺) in patients with severe disease and a significant increase in the CD56⁺CD14⁺Ki67⁺IFN-γ⁺ monocyte population in patients with moderate and severe COVID-19 that has not been previously described. Enhanced circulating endothelial cells (CD45^-CD31⁺CD34⁺CD146⁺), circulating endothelial progenitors (CD45^-CD31⁺CD34^+/-CD146^-), and neutrophils (CD11b⁺CD66b⁺) were coevaluated for COVID-19 severity. Spearman correlation analysis demonstrated the synergism among age, obesity, and hypertension with upregulated CD56⁺ monocytes, endothelial cells, and decreased T cells that lead to severe outcomes of SARS-CoV-2 infection. Circulating monocytes and endothelial cells may represent important cellular markers for monitoring postacute sequelae and impacts of SARS-CoV-2 infection during convalescence and for their role in immune host defense in high-risk adults after vaccination.

Association of city-level walkability, accessibility to biking and public transportation and socio-economic features with COVID-19 infection in Massachusetts, USA: An ecological study

With people restricted to their residences, neighbourhood characteristics may affect behaviour and risk of coronavirus disease 2019 (COVID-19) infection. We aimed to analyse whether neighbourhoods with higher walkability, public transit, biking services and higher socio-economic status were associated with lower COVID-19 infection during the peak of the COVID-19 pandemic in Massachusetts. We used Walk Score®, Bike Score®, and Transit Score® indices to assess the walkability and transportation of 72 cities in Massachusetts, USA based on availability of data and collected the total COVID-19 case numbers of each city up to 10 April 2021. We used univariate and multivariate linear models to analyse the effects of these scores on COVID-19 cases per 100,000 in each city, adjusting for demographic covariates and all covariates, respectively. In the 72 cities studied, the average Walk Score, Transit Score and Bike Score was 48.7, 36.5 and 44.1, respectively, with a total of 426,182 COVID-19 cases. Higher Walk Score, Transit Score, and Bike Score rankings were negatively associated with COVID-19 cases per 100,000 persons (<0.05). Cities with a higher proportion of Hispanic population and a lower median household income were associated with more COVID-19 cases per 100,000 (P<0.05). Higher Walk Score, Transit Score and Bike Score were shown to be protective against COVID-19 transmission, while socio-demographic factors were associated with COVID-19 infection. Understanding the complex relationship of how the structure of the urban environment may constrain commuting patterns for residents and essential workers during COVID-19 would offer potential insights on future pandemic preparedness and response.

Prevalence and Correlates of SARS CoV-2 Among a Community-Based Sample Recruited Using Randomized Venue-Based Sampling. Essex County, NJ, 2020

Disparities in morbidity and mortality related to COVID-19 based on race and ethnicity have been documented in the USA. However, it is unclear if these disparities also exist at the exposure stage. To determine this, studies are needed to document the underlying burden of disease, potential disparities through serologic surveillance. Additionally, such studies can help identify where along the disease spectrum (e.g., exposure, infection, diagnosis, treatment, death) and with regard to the structural factors that necessitate public health and/or clinical interventions. Our objectives in this study were to estimate the true burden of SARS CoV-2 in the community of Essex County, NJ, an early and hard hit area, to determine the correlates of SARS CoV-2 prevalence and to determine if COVID-19 disparities seen by race/ethnicity were also reflected in SARS CoV-2 burden. We utilized venue-based-sampling (VBS) to sample members of the community in Essex County. Participants completed a short electronic survey and provided finger stick blood samples for testing. We sampled 924 residents of Essex County, New Jersey. Testing conducted in this study identified 83 (9.0%) participants as positive for SARS-CoV-2 antibodies. Importantly, our findings suggest that the true burden of SARS-Cov-2 and the pool of persons potentially spreading the virus are slightly more than six times than that suggested by PCR testing Notably, there were no significant differences in odds of testing positive for SARS CoV-2 antibodies in terms of race/ethnicity where we compared Black and Latinx participants to other race participants. Our study suggests that disparities in COVID-19 outcomes stem from potential upstream issues such as underlying conditions, access to testing, and access to care rather than disparities in exposure to the virus.

Future Directions for Vaccinating Children against the American Endemic: Treating Racism as a Virus

For Black American youth and their families, the racial terror that claimed the life of George Floyd in May 2020 is nothing new, as stories of people who look just like them have been part and parcel of their lived experience in the United States. Beyond state-sanctioned murder, Black youth were also witnessing the disproportionate transmission, treatment, and travesty plaguing their community with COVID-19 - all predictable outcomes given the inequitable systems supporting the American pipeline from cradle to grave. Why, then, were so many White Americans just coming into awareness of this deadly disease of individual and systemic racism that has ravaged Black American communities for centuries? In this work, we seek to explain in what ways racism is tantamount to a social virus and how its permeation is endemic to the American body, rather than an emerging threat, like a pandemic. We will also address how better conceptualizing racism as a virus allows for more accurate, precise, and feasible treatments for transmitters and targets of racism with respect to prevention (e.g., inoculation) and intervention (e.g., healing and vaccination). Finally, we will describe clinical therapeutic trials that will help to decipher whether our treatment of this social disease is effective, including family-level interventions and systemic shifts in prevention through clinical training.

Using GIS-based spatial analysis to determine urban greenspace accessibility for different racial groups in the backdrop of COVID-19: a case study of four US cities

As the United States leads COVID-19 cases on global charts, its spatial distribution pattern offers a unique opportunity for studying the social and ecological factors that contribute to the pandemic's scale and size. We use a GIS-data-based approach to evaluate four American cities-Anchorage (Alaska), Atlanta (Georgia), Phoenix (Arizona), and Portland (Oregon) characterized by the significant composition of different racial and ethnic group populations. Building upon previous studies that investigated urban spatial inequalities using the environmental justice framework, we examine: (1) the relative racial vulnerability of Census Block Groups (CBG) and ZIP Code Tabulation Areas (ZCTA) to COVID-19 (2) green space distribution at CBG and ZCTA scale. Using standard normalization methods, we ranked racial vulnerability against % available green space for each city. Our results highlight the legacy of past and present urban planning injustices. The project is useful from environmental justice, public health management, and urban planning perspectives.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10708-021-10538-8.

Exploring the Scope and Dimensions of Vaccine Hesitancy and Resistance to Enhance COVID-19 Vaccination in Black Communities

BACKGROUND

The long history of distrust that characterizes the relationship between the Black/African-American population and the US Medical community makes COVID-19 vaccine hesitancy of great concern. A needs assessment of the Black/African-American community assessed willingness and explored the perceptions of community members regarding COVID-19 vaccination.

METHODS

The study used a mixed-methods approach. Respondents (n = 183) were surveyed with a web-based questionnaire. They were asked whether there would get vaccinated for COVID-19 barring any access or cost-related challenges. Perceptions of community members regarding vaccination were explored through one-on-one interviews (n = 30) and eight focus groups (n = 49), with participants drawn from across various demographic characteristics. Survey responses were summarized using frequencies and proportions. A thematic analysis was conducted on the qualitative data.

RESULTS

Thirty-four percent of respondents indicated "Yes" (willing to get vaccinated); 26.8% indicated "No", while 37.1% expressed hesitancy ("Maybe" or "I don't know"). Themes emerging from the qualitative data are grouped into three broad categories: vaccine accessibility (transportation, information, navigating healthcare system); vaccine hesitancy (with sub-categories of compliance, complacency and confidence); and vaccine "resistance" (conspiracy theories, conflicting beliefs, distrust of Government, trustworthiness of Health care).

CONCLUSION

Findings demonstrate a nuanced expansion of "vaccine hesitancy" to delineate groups with varying issues and perspectives. Interventions to enhance vaccination rates in Black/African-American communities should incorporate components that assure accessibility at the minimum, but also address non-access-related issues. Priority should be given to enhancing vaccine literacy, information-sharing as efficacy and safety data emerge, and addressing specific concerns identified through community-engaged outreach efforts.

Diversity's Pandemic Distractions

Pandemic diseases have a nasty history of racialization. COVID-19 is no exception. Beyond the obvious racist invocations of the "China virus" or the "Wuhan Flu" are subtler racializing dynamics that are often veiled in more benign motives but are nonetheless deeply problematic. The racialization of COVID-19 proceeded along two distinct trajectories each of which threatened to reinforce inaccurate biologized conceptions of race while diverting attention from the social, legal, and political forces historically structuring race-based health disparities. First, early on as significant racial disparities in disease incidence and mortality became evident, a frame of race-based genetic difference came to the fore as a possible explanation. Second, as vaccine development ramped up there came widespread calls for racially "diversifying" clinical trials for the vaccines being tested. The rationales for such diversification were varied but tended to reinforce genetic frames of racial difference. Most common was the assertion (without substantial evidence) that vaccines might work differently in Black or Brown bodies and so racial diversity in trials was imperative for reasons of safety and efficacy. Derrick Bell cautioned 20 years ago that "the concept of diversity … is a serious distraction in the ongoing efforts to achieve racial justice." (Derrick Bell, Diversity's Distractions, 103 Colum. L. Rev. 1622, 1622 (2003).) This article explores the dynamics of how the concept of "diversity" racialized responses to COVID-19 and considers their broader implications for understanding and responding to racial disparities in the face of pandemic emergencies and beyond. In the short term, vaccine developers did a decent job of enrolling minorities in their clinical trials and the vaccines have proven to have the same safety and efficacy across races. In the long term, diversity in the biomedical context of pandemic response not only distracts attention from important structural causes of health injustice, but it also focuses attention on the genetics of disparities in a manner that has the potential to reinforce pernicious and false ideas of essential biological difference among racial groups. This article argues that an uncritical embrace of the idea of diversity in analyzing and responding to emergent health crises has the potential to distract us from considering deeper historical and structural formations contributing to racial health disparities. It proceeds first by exploring the dynamics through which initial responses to racial disparities in COVID-19 became geneticized. It will then move on to unpack the rationales for such racialization, examine their merits (or lack thereof), and consider their implications for developing an equitable response to pandemic emergencies. The next section will examine the subsequent racialization of clinical trials for COVID-19 vaccines through the concept of "diversity." It then moves on to explore how the geneticization of COVID-19 racial disparities laid the foundations for a similar geneticization of race in vaccine development. It will argue that in failing to clearly distinguish social and biological rationales for diversity, such framings, while generally well-intentioned, are poorly supported and work in tandem with the geneticization of racial disparities in COVID-19 morbidity and mortality to locate the causes of disparities in the minds and bodies of minoritized populations; again this distracts attention from the historical and structural forces contributing to such disparities. The article concludes by recognizing a certain intractability to the problems of using race in biomedical research and practice, particularly in the context of public health emergencies. It offers modest suggestions for improvement that could have significant practical effects if taken to heart by researchers, clinicians, and policy makers.

The unequal burden of the Covid-19 pandemic: Capturing racial/ethnic disparities in US cause-specific mortality

Despite a growing body of literature focused on racial/ethnic disparities in Covid-19 mortality, few previous studies have examined the pandemic's impact on 2020 cause-specific mortality by race and ethnicity. This paper documents changes in mortality by underlying cause of death and race/ethnicity between 2019 and 2020. Using age-standardized death rates, we attribute changes for Black, Hispanic, and White populations to various underlying causes of death and show how these racial and ethnic patterns vary by age and sex. We find that although Covid-19 death rates in 2020 were highest in the Hispanic community, Black individuals faced the largest increase in all-cause mortality between 2019 and 2020. Exceptionally large increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population. Within Black and White populations, percentage increases in all-cause mortality were similar for men and women, as well as for ages 25–64 and 65+. Among the Hispanic population, however, percentage increases in mortality were greatest for working-aged men. These findings reveal that the overall impact of the pandemic on racial/ethnic disparities in mortality was much larger than that captured by official Covid-19 death counts alone.

Changing Disparities in Coronavirus Disease 2019 (COVID-19) Burden in the Ethnically Homogeneous Population of Hong Kong Through Pandemic Waves: An Observational Study

BACKGROUND

Disparities were marked in previous pandemics, usually with higher attack rates reported for those in lower socioeconomic positions and for ethnic minorities.

METHODS

We examined characteristics of laboratory-confirmed coronavirus disease 2019 (COVID-19) cases in Hong Kong, assessed associations between incidence and population-level characteristics at the level of small geographic areas, and evaluated relations between socioeconomics and work-from-home (WFH) arrangements.

RESULTS

The largest source of COVID-19 importations switched from students studying overseas in the second wave to foreign domestic helpers in the third. The local cases were mostly individuals not in formal employment (retirees and homemakers) and production workers who were unable to WFH. For every 10% increase in the proportion of population employed as executives or professionals in a given geographic region, there was an 84% (95% confidence interval [CI], 1-97%) reduction in the incidence of COVID-19 during the third wave. In contrast, in the first 2 waves, the same was associated with 3.69 times (95% CI, 1.02-13.33) higher incidence. Executives and professionals were more likely to implement WFH and experienced frequent changes in WFH practice compared with production workers.

CONCLUSIONS

Consistent findings on the reversed socioeconomic patterning of COVID-19 burden between infection waves in Hong Kong in both individual- and population-level analyses indicated that risks of infections may be related to occupations involving high exposure frequency and WFH flexibility. Contextual determinants should be taken into account in policy planning aiming at mitigating such disparities.

Not the great equalizers: Covid-19, 1918-20 influenza, and the need for a paradigm shift in pandemic preparedness

Despite common perceptions to the contrary, pandemic diseases do not affect populations indiscriminately. In this paper, we review literature produced by demographers, historians, epidemiologists, and other researchers on disparities during the 1918-20 influenza pandemic and the Covid-19 pandemic. Evidence from these studies demonstrates that lower socio-economic status and minority/stigmatized race or ethnicity are associated with higher morbidity and mortality. However, such research often lacks theoretical frameworks or appropriate data to explain the mechanisms underlying these disparities fully. We suggest using a framework that considers proximal and distal factors contributing to differential exposure, susceptibility, and consequences as one way to move this research forward. Further, current pandemic preparedness plans emphasize medically defined risk groups and epidemiological approaches. Therefore, we conclude by arguing in favour of a transdisciplinary paradigm that recognizes socially defined risk groups, includes input from the social sciences and humanities and other diverse perspectives, and contributes to the reduction of health disparities before a pandemic hits.

Measuring Discharge Outcomes, Length of Stay, and Functional ADL Score During COVID-19 in Inpatient Rehabilitation Hospitals

OBJECTIVE

To measure discharge disposition, length of stay (LOS), and functional activities of daily living (ADL) scores for patients admitted to acute inpatient rehabilitation hospitals (IRHs) during the coronavirus disease 2019 (COVID-19) pandemic and to compare these parameters with a period prior to the pandemic.

DESIGN

Retrospective cohort study via systematic retrospective chart review of consecutive patients admitted to IRHs from January 1-February 19, 2020 (pre-COVID-19T), and COVID-19 time period/patients admitted from April 1, 2020-May 9, 2020 (COVID-19T).

SETTING

System of 3 IRHs in the Northeastern United States.

PARTICIPANTS

Pre-COVID-19T, n=739; COVID-19T, n=335, of whom n=139 were positive for COVID-19 (COVID+) and n=196 were negative (COVID-) (N=1074).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Discharge disposition, LOS, and functional ADL scores.

RESULTS

COVID-19T patients were younger (P=.03) and less likely to be White (P=.03). These patients also had a higher case mix index (CMI; P<.01), longer acute care LOS (P<.01), and longer IRH LOS (P<.01). Patients who were COVID+ (during COVID-19T) were less likely to be White (P<.01), had lower CMI (P<.01), had higher admission and discharge functional ADL scores (P=.02, P<.01), and had longer acute care LOS compared with those who were COVID- (P<.01). There were no differences in discharge outcomes between pre-COVID-19T and COVID-19T cohorts (P=.75), including when stratified for COVID-19 status (P=.74). Functional ADL scores on admission and discharge were lower in COVID-19T than in pre-COVID-19T (P=.01), including when stratified for COVID-19 status though not significant (P=.06).

CONCLUSIONS

There were no differences in discharge outcomes for any group. IRH LOS was significantly increased during the pandemic, but there were no statistically significant differences between the COVID+ and COVID- cohorts within COVID-19T. Functional ADL scores were significantly lower during COVID-19T, but COVID status was not a significant predictor. This suggests that COVID+ status was not a barrier to discharge or functional outcomes. This supports the importance of IRHs to restore function and discharge patients to home, even with a more medically complex COVID-19 pandemic population.

COVID-19 Vaccine Hesitancy and Its Determinants Among Adults with a History of Tobacco or Marijuana Use

Decreasing COVID-19 vaccine hesitancy is an urgent challenge in the US. This study aimed to examine COVID-19 vaccine hesitancy among U.S. adults with a history of using tobacco products or marijuana. Data were collected online in 2020-2021 including respondents' willingness to accept a COVID-19 vaccine, factors that may promote vaccine acceptance, and prior history of influenza vaccination. Logistic regression models were conducted to estimate the associations between vaccine hesitancy and demographic characteristics, substance use, the impact of the COVID-19 pandemic, and prior influenza vaccination. Among 387 respondents, 49.1% were willing to receive a COVID-19 vaccine, 26.0% were unwilling, and 24.9% were "not sure." Blacks, suburban or rural residents, those who lived by themselves or with a family with five members or above, those who were not stressed because of the COVID-19 pandemic were more likely to say "no" to a COVID-19 vaccine. Respondents who never, only once, or during some years received an influenza vaccine were 7.0, 6.2, and 5.2 times more likely to say "no" to a COVID-19 vaccine than respondents who received an influenza vaccination every year or almost every year. The use of cigarettes, e-cigarettes, and marijuana, as well as heavy drinking of alcohol, were not associated with COVID-19 hesitancy. The associations between demographic factors and vaccine hesitancy were roughly similar for COVID-19 and influenza vaccines. Although various demographic groups have different levels of vaccine hesitancy and also have different factors to increase their acceptance, addressing misinformation related to COVID-19 vaccines, particularly concern about the safety of the vaccines is crucial in general.

Dynamic COVID risk assessment accounting for community virus exposure from a spatial-temporal transmission model

COVID-19 pandemic has caused unprecedented negative impacts on our society, including further exposing inequity and disparity in public health. To study the impact of socioeconomic factors on COVID transmission, we first propose a spatial-temporal model to examine the socioeconomic heterogeneity and spatial correlation of COVID-19 transmission at the community level. Second, to assess the individual risk of severe COVID-19 outcomes after a positive diagnosis, we propose a dynamic, varying-coefficient model that integrates individual-level risk factors from electronic health records (EHRs) with community-level risk factors. The underlying neighborhood prevalence of infections (both symptomatic and pre-symptomatic) predicted from the previous spatial-temporal model is included in the individual risk assessment so as to better capture the background risk of virus exposure for each individual. We design a weighting scheme to mitigate multiple selection biases inherited in EHRs of COVID patients. We analyze COVID transmission data in New York City (NYC, the epicenter of the first surge in the United States) and EHRs from NYC hospitals, where time-varying effects of community risk factors and significant interactions between individual- and community-level risk factors are detected. By examining the socioeconomic disparity of infection risks and interaction among the risk factors, our methods can assist public health decision-making and facilitate better clinical management of COVID patients.

Age and Racial Disparities in Telemedicine Utilization in an Academic Orthopedic Surgery Department

Introduction: The COVID-19 pandemic has highlighted significant racial and age-related health disparities. In response to pandemic-related restrictions, orthopedic surgery departments have expanded telemedicine use. We analyzed data from a tertiary care institute during the pandemic to understand potential racial and age-based disparities in access to care and telemedicine utilization. Materials and Methods: Data on patient race and age, and numbers of telemedicine visits, in-person office visits, and types of telemedicine were extracted for time periods during and preceding the pandemic. We calculated odds ratios for visit occurrence and type across race and age groups. Results: Patients ages 27-54 were 1.3 (95% confidence interval [CI] 1.1-1.4, p < 0.01) and 1.2 (95% CI 1.0-1.3, p < 0.05) times more likely to be seen than patients <27 during the pandemic, versus the 2019 and 2020 controls. Patients 54-82 were 1.3 (95% CI 1.1-1.5, p < 0.001) times more likely to be seen than patients <27 during the pandemic versus the 2019 control. Patients 27-54, 54-82, and 82+, respectively, were 3.3 (95% CI 2.6-4.2, p < 1e-20), 3.5 (95% CI 2.8-4.4, p < 1e-24), and 1.9 (95% CI 1.1-3.4, p < 0.05) times more likely to be seen by telemedicine than patients <27. Among pandemic telemedicine appointments, Black patients were 1.5 (95% CI 1.2-1.9, p < 1e-3) times more likely to be seen by audio-only telemedicine than White patients, as compared with video telemedicine. Conclusions: Telemedicine access barriers must be reduced to ensure that disparities during the pandemic do not persist.

Racial and Ethnic Disparities in SARS-CoV-2 Testing and COVID-19 Outcomes in a Medicaid Managed Care Cohort

INTRODUCTION

Socioeconomic differences may confound racial and ethnic differences in SARS-CoV-2 testing and COVID-19 outcomes.

METHODS

A retrospective cohort study was conducted of racial/ethnic differences in SARS-CoV-2 testing and positive tests and COVID-19 hospitalizations and deaths among adults impaneled at a Northern California regional medical center and enrolled in the county Medicaid managed care plan (N=84,346) as of March 1, 2020. Logistic regressions adjusted for demographics, comorbidities, and neighborhood characteristics.

RESULTS

Nearly 30% of enrollees were ever tested for SARS-CoV-2, and 4% tested positive. A total of 19.7 per 10,000 were hospitalized for and 9.4 per 10,000 died of COVID-19. Those identified as Asian, Black, or of other/unknown race had lower testing rates, whereas those identified as Latino had higher testing rates than Whites. Enrollees of Asian or other/unknown race had slightly higher odds of a positive test, and Latinos had much higher odds of a positive test (OR=3.77, 95% CI=3.41, 4.17) than Whites. The odds of hospitalization (OR=2.85, 95% CI=1.85, 4.40) and death (OR=4.75, 95% CI=2.23, 10.12) were higher for Latino than for White patients, even after adjusting for demographics, comorbidities, and neighborhood characteristics.

CONCLUSIONS

In a Medicaid managed care population, where socioeconomic differences may be reduced, the odds of a positive SARS-CoV-2 test, COVID-19 hospitalization, and COVID-19 death were higher for Latino but not Black patients than for White patients. Racial/ethnic disparities depend on local context. The substantially higher risk facing Latinos should be a key consideration in California's strategies to mitigate disease transmission and harm.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis

IMPORTANCE

COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

OBJECTIVE

To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

DATA SOURCES

A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.

STUDY SELECTION

Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.

DATA EXTRACTION AND SYNTHESIS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

The main measures were RRs, ORs, and combined prevalence values.

RESULTS

A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).

CONCLUSIONS AND RELEVANCE

In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Variation in COVID-19 Mortality in the US by Race and Ethnicity and Educational Attainment

Importance

Racial and ethnic inequities in COVID-19 mortality have been well documented, but little prior research has assessed the combined roles of race and ethnicity and educational attainment.

Objective

To measure inequality in COVID-19 mortality jointly by race and ethnicity and educational attainment.

Design, Setting, and Participants

This cross-sectional study analyzed data on COVID-19 mortality from the 50 US states and the District of Columbia for the full calendar year 2020. It included all persons in the United States aged 25 years or older and analyzed them in subgroups jointly stratified by age, sex, race and ethnicity, and educational attainment.

Main Outcomes and Measures

Population-based cumulative mortality rates attributed to COVID-19.F.

Results

Among 219.1 million adults aged 25 years or older (113.3 million women [51.7%]; mean [SD] age, 51.3 [16.8] years), 376 125 COVID-19 deaths were reported. Age-adjusted cumulative mortality rates per 100 000 ranged from 54.4 (95% CI, 49.8-59.0 per 100 000 population) among Asian women with some college to 699.0 (95% CI, 612.9-785.0 per 100 000 population) among Native Hawaiian and Other Pacific Islander men with a high school degree or less. Racial and ethnic inequalities in COVID-19 mortality rates remained when comparing within educational attainment categories (median rate ratio reduction, 17% [IQR, 0%-25%] for education-stratified estimates vs unstratified, with non-Hispanic White individuals as the reference). If all groups had experienced the same mortality rates as college-educated non-Hispanic White individuals, there would have been 48% fewer COVID-19 deaths among adults aged 25 years or older overall, including 71% fewer deaths among racial and ethnic minority populations and 89% fewer deaths among racial and ethnic minority populations aged 25 to 64 years.

Conclusions and Relevance

Public health research and practice should attend to the ways in which populations that share socioeconomic characteristics may still experience racial and ethnic inequity in the distribution of risk factors for SARS-CoV-2 exposure and infection fatality rates (eg, housing, occupation, and prior health status). This study suggests that a majority of deaths among racial and ethnic minority populations could have been averted had all groups experienced the same mortality rate as college-educated non-Hispanic White individuals, thus highlighting the importance of eliminating joint racial-socioeconomic health inequities.

Performance characteristics of the Abbott BinaxNOW SARS-CoV-2 antigen test in comparison to real-time RT-PCR and viral culture in community testing sites during November 2020

Point-of-care antigen tests are an important tool for SARS-CoV-2 detection. Antigen tests are less sensitive than real-time reverse-transcriptase PCR (rRT-PCR). Data on the performance of the BinaxNOW antigen test compared to rRT-PCR and viral culture by symptom and known exposure status, timing during disease or exposure period and demographic variables are limited. During November 3^rd-17^th, 2020, we collected paired upper respiratory swab specimens to test for SARS-CoV-2 by rRT-PCR and Abbott BinaxNOW (BinaxNOW) antigen test at two community testing sites in Pima County, Arizona. We administered a questionnaire to capture symptoms, known exposure status and previous SARS-CoV-2 test results. Specimens positive by either test were analyzed by viral culture. Previously we showed overall BinaxNOW sensitivity was 52.5%. Here we showed BinaxNOW sensitivity increased to 65.7% among currently symptomatic individuals reporting a known exposure. BinaxNOW sensitivity was lower among participants with a known exposure and previously symptomatic (32.4%) or never symptomatic (47.1%) within 14 days of testing. Sensitivity was 71.1% in participants within a week of symptom onset. In participants with a known exposure, sensitivity was highest 8-10 days post-exposure (75%). The positive predictive value for recovery of virus in cell culture was 56.7% for BinaxNOW-positive and 35.4% for rRT-PCR-positive specimens. Result reporting time was 2.5 hours for BinaxNOW and 26 hours for rRT-PCR. Point-of-care antigen tests have a shorter turn-around time compared to laboratory-based nucleic acid amplification tests, which allows for more rapid identification of infected individuals. Antigen test sensitivity limitations are important to consider when developing a testing program.

Case-control study of the association of chronic acid suppression and social determinants of health with COVID-19 infection

Acid suppressants are widely-used classes of medications linked to increased risks of aerodigestive infections. Prior studies of these medications as potentially reversible risk factors for COVID-19 have been conflicting. We aimed to determine the impact of chronic acid suppression use on COVID-19 infection risk while simultaneously evaluating the influence of social determinants of health to validate known and discover novel risk factors. We assessed the association of chronic acid suppression with incident COVID-19 in a 1:1 case–control study of 900 patients tested across three academic medical centers in California, USA. Medical comorbidities and history of chronic acid suppression use were manually extracted from health records by physicians following a pre-specified protocol. Socio-behavioral factors by geomapping publicly-available data to patient zip codes were incorporated. We identified no evidence to support an association between chronic acid suppression and COVID-19 (adjusted odds ratio 1.04, 95% CI 0.92–1.17, P = 0.515). However, several medical and social features were positive (Latinx ethnicity, BMI ≥ 30, dementia, public transportation use, month of the pandemic) and negative (female sex, concurrent solid tumor, alcohol use disorder) predictors of new infection. These findings demonstrate the value of integrating publicly-available databases with medical data to identify critical features of communicable diseases.

How the COVID-19 Pandemic Can and Must Expand Social Worker e-Interventions for Mental Health, Family Wellness, and Beyond

Both media and academic reports have highlighted COVID-19's negative impacts on mental health and safety in the United States, yet care and service gaps persist. Evidence suggests that a default to in-person service delivery did not meet clients' needs before the pandemic, and that unmet needs have ballooned since COVID-19 spread throughout the United States due to a combination of increased stress, social isolation, and fewer available services during lockdowns. This article reviews literature on online interventions' utility and effectiveness in preventing and treating problems likely exacerbated under pandemic conditions, including mental health conditions, anger, couple dynamics, parenting, and alcohol misuse. The article also describes barriers to evidence-based e-interventions' wider and more consistent use, highlights some vulnerable populations' unique service needs, outlines service gaps that online programs might effectively mitigate, and offers a path by which social workers can lead an interdisciplinary charge in researching, developing, and implementing e-interventions during the current pandemic and beyond.

Geographically targeted COVID-19 vaccination is more equitable and averts more deaths than age-based thresholds alone

COVID-19 mortality increases markedly with age and is also substantially higher among Black, Indigenous, and People of Color (BIPOC) populations in the United States. These two facts can have conflicting implications because BIPOC populations are younger than white populations. In analyses of California and Minnesota—demographically divergent states—we show that COVID vaccination schedules based solely on age benefit the older white populations at the expense of younger BIPOC populations with higher risk of death from COVID-19. We find that strategies that prioritize high-risk geographic areas for vaccination at all ages better target mortality risk than age-based strategies alone, although they do not always perform as well as direct prioritization of high-risk racial/ethnic groups. Vaccination schemas directly implicate equitability of access, both domestically and globally.

Unequal Opportunity Spreaders: Higher COVID-19 Deaths with Later School Closure in the United States

Mixed evidence on the relationship between school closure and COVID-19 prevalence could reflect focus on large-scale levels of geography, limited ability to address endogeneity, and demographic variation. Using county-level Centers for Disease Control and Prevention (CDC) COVID-19 data through June 15, 2020, two matching strategies address potential heterogeneity: nearest geographic neighbor and propensity scores. Within nearest neighboring pairs in different states with different school closure timing, each additional day from a county's first case until state-ordered school closure is related to 1.5 to 2.4 percent higher cumulative COVID-19 deaths per capita (1,227-1,972 deaths for a county with median population and deaths/capita). Results are consistent using propensity score matching, COVID-19 data from two alternative sources, and additional sensitivity analyses. School closure is more strongly related to COVID-19 deaths in counties with a high concentration of Black or poor residents, suggesting schools play an unequal role in transmission and earlier school closure is related to fewer lives lost in disadvantaged counties.

Disruption of medical care among individuals in the southeastern United States during the COVID-19 pandemic

BACKGROUND

Widespread disruptions of medical care to mitigate COVID-19 spread and reduce burden on healthcare systems may have deleterious public health consequences.

DESIGN AND METHODS

To examine factors contributing to healthcare interruptions during the pandemic, we conducted a COVID-19 impact survey between 10/7-12/14/2020 among participants of the Southern Community Cohort Study, which primarily enrolled low-income individuals in 12 southeastern states from 2002-2009. COVID survey data were combined with baseline and follow-up data.

RESULTS

Among 4,463 respondents, 40% reported having missed/delayed a health appointment during the pandemic; the common reason was provider-initiated cancellation or delay (63%). In a multivariable model, female sex was the strongest independent predictor of interrupted care, with odds ratio (OR) 1.63 (95% confidence interval [CI] 1.40-1.89). Those with higher education (OR 1.27; 95% CI 1.05-1.54 for college graduate vs ≤high school) and household income (OR 1.47; 95% CI 1.16-1.86 for >$50,000 vs <$15,000) were at significantly increased odds of missing healthcare.  Having greater perceived risk for acquiring (OR 1.42; 95% CI 1.17-1.72) or dying from COVID-19 (OR 1.25; 95% CI 1.04-1.51) also significantly increased odds of missed/delayed healthcare. Age was inversely associated with missed healthcare among men (OR for 5-year increase in age 0.88; 95% CI 0.80-0.96) but not women (OR 0.97; 95% CI 0.91-1.04; p-interaction=0.04). Neither race/ethnicity nor comorbidities were associated with interrupted healthcare.

CONCLUSIONS

Disruptions to healthcare disproportionately affected women and were primarily driven by health system-initiated deferrals and individual perceptions of COVID-19 risk, rather than medical co-morbidities or other traditional barriers to healthcare access.

Association Of Unemployment With Medicaid Enrollment By Social Vulnerability In North Carolina During COVID-19

The COVID-19 pandemic precipitated an unemployment crisis in the US that surpassed the Great Recession of 2007-09 within the first three months of the pandemic. This article builds on the limited early evidence of the relationship between the pandemic and health insurance coverage, using county-level unemployment and Medicaid enrollment data from North Carolina, a large state that did not expand Medicaid. We used linear and county fixed effects models to assess this relationship, accounting for county-level social vulnerability, physical and virtual access to Medicaid enrollment, and COVID-19 case burden. Using data from January 2018 through August 2020, we estimated that the passthrough rate-the share of unemployed people who gained Medicaid coverage-was approximately 15 percent statewide but higher in more socially vulnerable counties. This low passthrough rate during a period of increased unemployment resulting from the COVID-19 pandemic means that Medicaid was unable to completely fulfill its countercyclical role, in which it grows to meet greater need during periods of widespread economic hardship, because of North Carolina's stringent Medicaid eligibility criteria. Working toward greater adoption of Medicaid expansion may help ensure that the US is better prepared for the next crisis by ensuring access to health insurance coverage.

External validation of the 4C Mortality Score for patients with COVID-19 and pre-existing cardiovascular diseases/risk factors

OBJECTIVES

Predictive algorithms to inform risk management decisions are needed for patients with COVID-19, although the traditional risk scores have not been adequately assessed in Asian patients. We aimed to evaluate the performance of a COVID-19-specific prediction model, the 4C (Coronavirus Clinical Characterisation Consortium) Mortality Score, along with other conventional critical care risk models in Japanese nationwide registry data.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Hospitalised patients with COVID-19 and cardiovascular disease or coronary risk factors from January to May 2020 in 49 hospitals in Japan.

MAIN OUTCOME MEASURES

Two different types of outcomes, in-hospital mortality and a composite outcome, defined as the need for invasive mechanical ventilation and mortality.

RESULTS

The risk scores for 693 patients were tested by predicting in-hospital mortality for all patients and composite endpoint among those not intubated at baseline (n=659). The number of events was 108 (15.6%) for mortality and 178 (27.0%) for composite endpoints. After missing values were multiply imputed, the performance of the 4C Mortality Score was assessed and compared with three prediction models that have shown good discriminatory ability (RISE UP score, A-DROP score and the Rapid Emergency Medicine Score (REMS)). The area under the receiver operating characteristic curve (AUC) for the 4C Mortality Score was 0.84 (95% CI 0.80 to 0.88) for in-hospital mortality and 0.78 (95% CI 0.74 to 0.81) for the composite endpoint. It showed greater discriminatory ability compared with other scores, except for the RISE UP score, for predicting in-hospital mortality (AUC: 0.82, 95% CI 0.78 to 0.86). Similarly, the 4C Mortality Score showed a positive net reclassification improvement index over the A-DROP and REMS for mortality and over all three scores for the composite endpoint. The 4C Mortality Score model showed good calibration, regardless of outcome.

CONCLUSIONS

The 4C Mortality Score performed well in an independent external COVID-19 cohort and may enable appropriate disposition of patients and allocation of medical resources.Trial registration number UMIN000040598.

Accounting for uncertainty during a pandemic

We discuss several issues of statistical design, data collection, analysis, communication, and decision-making that have arisen in recent and ongoing coronavirus studies, focusing on tools for assessment and propagation of uncertainty. This paper does not purport to be a comprehensive survey of the research literature; rather, we use examples to illustrate statistical points that we think are important.

Association of Race and Ethnicity with COVID-19 Test Positivity and Hospitalization Is Mediated by Socioeconomic Factors

Rationale: Black race and Hispanic ethnicity are associated with increased risks for coronavirus disease (COVID-19) infection and severity. It is purported that socioeconomic factors may drive this association, but data supporting this assertion are sparse. Objectives: To evaluate whether socioeconomic factors mediate the association of race/ethnicity with COVID-19 incidence and outcomes. Methods: We conducted a retrospective cohort study of adults tested for (cohort 1) or hospitalized with (cohort 2) COVID-19 between March 1, 2020, and July 23, 2020, at the University of Miami Hospital and Clinics. Our primary exposure was race/ethnicity. We considered socioeconomic factors as potential mediators of our exposure's association with outcomes. We used standard statistics to describe our cohorts and multivariable regression modeling to identify associations of race/ethnicity with our primary outcomes, one for each cohort, of test positivity (cohort 1) and hospital mortality (cohort 2). We performed a mediation analysis to see whether household income, population density, and household size mediated the association of race/ethnicity with outcomes. Results: Our cohorts included 15,473 patients tested (29.0% non-Hispanic White, 48.1% Hispanic White, 15.0% non-Hispanic Black, 1.7% Hispanic Black, and 1.6% other) and 295 patients hospitalized (9.2% non-Hispanic White, 56.9% Hispanic White, 21.4% non-Hispanic Black, 2.4% Hispanic Black, and 10.2% other). Among those tested, 1,256 patients (8.1%) tested positive, and, of the hospitalized patients, 47 (15.9%) died. After adjustment for demographics, race/ethnicity was associated with test positivity-odds-ratio (95% confidence interval [CI]) versus non-Hispanic White for Non-Hispanic Black: 3.21 (2.60-3.96), Hispanic White: 2.72 (2.28-3.26), and Hispanic Black: 3.55 (2.33-5.28). Population density mediated this association (percentage mediated, 17%; 95% CI, 11-31%), as did median income (27%; 95% CI, 18-52%) and household size (20%; 95% CI, 12-45%). There was no association between race/ethnicity and mortality, although this analysis was underpowered. Conclusions: Black race and Hispanic ethnicity are associated with an increased odds of COVID-19 positivity. This association is substantially mediated by socioeconomic factors.

Estimated Mortality Increases During The COVID-19 Pandemic By Socioeconomic Status, Race, And Ethnicity

This article estimates changes in all-cause mortality due to the COVID-19 pandemic by socioeconomic characteristics and occupation for nonelderly adults in the US, using large-scale, national survey data linked to administrative mortality records. Mortality increases were largest for adults living in correctional facilities or in health care-related group quarters, those without health insurance coverage, those with family incomes below the federal poverty level, and those in occupations with limited work-from-home options. For almost all subgroups, mortality increases were higher among non-Hispanic Black respondents than among non-Hispanic White respondents. Hispanic respondents with health insurance, those not living in group quarters, those with work-from-home options, and those in essential industries also experienced larger increases in mortality during the COVID-19 crisis compared with non-Hispanic Whites in those categories. Occupations that experienced the largest mortality increases were related to installation, maintenance, and repair and production. This research highlights the relevance of individual economic, social, and demographic characteristics during the COVID-19 crisis.

A longitudinal SARS-CoV-2 biorepository for COVID-19 survivors with and without post-acute sequelae

BACKGROUND

SARS-CoV-2 has swept across the globe, causing millions of deaths worldwide. Though most survive, many experience symptoms of COVID-19 for months after acute infection. Successful prevention and treatment of acute COVID-19 infection and its associated sequelae is dependent on in-depth knowledge of viral pathology across the spectrum of patient phenotypes and physiologic responses. Longitudinal biobanking provides a valuable resource of clinically integrated, easily accessed, and quality-controlled samples for researchers to study differential multi-organ system responses to SARS-CoV-2 infection, post-acute sequelae of COVID-19 (PASC), and vaccination.

METHODS

Adults with a history of a positive SARS-CoV-2 nasopharyngeal PCR are actively recruited from the community or hospital settings to enroll in the Northern Colorado SARS-CoV-2 Biorepository (NoCo-COBIO). Blood, saliva, stool, nasopharyngeal specimens, and extensive clinical and demographic data are collected at 4 time points over 6 months. Patients are assessed for PASC during longitudinal follow-up by physician led symptom questionnaires and physical exams. This clinical trial registration is NCT04603677 .

RESULTS

We have enrolled and collected samples from 119 adults since July 2020, with 66% follow-up rate. Forty-nine percent of participants assessed with a symptom surveillance questionnaire (N = 37 of 75) had PASC at any time during follow-up (up to 8 months post infection). Ninety-three percent of hospitalized participants developed PASC, while 23% of those not requiring hospitalization developed PASC. At 90-174 days post SARS-CoV-2 diagnosis, 67% of all participants had persistent symptoms (N = 37 of 55), and 85% percent of participants who required hospitalization during initial infection (N = 20) still had symptoms. The most common symptoms reported after 15 days of infection were fatigue, loss of smell, loss of taste, exercise intolerance, and cognitive dysfunction.

CONCLUSIONS

Patients who were hospitalized for COVID-19 were significantly more likely to have PASC than those not requiring hospitalization, however 23% of patients who were not hospitalized also developed PASC. This patient-matched, multi-matrix, longitudinal biorepository from COVID-19 survivors with and without PASC will allow for current and future research to better understand the pathophysiology of disease and to identify targeted interventions to reduce risk for PASC. Registered 27 October 2020 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04603677 .

Variations in Presentation and Management of COVID-19 Inpatients by Race and Ethnicity in a Large Texas Metroplex

OBJECTIVE

The aim of this study was to assess variations in presentation and outcomes of coronavirus disease 2019 (COVID-19) across race/ethnicity at a large Texas metroplex hospital.

METHODS

A retrospective cohort study was performed.

RESULTS

Although COVID-19 patients demonstrated significant socioeconomic disparities, race/ethnicity was not a significant predictor of intensive care unit (ICU) admission (P = 0.067) or case fatality (P = 0.078). Hospital admission varied by month, with incidence among Black/African-American and Hispanic/Latino patients peaking earlier in the pandemic timeline (P < 0.001). Patients reporting Spanish as their primary language were significantly more likely to be admitted to the ICU (odds ratio, 1.75; P = 0.007).

CONCLUSIONS

COVID-19 patients do not demonstrate significant racial/ethnic disparities in case fatality, suggesting that state-wide disparities in mortality rate are rooted in infection risk rather than hospital course. Variations in admission rates by race/ethnicity across the timeline and increased ICU admission among Spanish-speaking patients demonstrate the need to pursue tailored interventions on both a community and structural level to mitigate further health disparities throughout the pandemic and after.

Statins and clinical outcomes in hospitalized COVID-19 patients with and without Diabetes Mellitus: a retrospective cohort study with propensity score matching

BACKGROUND

The pleiotropic effects of statins may reduce the severity of COVID-19 disease. This study aims to determine the association between inpatient statin use and severe disease outcomes among hospitalized COVID-19 patients, especially those with Diabetes Mellitus (DM).

RESEARCH DESIGN AND METHODS

A retrospective cohort study on hospitalized patients with confirmed COVID-19 diagnosis. The primary outcome was mortality during hospitalization. Patients were classified into statin and non-statin groups based on the administration of statins during hospitalization. Analysis included multivariable regression analysis adjusting for confounders and propensity score matching to achieve a 1:1 balanced cohort. Subgroup analyses based on presence of DM were conducted.

RESULTS

In the cohort of 922 patients, 413 had a history of DM. About 27.1% patients (n = 250) in the total cohort (TC) and 32.9% patients (n = 136) in DM cohort received inpatient statins. Atorvastatin (n = 205, 82%) was the most commonly prescribed statin medication in TC. On multivariable analysis in TC, inpatient statin group had reduced mortality compared to the non-statin group (OR, 0.61; 95% CI, 0.42-0.90; p = 0.01). DM modified this association between inpatient statins and mortality. Patients with DM who received inpatient statins had reduced mortality (OR, 0.35; 95% CI, 0.21-0.61; p < 0.001). However, no such association was noted among patients without DM (OR, 1.21; 95% CI, 0.67-2.17; p = 0.52). These results were further validated using propensity score matching.

CONCLUSIONS

Inpatient statin use was associated with significant reduction in mortality among COVID-19 patients especially those with DM. These findings support the pursuit of randomized clinical trials and inpatient statin use appears safe among COVID-19 patients.