Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study

Development, Implementation, and Evaluation of Three Outreach Events to Improve COVID-19 Vaccine Uptake Among Racial and Ethnic Minority Communities in Houston, Texas, 2022

OBJECTIVES

Lack of access to timely, accurate, and linguistically appropriate COVID-19 information has complicated the dissemination of evidence-based information and contributed to vaccine hesitancy among racial and ethnic minority groups in the United States. We developed community events that provided outreach, education, and access to COVID-19 vaccination to overcome vaccine hesitancy in these communities.

METHODS

Using spatial analysis techniques, we identified 3 communities with low vaccine uptake in Houston, Texas, in fall 2021; engaged 20 stakeholders from these communities via 4 focus groups to understand barriers to vaccination; and developed and implemented 3 COVID-19 vaccine education and outreach events tailored to the needs of these communities in January-March 2022. We used program evaluation surveys to assess attendee characteristics and satisfaction with the events. Vaccinated attendees also completed surveys on what motivated them to get vaccinated.

RESULTS

Two communities were predominantly Hispanic, and the third had an equal number of Black and Hispanic residents. Based on community stakeholder input, the study team organized 2 health fairs and 1 community festival featuring dialogue-based COVID-19 vaccine engagement in January and March 2022. Across the 3 events, a total of 865 attendees received COVID-19 education and 205 (24.0%) attendees received a COVID-19 vaccine or booster. Of 90 attendees who completed program evaluation surveys, 81 (90%) rated the outreach event as good or excellent. Of 145 attendees who completed postvaccination surveys, 132 (91%) endorsed ≥1 key program feature as motivating them to either get vaccinated or vaccinate their child that day.

CONCLUSION

Community outreach events are important strategies for disseminating information, building trust, and facilitating COVID-19 vaccine uptake.

Age and urban-rural disparities in cutaneous melanoma mortality rates in the United States during the COVID-19 pandemic

Most recent studies on the coronavirus disease 2019 (COVID-19) pandemic and cutaneous melanoma (CM) focused more on delayed diagnosis or advanced presentation. We aimed to ascertain mortality trends of CM between 2012 and 2022, focusing on the effects of the COVID-19 pandemic. In this serial population-based study, the National Vital Statistics System dataset was queried for mortality data. Excess CM-related mortality rates were estimated by calculating the difference between observed and projected mortality rates during the pandemic. Totally there were 108,853 CM-associated deaths in 2012-2022. CM-associated mortality saw a declining trend from 2012 to 2019 overall. However, it increased sharply in 2020 (ASMR 3.73 per 100,000 persons, 5.95% excess mortality), and remained high in 2021 and 2022, with the ASMRs of 3.82 and 3.81, corresponding to 11.17% and 13.20% excess mortality, respectively. The nonmetro areas had the most pronounced rise in mortality with 12.20% excess death in 2020, 15.33% in 2021 and 20.52% in 2022, corresponding to a 4-6 times excess mortality risk compared to large metro areas during the pandemic. The elderly had the most pronounced rise in mortality, but the mortality in the younger population was reduced.

A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness

OBJECTIVES

We evaluated methods for preparing electronic health record data to reduce bias before applying artificial intelligence (AI).

METHODS

We created methods for transforming raw data into a data framework for applying machine learning and natural language processing techniques for predicting falls and fractures. Strategies such as inclusion and reporting for multiple races, mixed data sources such as outpatient, inpatient, structured codes, and unstructured notes, and addressing missingness were applied to raw data to promote a reduction in bias. The raw data was carefully curated using validated definitions to create data variables such as age, race, gender, and healthcare utilization. For the formation of these variables, clinical, statistical, and data expertise were used. The research team included a variety of experts with diverse professional and demographic backgrounds to include diverse perspectives.

RESULTS

For the prediction of falls, information extracted from radiology reports was converted to a matrix for applying machine learning. The processing of the data resulted in an input of 5,377,673 reports to the machine learning algorithm, out of which 45,304 were flagged as positive and 5,332,369 as negative for falls. Processed data resulted in lower missingness and a better representation of race and diagnosis codes. For fractures, specialized algorithms extracted snippets of text around keywork "femoral" from dual x-ray absorptiometry (DXA) scans to identify femoral neck T-scores that are important for predicting fracture risk. The natural language processing algorithms yielded 98% accuracy and 2% error rate The methods to prepare data for input to artificial intelligence processes are reproducible and can be applied to other studies.

CONCLUSION

The life cycle of data from raw to analytic form includes data governance, cleaning, management, and analysis. When applying artificial intelligence methods, input data must be prepared optimally to reduce algorithmic bias, as biased output is harmful. Building AI-ready data frameworks that improve efficiency can contribute to transparency and reproducibility. The roadmap for the application of AI involves applying specialized techniques to input data, some of which are suggested here. This study highlights data curation aspects to be considered when preparing data for the application of artificial intelligence to reduce bias.

A longitudinal analysis of COVID-19 prevention strategies implemented among US K-12 public schools during the 2021-2022 school year

PURPOSE

Examine how school-based COVID-19 prevention strategy implementation varied over time, including by local characteristics.

METHODS

School administrators (n = 335) from a nationally representative sample of K-12 public schools completed four surveys assessing COVID-19 prevention strategies at two-month intervals between October 2021 and June 2022. We calculated weighted prevalence estimates by survey wave. Generalized estimating equations (GEE) were used to model longitudinal changes in strategy implementation, accounting for school and county covariates.

RESULTS

Opening doors/windows, daily cleaning, and diagnostic testing were reported by ≥ 50 % of schools at each survey wave. Several strategies were consistently implemented across the 2021-2022 school year (i.e., daily cleaning, opening doors and windows, diagnostic testing) while other strategies increased initially and then declined (i.e., contact tracing, screening testing, on-campus vaccination) or declined consistently throughout the school year (i.e., mask requirement, classroom distancing, quarantine). Although longitudinal changes in strategy implementation did not vary by school characteristics, strategy implementation varied by urban-rural classification and school level throughout the school year.

CONCLUSIONS

Strategies that were consistently implemented throughout the school year were also reported by a majority of schools, speaking toward their feasibility for school-based infection control and prevention and potential utility in future public health emergencies.

Area-Level Social Vulnerability and Severe COVID-19: A Case-Control Study Using Electronic Health Records from Multiple Health Systems in the Southeastern Pennsylvania Region

Knowledge about neighborhood characteristics that predict disease burden can be used to guide equity-based public health interventions or targeted social services. We used a case-control design to examine the association between area-level social vulnerability and severe COVID-19 using electronic health records (EHR) from a regional health information hub in the greater Philadelphia region. Severe COVID-19 cases (n = 15,464 unique patients) were defined as those with an inpatient admission and a diagnosis of COVID-19 in 2020. Controls (n = 78,600; 5:1 control-case ratio) were a random sample of individuals who did not have a COVID-19 diagnosis from the same geographic area. Retrospective data on comorbidities and demographic variables were extracted from EHR and linked to area-level social vulnerability index (SVI) data using ZIP codes. Models adjusted for different sets of covariates showed incidence rate ratios (IRR) ranging from 1.15 (95% CI, 1.13-1.17) in the model adjusted for individual-level age, sex, and marital status to 1.09 (95% CI, 1.08-1.11) in the fully adjusted model, which included individual-level comorbidities and race/ethnicity. The fully adjusted model indicates that a 10% higher area-level SVI was associated with a 9% higher risk of severe COVID-19. Individuals in neighborhoods with high social vulnerability were more likely to have severe COVID-19 after accounting for comorbidities and demographic characteristics. Our findings support initiatives incorporating neighborhood-level social determinants of health when planning interventions and allocating resources to mitigate epidemic respiratory diseases, including other coronavirus or influenza viruses.

Breast Cancer Screening and BI-RADS Scoring Trends Before and During the COVID-19 Pandemic in an Academic Safety-Net Hospital

BACKGROUND

Little is known about how the COVID-19 pandemic affected screening mammography rates and Breast Imaging Reporting and Data Systems (BI-RADS) categorizations within populations facing social and economic inequities. Our study seeks to compare trends in breast cancer screening and BI-RADS assessments in an academic safety-net patient population before and during the COVID-19 pandemic.

PATIENTS AND METHODS

Our single-center retrospective study evaluated women ≥ 18 years old with no known breast cancer diagnosis who received breast cancer screening from March 2019-September 2020. The screening BI-RADS score, completion of recommended diagnostic imaging, and diagnostic BI-RADS scores were compared between the pre-COVID-19 era (from 1 March 2019 to 19 March 2020) and COVID-19 era (from 20 March 2020 to 30 September 2020).

RESULTS

Among the 11,798 patients identified, screened patients were younger (median age 57 versus 59 years, p < 0.001) and more likely covered by private insurance (35.9% versus 32.3%, p < 0.001) during the COVID-19 era compared with the pre-COVID-19 era. During the pandemic, there was an increase in screening mammograms categorized as BI-RADS 0 compared with the pre-COVID-19 era (20% versus 14.5%, p < 0.0001). There was no statistically significant difference in rates of completion of diagnostic imaging (81.6% versus 85.4%, p = 0.764) or assignment of suspicious BI-RADS scores (BI-RADS 4-5; 79.9% versus 80.8%, p = 0.762) between the two eras.

CONCLUSIONS

Although more patients were recommended to undergo diagnostic imaging during the pandemic, there were no significant differences in race, completion of diagnostic imaging, or proportions of mammograms categorized as suspicious between the two time periods. These findings likely reflect efforts to maintain equitable care among diverse racial groups served by our safety-net hospital.

Racism, health and pandemic: a narrative review of the relationship between black population and COVID-19 events in 2020

This study aimed to analyze how scientific publications described and interpreted findings about the relationship between the Black population and events linked to COVID-19 in 2020. Narrative review with systematic search, in which a survey was conducted on articles published in 2020 in the Scopus, Medline/PubMed, and Web of Science databases. Initially, 665 articles were found, and after reading and applying the eligible criteria, the final number of 45 articles was reached. Epidemiological, observational studies, secondary data and developed in the United States predominated. Four groupings and respective findings emerged from the synthesis of information extracted: Main events in the Black population - high number of deaths and mortality rate; Direct relationships - poor health, housing, and work conditions; Intermediate relationships - low income and anti-Black prejudice; Comprehensive relationships - structural racism and social determinants of health. The identification of racial health disparities is an important finding about the dynamics of the pandemic among the Black population. However, multicausal explanations were limited. It is necessary to mobilize critical theoretical resources from ethnic and health studies to qualify research in order to support global actions to combat the SARS-CoV-2 epidemic in this group.

The American Heart Association Emergency Cardiovascular Care 2030 Impact Goals and Call to Action to Improve Cardiac Arrest Outcomes: A Scientific Statement From the American Heart Association

Every 10 years, the American Heart Association (AHA) Emergency Cardiovascular Care Committee establishes goals to improve survival from cardiac arrest. These goals align with broader AHA Impact Goals and support the AHA's advocacy efforts and strategic investments in research, education, clinical care, and quality improvement programs. This scientific statement focuses on 2030 AHA emergency cardiovascular care priorities, with a specific focus on bystander cardiopulmonary resuscitation, early defibrillation, and neurologically intact survival. This scientific statement also includes aspirational goals, such as establishing cardiac arrest as a reportable disease and mandating reporting of standardized outcomes from different sources; advancing recognition of and knowledge about cardiac arrest; improving dispatch system response, availability, and access to resuscitation training in multiple settings and at multiple time points; improving availability, access, and affordability of defibrillators; providing a focus on early defibrillation, in-hospital programs, and establishing champions for debriefing and review of cardiac arrest events; and expanding measures to track outcomes beyond survival. The ability to track and report data from these broader aspirational targets will potentially require expansion of existing data sets, development of new data sets, and enhanced integration of technology to collect process and outcome data, as well as partnerships of the AHA with national, state, and local organizations. The COVID-19 (coronavirus disease 2019) pandemic, disparities in COVID-19 outcomes for historically excluded racial and ethnic groups, and the longstanding disparities in cardiac arrest treatment and outcomes for Black and Hispanic or Latino populations also contributed to an explicit focus and target on equity for the AHA Emergency Cardiovascular Care 2030 Impact Goals.

The Association of Vaccination for Common Adult Infectious Diseases and Uptake of COVID-19 Vaccines among 5,006,851 Veterans, 20 December 2020-31 October 2021

Disparities in vaccination coverage for coronavirus disease 2019 (COVID-19) in the United States (U.S.) are consistent barriers limiting our ability to control the spread of disease, particularly those by age and race/ethnicity. This study examines the association between previous vaccination for common adult infectious diseases and vaccination for SARS-CoV-2 among a cohort of veterans in the U.S. Sociodemographic and clinical data were utilized from three databases within the Veterans Health Administration included in the electronic health record. We examined the association of previous vaccination for common adult vaccinations through six separate multivariable logistic regression analyses, one for each previous vaccine exposure, adjusting for demographic and clinical variables. We also examined the association of receiving any one of the six common adult vaccinations and vaccination against SARS-CoV-2. Adjusted models indicate higher odds of vaccination for SARS-CoV-2 among those who received each of the previous vaccinations. Significant differences were also noted by race/ethnicity and age. Veterans who recorded receiving any one of the previous vaccinations for common adult infections had significantly greater odds of receiving any vaccination against SARS-CoV-2. Understanding veterans' previous vaccination status can assist researchers and clinicians in impacting the uptake of novel vaccines, such as vaccination against SARS-CoV-2.

Predictors of later COVID-19 test seeking

Background

Delays in COVID-19 testing may increase the risk of secondary household and community transmission. Little is known about what patient characteristics and symptom profiles are associated with delays in test seeking.

Methods

We conducted a retrospective cohort study of all symptomatic patients diagnosed with COVID-19 and assessed in a COVID Expansion to Outpatients (COVIDEO) virtual care program between March 2020 and June 2021. The primary outcome was later test seeking more than 3 days from symptom onset. Multivariable logistic regression was used to examine predictors of later testing including patient characteristics and symptoms (30 individual symptoms or 7 symptom clusters).

Results

Of 5,363 COVIDEO patients, 4,607 were eligible and 2,155/4,607 (46.8%) underwent later testing. Older age was associated with increased odds of late testing (adjusted odds ratio [aOR] 1.007/year; 95% CI 1.00 to 1.01), as was history of recent travel (aOR 1.4; 95% CI 1.01 to 1.95). Health care workers had lower odds of late testing (aOR 0.50; 95% CI 0.39 to 0.62). Late testing was associated with symptoms in the cardiorespiratory (aOR 1.2; 95% CI 1.05, 1.36), gastrointestinal (aOR = 1.2; 95% CI 1.04, 1.4), neurological (aOR 1.1; 95% CI 1.003, 1.3) and psychiatric (aOR 1.3; 95% CI 1.1, 1.5) symptom clusters. Among individual symptoms, dyspnea, anosmia, dysgeusia, sputum, and anorexia were associated with late testing; pharyngitis, myalgia, and headache were associated with early testing.

Conclusion

Certain patient characteristics and symptoms are associated with later testing, and warrant further efforts to encourage earlier testing to minimize transmission.

Excess mortality in US Veterans during the COVID-19 pandemic: an individual-level cohort study

BACKGROUND

Most analyses of excess mortality during the COVID-19 pandemic have employed aggregate data. Individual-level data from the largest integrated healthcare system in the US may enhance understanding of excess mortality.

METHODS

We performed an observational cohort study following patients receiving care from the Department of Veterans Affairs (VA) between 1 March 2018 and 28 February 2022. We estimated excess mortality on an absolute scale (i.e. excess mortality rates, number of excess deaths) and a relative scale by measuring the hazard ratio (HR) for mortality comparing pandemic and pre-pandemic periods, overall and within demographic and clinical subgroups. Comorbidity burden and frailty were measured using the Charlson Comorbidity Index and Veterans Aging Cohort Study Index, respectively.

RESULTS

Of 5 905 747 patients, the median age was 65.8 years and 91% were men. Overall, the excess mortality rate was 10.0 deaths/1000 person-years (PY), with a total of 103 164 excess deaths and pandemic HR of 1.25 (95% CI 1.25-1.26). Excess mortality rates were highest among the most frail patients (52.0/1000 PY) and those with the highest comorbidity burden (16.3/1000 PY). However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46).

CONCLUSIONS

Individual-level data offered crucial clinical and operational insights into US excess mortality patterns during the COVID-19 pandemic. Notable differences emerged among clinical risk groups, emphasizing the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.

Demographic Characteristics of Unvaccinated Asymptomatic and Symptomatic SARS-CoV-2 Cases in Barwon South West, Victoria, Australia

We investigated 328 SARS-CoV-2 cases in Barwon South West, Victoria, Australia, in the 2020 pre-vaccination period, comparing infections with symptoms to those that remained asymptomatic. De-identified self-reported data on case characteristics and symptom progression from three sequential questionnaires were examined. Multivariable logistic regression was used to model associations between demographic profiles and symptoms. Asymptomatic infections were more than three times as likely to be seen in ethnic minority groups than the Caucasian population after adjusting for gender and age [OR 3.2, 95% CI 1.5-6.7, p < 0.01] and were more common among cases of Asian background [OR 2.8, 95%CI 1.2-6.4]. Asymptomatic infections were also more common in youth and younger adults, but cases were approximately seven times more likely to be in seniors (≥65 years) compared with those 24 years of age or younger after adjusting for sex and ethnicity [OR 6.9, 95% CI 1.3-35.8]. The overrepresentation of ethnic minority groups among asymptomatic infections is suggestive of genetic haplotype variability by ethnic group, conferring greater cross-protection from other coronaviruses in the initial phase of the COVID-19 pandemic. Replication of this analysis in the post-vaccination era and reassessment of symptom expression according to ethnicity in a community with established vaccine and infection-induced immunity would determine whether this is a sustained association or one confined to the early stages of a pandemic in an immunologically naive population. These findings may, in part, reflect differences in testing patterns by ethnicity and true differences in disease expression, both of which are important to understand in order to inform transmission prevention strategies and tailored risk messaging according to ethnic background.

Development of a Novel Clinical Risk Score for COVID-19 Infections

OBJECTIVE

The ongoing emergence of novel severe acute respiratory syndrome coronavirus 2 strains such as the Omicron variant amplifies the need for precision in predicting severe COVID-19 outcomes. This study presents a machine learning model, tailored to the evolving COVID-19 landscape, emphasizing novel risk factors and refining the definition of severe outcomes to predict the risk of a patient experiencing severe disease more accurately.

METHODS

Utilizing electronic health records from the Healthjump database, this retrospective study examined over 1 million US COVID-19 diagnoses from March 2020 to September 2022. Our model predicts severe outcomes, including acute respiratory failure, intensive care unit admission, or ventilator use, circumventing biases associated with hospitalization, which exhibited ∼4× geographical variance of the new outcome.

RESULTS

The model exceeded similar predictors with an area under the curve of 0.83 without lab data to predict patient risk. It identifies new risk factors, including acute care history, health care encounters, and distinct medication use. An increase in severe outcomes, typically 2-3× higher than subsequent months, was observed at the onset of each new strain era, followed by a plateau phase, but the risk factors remain consistent across strain eras.

CONCLUSION

We offer an improved machine learning model and risk score for predicting severe outcomes during changing COVID-19 strain eras. By emphasizing a more clinically precise definition of severe outcomes, the study provides insights for resource allocation and intervention strategies, aiming to better patient outcomes and reduce health care strain. The necessity for regular model updates is highlighted to maintain relevance amidst the rapidly evolving COVID-19 epidemic.

Determinants of SARS-CoV-2 nasopharyngeal testing in a rural community sample susceptible of first infection: the CHRIS COVID-19 study

To characterize COVID-19 epidemiology, numerous population-based studies have been undertaken to model the risk of SARS-CoV-2 infection. Less is known about what may drive the probability to undergo testing. Understanding how much testing is driven by contextual or individual conditions is important to delineate the role of individual behavior and to shape public health interventions and resource allocation. In the Val Venosta/Vinschgau district (South Tyrol, Italy), we conducted a population-representative longitudinal study on 697 individuals susceptible to first infection who completed 4,512 repeated online questionnaires at four-week intervals between September 2020 and May 2021. Mixed-effects logistic regression models were fitted to investigate associations of self-reported SARS-CoV-2 testing with individual characteristics (social, demographic, and biological) and contextual determinants. Testing was associated with month of reporting, reflecting the timing of both the pandemic intensity and public health interventions, COVID-19-related symptoms (odds ratio, OR:8.26; 95% confidence interval, CI:6.04-11.31), contacts with infected individuals within home (OR:7.47, 95%CI:3.81-14.62) or outside home (OR:9.87, 95%CI:5.78-16.85), and being retired (OR:0.50, 95%CI:0.34-0.73). Symptoms and next within- and outside-home contacts were the leading determinants of swab testing predisposition in the most acute phase of the pandemics. Testing was not associated with age, sex, education, comorbidities, or lifestyle factors. In the study area, contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining the SARS-CoV-2 probability of testing. Decision makers should evaluate whether the intended target groups were correctly prioritized by the testing campaign.

A bioinformatic analysis: Previous allergen exposure may support anti- SARS-CoV-2 immune response

COVID-19, caused by infection with the SARS-CoV-2 has become a global health problem due to significant mortality rates; the exact pathophysiological mechanism remains uncertain. Articles reporting patient data are quite heterogeneous and have several limitations. Surviving patients develop a CD4 and CD8 T-cell response to the virus SARS-CoV-2 during COVID-19. Interestingly, pre-existing virus-reactive T-cells have been found in patients that were not infected before, suggesting some form of cross-reactivity or immunological mimicry. To better understand this phenomenon, we performed a bioinformatic study, which was aimed to identify antigenic structures that may explain the presence of such "reactive" T-cells, which may support or modulate the immune response to SARS-CoV-2 infections. Seven different common environmental allergen epitopes identical to the SARS-CoV-2 S-protein were identified that share affinity to 8 MHCI-specific epitope regions. Pollen showed the greatest similarity with the S protein epitope. In the epitope similarity analysis between the S protein and MHC-II / T helper epitopes, the highest similarity was determined for mites. When S-protein that stimulates B cells and identical epitope antigens are examined, the most common allergens were hornbeam and wheat. The high epitope similarity observed for the allergens examined and S protein epitopes suggest that these allergens may be a reason for pre-existing SARS-CoV-2 - reactive T-cells in previously non-infected subjects and such a previous exposure may affect the course of the disease in COVID-19 infection. It remains to be determined whether such a previous existence of SARS-CoV-2 reactive cells can support the clearance of the virus or if they, in contrast, may even aggravate the disease course. (Table 4, Ref 54).

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic

The COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of 'experimentation' in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of 'team science', the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a 'call to actions' for both policy-makers and researchers.

Space-time clustering of COVID-19 cases in the United States veteran population

PURPOSE

To assess the distribution and clustering of coronavirus disease 2019 (COVID-19) testing and incidence over space and time, U.S. Department of Veteran's Affairs (VA) data were used to describe where and when veterans experienced highest proportions of test positivity.

METHODS

Data for 6,342,455 veterans who utilized VA services between January 1, 2018, and September 30, 2021, were assessed for COVID-19 testing and test positivity. Testing and positivity proportions by county were mapped and focused-cluster tests identified significant clustering around VA facilities. Spatial cluster analysis also identified where and when veterans experienced highest proportions of test positivity.

RESULTS

Within the veterans study population and our time window, 21.3% received at least one COVID-19 test, and 20.4% of those tested had at least one positive test. There was statistically significant clustering of testing around VA facilities, revealing regional variation in testing practices. Veterans experienced highest test positivity proportions between November 2020 and January 2021 in a cluster of states in the Midwest, compared to those who received testing outside of the identified cluster (RR: 3.45).

CONCLUSIONS

Findings reflect broad regional trends in COVID-19 positivity which can inform VA policy and resource allocation. Additional analysis is needed to understand patterns during Delta and Omicron variant periods.

Leveraging the Million Veteran Program Infrastructure and Data for a Rapid Research Response to COVID-19

Background

The Veterans Health Administration Office of Research and Development (ORD) played a key role in the federal government's response to the COVID-19 pandemic. The ORD effectively leveraged existing resources to answer questions related to the SARS-CoV-2 virus and COVID-19.

Observations

When the COVID-19 pandemic hit in 2020, the Million Veteran Program (MVP), one of the largest genomic cohorts in the world, extended the centralized recruitment and enrollment infrastructure to develop a COVID-19 research volunteer registry to assist enrollment in the vaccine and treatment trials in which the US Department of Veterans Affairs (VA) participated. In addition, the MVP allowed for new data collection and a large genomic cohort to understand host contributions to COVID-19. This article describes ways the MVP contributed to the VA's rapid research response to COVID-19. Several host genetic factors believed to play a role in the development and severity of COVID-19 were identified. Furthermore, existing MVP partnerships with other federal agencies, particularly with the Department of Energy, were leveraged to improve understanding and management of COVID-19.

Conclusions

A previously established enterprise approach and research infrastructure were essential to the VA's successful and timely COVID-19 research response. This infrastructure not only supported rapid recruitment in vaccine and treatment trials, but also leveraged the unique MVP and VA electronic health record data to drive rapid scientific discovery and inform clinical operations. Extending the models that VA research applied to the federal government at large and establishing centralized resources for shared or federated data analyses across federal agencies will better equip the nation to respond to future public health crises.

The Social, Demographic, and Clinical Predictors of COVID-19 Severity: a Model-based Analysis of United States Veterans

PURPOSE

This study aims to identify the contributions of individual and community social determinants of health (SDOH), demographic, and clinical factors in COVID-19 disease severity through a model-based analysis.

METHODS

This national cross-sectional study focused on hospitalization among those tested for COVID-19 and use of intensive care, analyzing data on 220,848 Veterans tested between February 20, 2020 and October 20, 2021. Multiple logistic regression models were constructed using backwards elimination. The predictive value of each model was assessed with a c-statistic.

RESULTS

Those hospitalized were older, more likely to be male, of Black or Asian race, have an income less than $39,999, live in an urban residence, and have medical comorbidities. The strongest predictors for hospitalization included Gini inequality index, race, income, heart failure, chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD). For intensive care, Asian race, rural residence, COPD, and CKD were the strongest predictors. C-statistics were c = 0.749 for hospitalization and c = 0.582 for ICU admission.

CONCLUSIONS

A combination of clinical, demographic, individual and community SDOH factors predict COVID-19 hospitalization with good predictive ability and can inform risk stratification, discharge planning, and public health interventions. Racial disparities were not explained by social or clinical factors. Intensive care models had low discriminative power and may be better explained by other characteristics.

Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counterfactual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American-Indian or Alaska-Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

Evaluation of the Association Between Sociodemographic Status and Breast Screening Volumes During the COVID-19 Pandemic in a Provincial, Population-Based Organized Breast Screening Program

OBJECTIVES

We sought to evaluate the association between patient sociodemographic status and breast screening volumes (BSVs) during the COVID-19 pandemic in a large, population-based breast screening program that serves a provincial population of over 5 million.

METHODS

All patients who completed breast screening between April 1st, 2017 and March 31st, 2021 were eligible to participate. An average of 3 annual periods between April 1st, 2017 and March 31st, 2020 were defined as the pre-COVID period while the period between April 1st, 2020 and March 31st, 2021 was defined as the COVID-impacted period. The Postal CodeOM Conversion File Plus was applied to map patient residential postal codes to 2016 census standard geographical areas, which provided information on community size, income quintile and dissemination areas. Dissemination areas were subsequently linked to the Canadian Index of Multiple Deprivation (CIMD).

RESULTS

Overall BSV was reduced by 23.0% during the COVID-impacted period as compared to the pre-COVID period. Percent reductions in BSVs were greatest among younger patients aged 40 to 49 years (31.3%) and patients residing in communities with a population of less than 10,000 (27.0%). Percent reduction in BSV was greatest among patients in the lowest income quintile (28.1%). Percent reductions in BSVs were greatest for patients in the most deprived quintiles across all 4 dimensions of the CIMD.

CONCLUSION

Disproportionate reductions in BSVs were observed during the COVID-19 pandemic among younger patients, patients residing in rural communities, patients in lower income quintiles, and patients in the most deprived quintiles across all 4 dimensions of the CIMD.

Socio-Economic Factors Associated with Ethnic Disparities in SARS-CoV-2 Infection and Hospitalization

BACKGROUND

There is evidence that non-Italians presented higher incidence of infection and worse health outcomes if compared to native populations in the COVID-19 pandemic. The aim of the study was to compare Italian- and non-Italian-born health outcomes, accounting for socio-economic levels.

METHODS

We analyzed data relative to 906,463 people in Umbria (Italy) from 21 February 2020 to 31 May 2021. We considered the National Deprivation Index, the Urban-Rural Municipalities Index and the Human Development Index (HDI) of the country of birth. We used a multilevel logistic regression model to explore the influence of these factors on SARS-CoV-2 infection and hospitalization rates. Diagnosis in the 48 h preceding admission was an indicator of late diagnosis among hospitalized cases.

RESULTS

Overall, 54,448 persons tested positive (6%), and 9.7% of them were hospitalized. The risk of hospital admission was higher among non-Italians and was inversely related to the HDI of the country of birth. A diagnosis within 48 h before hospitalization was more frequent among non-Italians and correlated to the HDI level.

CONCLUSIONS

COVID-19 had unequal health outcomes among the population in Umbria. Reduced access to primary care services in the non-Italian group could explain our findings. Policies on immigrants' access to primary healthcare need to be improved.

Perceived COVID-19 risk and testing experiences in the San Ysidro U.S./Mexico border region

Racial and ethnic disparities in COVID-19 incidence are pronounced in underserved U.S./Mexico border communities. Working and living environments in these communities can lead to increased risk of COVID-19 infection and transmission, and this increased risk is exacerbated by lack of access to testing. As part of designing a community and culturally tailored COVID-19 testing program, we surveyed community members in the San Ysidro border region. The purpose of our study was to characterize knowledge, attitudes, and beliefs of prenatal patients, prenatal caregivers, and pediatric caregivers at a Federally Qualified Health Center (FHQC) in the San Ysidro region regarding perceived risk of COVID-19 infection and access to testing. A cross-sectional survey was used to collect information on experiences accessing COVID-19 testing and perceived risk of COVID-19 infection within San Ysidro between December 29, 2020 and April 2, 2021. A total of 179 surveys were analyzed. Most participants identified as female (85%) and as Mexican/Mexican American (75%). Over half (56%) were between the age of 25 and 34 years old. Perceived Risk: 37% reported moderate to high risk of COVID-19 infection, whereas 50% reported their risk low to none. Testing Experience: Approximately 68% reported previously being tested for COVID-19. Among those tested, 97% reported having very easy or easy access to testing. Reasons for not testing included limited appointment availability, cost, not feeling sick, and concern about risk of infection while at a testing facility. This study is an important first step to understand the COVID-19 risk perceptions and testing access among patients and community members living near the U.S./Mexico border in San Ysidro, California.

Decrease in Overall Vaccine Hesitancy in College Students during the COVID-19 Pandemic

The COVID-19 pandemic changed our world as we know it and continues to be a global problem three years since the pandemic began. Several vaccines were produced, but there was a considerable amount of societal turmoil surrounding them that has affected the way people view not only COVID-19 vaccines but all vaccines. We used a survey to compare how attitudes towards vaccination have changed in college students during the pandemic. An initial survey was administered in 2021, then a follow-up in 2022. Out of 316 respondents who answered the first survey, 192 completed the follow-up. The survey was designed to measure trends in changes to vaccine attitudes since the COVID-19 pandemic began. By comparing the first survey in 2021 and the follow-up, we found that roughly 55% of respondents' vaccine attitudes did not change, roughly 44% of respondents' attitudes towards vaccines became more positive, and only about 1% of the respondents' vaccine attitudes became more negative. Improved view of vaccines was associated with political views and increased trust in medicine and the healthcare system. Worsened opinions of vaccines were associated with a belief that the COVID-19 vaccine affected fertility.

Associations Between Insurance, Race and Ethnicity, and COVID-19 Hospitalization, Beyond Underlying Health Conditions: A Retrospective Cohort Study

Introduction

: People of lower socioeconomic position (SEP) and people of color (POC) experience higher risks of severe COVID-19, but understanding of these associations beyond the effect of underlying health conditions (UHCs) is limited. Moreover, few studies have focused on young adults, who have had the highest incidence of COVID-19 during much of the pandemic.

Methods

: We conducted a retrospective cohort study using electronic health record data from the University of Washington Medicine healthcare system. Our study population included individuals aged 18-39 years who tested positive for SARS-CoV-2 from February 2020 to March 2021. Using regression modeling, we estimated adjusted risk ratios (aRRs) and differences (aRDs) of COVID-19 hospitalization by SEP (using health insurance as a proxy) and race and ethnicity. We adjusted for any UHC to examine these associations beyond the effect of UHCs. Results: Among 3,101 individuals, the uninsured/publicly insured had a 1.9-fold higher risk of hospitalization (aRR [95% CI]=1.9 [1.0, 3.6]) and 9 additional hospitalizations per 1,000 SARS-CoV-2 positive persons (aRD [95% CI]=9 [-1, 20]) compared to the privately insured. Hispanic or Latine, non-Hispanic (NH) Asian, NH Black, and NH Native Hawaiian or Pacific Islander patients had a 1.5-, 2.7-, 1.4-, and 2.1-fold-higher risk of hospitalization (aRR [95% CI]=1.5 [0.7, 3.1]; 2.7 [1.1, 6.5]; 1.4 [0.6, 3.3]; 2.1 [0.5, 9.1]), respectively, compared to NH White patients. Conclusions: Though they should be interpreted with caution given low precision, our findings suggest the increased risk of COVID-19 hospitalization among young adults of lower SEP and young adults of color may be driven by forces other than UHCs, including social determinants of health.

Cross-sectional study examining household factors associated with SARS-CoV-2 seropositivity in low-income children in Los Angeles

OBJECTIVES

This study aims to quantify the degree to which an underserved, Hispanic population in Los Angeles is impacted by SARS-CoV-2, and determine factors associated with paediatric seropositivity.

DESIGN

Cross-sectional.

SETTING

AltaMed, a Federally Qualified Health Center in Los Angeles.

PARTICIPANTS

A random sample of households who had received healthcare at AltaMed Medical Group was invited to participate. Households with at least one adult and one paediatric participant between 5 and 17 years of age were eligible to participate. Consented participants completed a survey on social determinants of health and were tested for antibodies using Abbott Architect SARS-CoV-2-IgG and SARS-CoV-2-IgM tests.

PRIMARY OUTCOME MEASURE

Seropositive status.

RESULTS

We analysed 390 adults (mean age in years, 38.98 (SD 12.11)) and 332 paediatric participants (11.26 (SD 3.51)) from 196 households. Estimated seropositivity was 52.11% (95% CI 49.61% to 55.19%) in paediatric participants and 63.58% (95% CI 60.39% to 65.24%) in adults. Seropositivity was 11.47% (95% CI 6.82% to 14.09%) lower in paediatric participants, but high relative to other populations. A household member with type 2 diabetes (OR 2.94 (95% CI 1.68 to 5.14)), receipt of food stamps (OR 1.66 (95% CI 1.08 to 2.56)) and lower head-of-household education (OR 1.73 (95% CI 1.06 to 2.84)) were associated with paediatric seropositivity.

CONCLUSIONS

SARS-CoV-2 seropositivity is high in Hispanic children and adolescents in Los Angeles. Food insecure households with low head-of-household education, and at least one household member with type 2 diabetes, had the highest risk. These factors may inform paediatrician COVID-19 mitigation recommendations.

TRIAL REGISTRATION NUMBER

NCT04901624.

VA Research and Operations Uniting to Combat COVID-19 Inequities

As novel coronavirus 2019 disease (COVID-19) began to spread across the United States in early 2020, health care systems faced extreme demands on resources. As the country's largest single-payer health care system, the U.S. Department of Veterans Affairs (VA) was uniquely positioned to study how the virus impacted different communities and work to improve care provided to all. Early on, a literature review of prior epidemics revealed that occupational exposures and an inability to socially distance could impact some groups more than others. The VA's Office of Health Equity leveraged a general sense of community to create a collaborative research space and a dedicated analytic space to inform pandemic operations. VA researchers and operations staff were able to quickly share information and respond to updates to produce accurate and reliable publications for medical professionals and the general public. Partnerships with VA Medical Centers and Veteran Service Organizations helped to increase communication across the nation and determine the most critical needs. Although COVID-19 was dynamic in nature, VA's intentional examination of social and structural factors was crucial in informing a more equitable approach. Moving forward, these inequities must be intentionally addressed in future pandemic responses.

Identity and COVID-19 in Canada: Gender, ethnicity, and minority status

BACKGROUND

During the COVID-19 pandemic, growing evidence from the United States, the United Kingdom, and China has demonstrated the unequal social and economic burden of this health crisis. Yet, in Canada, studies assessing the socioeconomic and demographic determinants of COVID-19, and how these determinants vary by gender and ethnic minority status, remain scarce. As new strains of COVID-19 emerge, it is important to understand the disparities to be able to initiate policies and interventions that target and prioritise the most at-risk sub-populations.

AIM

The objective of this study is to assess the socioeconomic and demographic factors associated with COVID-19-related symptoms in Canada, and how these determinants vary by identity factors including gender and visible minority status.

METHODS

We implemented an online survey and collected a nationally representative sample of 2,829 individual responses. The original data collected via the SurveyMonkey platform were analysed using a cross-sectional study. The outcome variables were COVID-19-related symptoms among respondents and their household members. The exposure variables were socioeconomic and demographic factors including gender and ethnicity as well as age, province, minority status, level of education, total annual income in 2019, and number of household members. Descriptive statistics, chi-square tests, and multivariable logistic regression analyses were performed to test the associations. The results were presented as adjusted odds ratios (aORs) at p < 0.05 and a 95% confidence interval.

RESULTS

We found that the odds of having COVID-19-related symptoms were higher among respondents who belong to mixed race [aOR = 2.77; CI = 1.18-6.48] and among those who lived in provinces other than Ontario and Quebec [aOR = 1.88; CI = 1.08-3.28]. There were no significant differences in COVID-19 symptoms between males and females, however, we did find a significant association between the province, ethnicity, and reported COVID-19 symptoms for female respondents but not for males. The likelihood of having COVID-19-related symptoms was also lower among respondents whose total income was $100,000 or more in 2019 [aOR = 0.18; CI = 0.07-0.45], and among those aged 45-64 [aOR = 0.63; CI = 0.41-0.98] and 65-84 [aOR = 0.42; CI = 0.28-0.64]. These latter associations were stronger among non-visible minorities. Among visible minorities, being black or of the mixed race and living in Alberta were associated with higher odds of COVID-19-related symptoms.

CONCLUSION

We conclude that ethnicity, age, total income in 2019, and province were significantly associated with experiencing COVID-19 symptoms in Canada. The significance of these determinants varied by gender and minority status. Considering our findings, it will be prudent to have COVID-19 mitigation strategies including screening, testing, and other prevention policies targeted toward the vulnerable populations. These strategies should also be designed to be specific to each gender category and ethnic group, and to account for minority status.

Retrospective Analysis of Equity-Based Optimization for COVID-19 Vaccine Allocation

Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counter-factual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American Indian or Alaska Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

Excess Mortality Among Patients in the Veterans Affairs Health System Compared With the Overall US Population During the First Year of the COVID-19 Pandemic

Importance

During the first year of the COVID-19 pandemic, there was a substantial increase in the rate of death in the United States. It is unclear whether those who had access to comprehensive medical care through the Department of Veterans Affairs (VA) health care system had different death rates compared with the overall US population.

Objective

To quantify and compare the increase in death rates during the first year of the COVID-19 pandemic between individuals who received comprehensive medical care through the VA health care system and those in the general US population.

Design, Setting, and Participants

This cohort study compared 10.9 million enrollees in the VA, including 6.8 million active users of VA health care (those with a visit in the last 2 years), with the general population of the US, with deaths occurring from January 1, 2014, to December 31, 2020. Statistical analysis was conducted from May 17, 2021, to March 15, 2023.

Main Outcomes and Measures

Changes in rates of death from any cause during the COVID-19 pandemic in 2020 compared with previous years. Changes in all-cause death rates by quarter were stratified by age, sex, race and ethnicity, and region, based on individual-level data. Multilevel regression models were fit in a bayesian setting. Standardized rates were used for comparison between populations.

Results

There were 10.9 million enrollees in the VA health care system and 6.8 million active users. The demographic characteristics of the VA populations were predominantly male (>85% in the VA health care system vs 49% in the general US population), older (mean [SD], 61.0 [18.2] years in the VA health care system vs 39.0 [23.1] years in the US population), and had a larger proportion of patients who were White (73% in the VA health care system vs 61% in the US population) or Black (17% in the VA health care system vs 13% in the US population). Increases in death rates were apparent across all of the adult age groups (≥25 years) in both the VA populations and the general US population. Across all of 2020, the relative increase in death rates compared with expected values was similar for VA enrollees (risk ratio [RR], 1.20 [95% CI, 1.14-1.29]), VA active users (RR, 1.19 [95% CI, 1.14-1.26]), and the general US population (RR, 1.20 [95% CI, 1.17-1.22]). Because the prepandemic standardized mortality rates were higher in the VA populations prior to the pandemic, the absolute rates of excess mortality were higher in the VA populations.

Conclusions and Relevance

In this cohort study, a comparison of excess deaths between populations suggests that active users of the VA health system had similar relative increases in mortality compared with the general US population during the first 10 months of the COVID-19 pandemic.

Prior SARS-CoV-2 infection and COVID-19 vaccine effectiveness against outpatient illness during widespread circulation of SARS-CoV-2 Omicron variant, US Flu VE network

BACKGROUND

We estimated combined protection conferred by prior SARS-CoV-2 infection and COVID-19 vaccination against COVID-19-associated acute respiratory illness (ARI).

METHODS

During SARS-CoV-2 Delta (B.1.617.2) and Omicron (B.1.1.529) variant circulation between October 2021 and April 2022, prospectively enrolled adult patients with outpatient ARI had respiratory and filter paper blood specimens collected for SARS-CoV-2 molecular testing and serology. Dried blood spots were tested for immunoglobulin-G antibodies against SARS-CoV-2 nucleocapsid (NP) and spike protein receptor binding domain antigen using a validated multiplex bead assay. Evidence of prior SARS-CoV-2 infection also included documented or self-reported laboratory-confirmed COVID-19. We used documented COVID-19 vaccination status to estimate vaccine effectiveness (VE) by multivariable logistic regression by prior infection status.

RESULTS

Four hundred fifty-five (29%) of 1577 participants tested positive for SARS-CoV-2 infection at enrollment; 209 (46%) case-patients and 637 (57%) test-negative patients were NP seropositive, had documented previous laboratory-confirmed COVID-19, or self-reported prior infection. Among previously uninfected patients, three-dose VE was 97% (95% confidence interval [CI], 60%-99%) against Delta, but not statistically significant against Omicron. Among previously infected patients, three-dose VE was 57% (CI, 20%-76%) against Omicron; VE against Delta could not be estimated.

CONCLUSIONS

Three mRNA COVID-19 vaccine doses provided additional protection against SARS-CoV-2 Omicron variant-associated illness among previously infected participants.

Ursodeoxycholic acid is associated with a reduction in SARS-CoV-2 infection and reduced severity of COVID-19 in patients with cirrhosis

BACKGROUND AND AIMS

Studies have demonstrated that reducing farnesoid X receptor activity with ursodeoxycholic acid (UDCA) downregulates angiotensin-converting enzyme in human lung, intestinal and cholangiocytes organoids in vitro, in human lungs and livers perfused ex situ, reducing internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the host cell. This offers a potential novel target against coronavirus disease 2019 (COVID-19). The objective of our study was to compare the association between UDCA exposure and SARS-CoV-2 infection, as well as varying severities of COVID-19, in a large national cohort of participants with cirrhosis.

METHODS

In this retrospective cohort study among participants with cirrhosis in the Veterans Outcomes and Costs Associated with Liver cohort, we compared participants with exposure to UDCA, with a propensity score (PS) matched group of participants without UDCA exposure, matched for clinical characteristics, and vaccination status. The outcomes included SARS-CoV-2 infection, symptomatic, at least moderate, severe, or critical COVID-19, and COVID-19-related death.

RESULTS

We compared 1607 participants with cirrhosis who were on UDCA, with 1607 PS-matched controls. On multivariable logistic regression, UDCA exposure was associated with reduced odds of developing SARS-CoV-2 infection (adjusted odds ratio [aOR] 0.54, 95% confidence interval [CI] 0.41-0.71, p < 0.0001). Among patients who developed COVID-19, UDCA use was associated with reduced disease severity, including symptomatic COVID-19 (aOR 0.54, 95% CI 0.39-0.73, p < 0.0001), at least moderate COVID-19 (aOR 0.51, 95% CI 0.32-0.81, p = 0.005), and severe or critical COVID-19 (aOR 0.48, 95% CI 0.25-0.94, p = 0.03).

CONCLUSIONS

In participants with cirrhosis, UDCA exposure was associated with both a decrease in SARS-CoV-2 infection, and reduction in symptomatic, at least moderate, and severe/critical COVID-19.

Racial, Ethnic, and Rural Disparities in US Veteran COVID-19 Vaccine Rates

Background

Race, ethnicity, and rurality-related disparities in coronavirus disease 2019 (COVID-19) vaccine uptake have been documented in the United States (US).

Objective

We determined whether these disparities existed among patients at the Department of Veterans Affairs (VA), the largest healthcare system in the US.

Design Settings Participants Measurements

Using VA Corporate Data Warehouse data, we included 5,871,438 patients (9.4% women) with at least one primary care visit in 2019 in a retrospective cohort study. Each patient was assigned a single race/ethnicity, which were mutually exclusive, self-reported categories. Rurality was based on 2019 home address at the zip code level. Our primary outcome was time-to-first COVID-19 vaccination between December 15, 2020-June 15, 2021. Additional covariates included age (in years), sex, geographic region (North Atlantic, Midwest, Southeast, Pacific, Continental), smoking status (current, former, never), Charlson Comorbidity Index (based on ≥1 inpatient or two outpatient ICD codes), service connection (any/none, using standardized VA-cutoffs for disability compensation), and influenza vaccination in 2019-2020 (yes/no).

Results

Compared with unvaccinated patients, those vaccinated (n=3,238,532; 55.2%) were older (mean age in years vaccinated=66.3, (standard deviation=14.4) vs. unvaccinated=57.7, (18.0), p<.0001)). They were more likely to identify as Black (18.2% vs. 16.1%, p<.0001), Hispanic (7.0% vs. 6.6% p<.0001), or Asian American/Pacific Islander (AA/PI) (2.0% vs. 1.7%, P<.0001). In addition, they were more likely to reside in urban settings (68.0% vs. 62.8, p<.0001). Relative to non-Hispanic White urban Veterans, the reference group for race/ethnicity-urban/rural hazard ratios reported, all urban race/ethnicity groups were associated with increased likelihood for vaccination except American Indian/Alaskan Native (AI/AN) groups. Urban Black groups were 12% more likely (Hazard Ratio (HR)=1.12 [CI 1.12-1.13]) and rural Black groups were 6% more likely to receive a first vaccination (HR=1.06 [1.05-1.06]) relative to white urban groups. Urban Hispanic, AA/PI and Mixed groups were more likely to receive vaccination while rural members of these groups were less likely (Hispanic: Urban HR=1.17 [1.16-1.18], Rural HR=0.98 [0.97-0.99]; AA/PI: Urban HR=1.22 [1.21-1.23], Rural HR=0.86 [0.84-0.88]). Rural White Veterans were 21% less likely to receive an initial vaccine compared with urban White Veterans (HR=0.79 [0.78-0.79]). AI/AN groups were less likely to receive vaccination regardless of rurality: Urban HR=0.93 [0.91-0.95]; AI/AN-Rural HR=0.76 [0.74-0.78].

Conclusions

Urban Black, Hispanic, and AA/PI Veterans were more likely than their urban White counterparts to receive a first vaccination; all rural race/ethnicity groups except Black patients had lower likelihood for vaccination compared with urban White patients. A better understanding of disparities and rural outreach will inform equitable vaccine distribution.

Ethnic disparities in COVID-19 outcomes: a multinational cohort study of 20 million individuals from England and Canada

BACKGROUND

Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes.

METHODS

We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the 'percentage of excess risk mediated' by these risk factors in the QResearch cohort.

RESULTS

There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death.

CONCLUSION

International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health policy as the pandemic continues.

Research in the USA on COVID-19's long-term effects: measures needed to ensure black, indigenous and Latinx communities are not left behind

The SARS-CoV-2 (COVID-19) pandemic continues to expose underlying inequities in healthcare for black, indigenous and Latinx communities in the USA. The gaps in equitable care for communities of colour transcend the diagnosis, treatment and vaccinations related to COVID-19. We are experiencing a continued gap across racial and socioeconomic lines for those who suffer prolonged effects of COVID-19, also known as 'Long COVID-19'. What we know about the treatment for Long COVID-19 so far is that it is complex, requires a multidisciplinary approach and there is still much research needed to fully understand the effects. In this paper, we discuss pragmatic considerations for including affected communities, relevant stakeholders, and leaders from communities of colour in the planning and implementation of Long COVID-19 research.

Prior SARS-CoV-2 Infection and COVID-19 Vaccine Effectiveness against Outpatient Illness during Widespread Circulation of SARS-CoV-2 Omicron Variant, US Flu VE Network

Background

We estimated combined protection conferred by prior SARS-CoV-2 infection and COVID-19 vaccination against COVID-19-associated acute respiratory illness (ARI).

Methods

During SARS-CoV-2 Delta (B.1.617.2) and Omicron (B.1.1.529) variant circulation between October 2021 and April 2022, prospectively enrolled adult patients with outpatient ARI had respiratory and filter paper blood specimens collected for SARS-CoV-2 molecular testing and serology. Dried blood spots were tested for immunoglobulin-G antibodies against SARS-CoV-2 nucleocapsid (NP) and spike protein receptor binding domain antigen using a validated multiplex bead assay. Evidence of prior SARS-CoV-2 infection also included documented or self-reported laboratory-confirmed COVID-19. We used documented COVID-19 vaccination status to estimate vaccine effectiveness (VE) by multivariable logistic regression by prior infection status.

Results

455 (29%) of 1577 participants tested positive for SARS-CoV-2 infection at enrollment; 209 (46%) case-patients and 637 (57%) test-negative patients were NP seropositive, had documented previous laboratory-confirmed COVID-19, or self-reported prior infection. Among previously uninfected patients, three-dose VE was 97% (95% confidence interval [CI], 60%- 99%) against Delta, but not statistically significant against Omicron. Among previously infected patients, three-dose VE was 57% (CI, 20%-76%) against Omicron; VE against Delta could not be estimated.

Conclusions

Three mRNA COVID-19 vaccine doses provided additional protection against SARS-CoV-2 Omicron variant-associated illness among previously infected participants.

Neither Race nor Ethnicity Impact the Mortality of Residents of Veterans Affairs Community Living Center With COVID-19

OBJECTIVES

COVID-19 disproportionately affected nursing home residents and people from racial and ethnic minorities in the United States. Nursing homes in the Veterans Affairs (VA) system, termed Community Living Centers (CLCs), belong to a national managed care system. In the period prior to the availability of vaccines, we examined whether residents from racial and ethnic minorities experienced disparities in COVID-19 related mortality.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Residents at 134 VA CLCs from April 14 to December 10, 2020.

METHODS

We used the VA Corporate Data Warehouse to identify VA CLC residents with a positive SARS-CoV-2 polymerase chain reaction test during or 2 days prior to their admission and without a prior case of COVID-19. We assessed age, self-reported race/ethnicity, frailty, chronic medical conditions, Charlson comorbidity index, the annual quarter of the infection, and all-cause 30-day mortality. We estimated odds ratios and 95% confidence intervals of all-cause 30-day mortality using a mixed-effects multivariable logistic regression model.

RESULTS

During the study period, 1133 CLC residents had an index positive SARS-CoV-2 test. Mortality at 30 days was 23% for White non-Hispanic residents, 15% for Black non-Hispanic residents, 10% for Hispanic residents, and 16% for other residents. Factors associated with increased 30-day mortality were age ≥70 years, Charlson comorbidity index ≥6, and a positive SARS-CoV-2 test between April 14 and June 30, 2020. Frailty, Black race, and Hispanic ethnicity were not independently associated with an increased risk of 30-day mortality.

CONCLUSIONS AND IMPLICATIONS

Among a national cohort of VA CLC residents with COVID-19, neither Black race nor Hispanic ethnicity had a negative impact on survival. Further research is needed to determine factors within the VA health care system that mitigate the influence of systemic racism on COVID-19 outcomes in US nursing homes.

The impact of the COVID-19 pandemic on cardiovascular health behaviors and risk factors: A new troubling normal that may be here to stay

In March 2020, the Coronavirus disease 2019 (COVID-19) outbreak was officially declared a global pandemic, leading to closure of public facilities, enforced social distancing and stay-at-home mandates to limit exposures and reduce transmission rates. While the severity of this "lockdown" period varied by country, the disruptions of the pandemic on multiple facets of life (e.g., daily activities, education, the workplace) as well as the social, economic, and healthcare systems impacts were unprecedented. These disruptions and impacts are having a profound negative effect on multiple facets of behavioral health and psychosocial wellbeing that are inextricably linked to cardiometabolic health and associated with adverse outcomes of COVID-19. For example, adoption of various cardiometabolic risk behavior behaviors observed during the pandemic contributed to irretractable trends in weight gain and poor mental health, raising concerns on the possible long-term consequences of the pandemic on cardiometabolic disease risk, and vulnerabilities to future viral pandemics. The purpose of this review is to summarize the direct and indirect effects of the pandemic on cardiometabolic health risk behaviors, particularly related to poor diet quality, physical inactivity and sedentary behaviors, smoking, sleep patterns and mental health. Additional insights into how the pandemic has amplified cardiovascular risk behaviors, particularly in our most vulnerable populations, and the potential implications for the future if these modifiable risk behaviors do not become better controlled, are described.

Testing the Acceptability and Usability of an AI-Enabled COVID-19 Diagnostic Tool Among Diverse Adult Populations in the United States

BACKGROUND AND OBJECTIVES

Although at-home coronavirus disease-2019 (COVID-19) testing offers several benefits in a relatively cost-effective and less risky manner, evidence suggests that at-home COVID-19 test kits have a high rate of false negatives. One way to improve the accuracy and acceptance of COVID-19 screening is to combine existing at-home physical test kits with an easily accessible, electronic, self-diagnostic tool. The objective of the current study was to test the acceptability and usability of an artificial intelligence (AI)-enabled COVID-19 testing tool that combines a web-based symptom diagnostic screening survey and a physical at-home test kit to test differences across adults from varying races, ages, genders, educational, and income levels in the United States.

METHODS

A total of 822 people from Richmond, Virginia, were included in the study. Data were collected from employees and patients of Virginia Commonwealth University Health Center as well as the surrounding community in June through October 2021. Data were weighted to reflect the demographic distribution of patients in United States. Descriptive statistics and repeated independent t tests were run to evaluate the differences in the acceptability and usability of an AI-enabled COVID-19 testing tool.

RESULTS

Across all participants, there was a reasonable degree of acceptability and usability of the AI-enabled COVID-19 testing tool that included a physical test kit and symptom screening website. The AI-enabled COVID-19 testing tool demonstrated overall good acceptability and usability across race, age, gender, and educational background. Notably, participants preferred both components of the AI-enabled COVID-19 testing tool to the in-clinic testing.

CONCLUSION

Overall, these findings suggest that our AI-enabled COVID-19 testing approach has great potential to improve the quality of remote COVID testing at low cost and high accessibility for diverse demographic populations in the United States.

Prevalence of SARS-CoV-2 infection and associated risk factors among asylum seekers living in asylum centres: A cross-sectional serologic study in Canton of Vaud, Switzerland

Background

Understanding the factors influencing SARS-CoV-2 transmission in asylum seekers and refugees living in centres is crucial to determine targeted public health policies protecting these populations fairly and efficiently. In response, this study was designed to explore the pandemic's spread into asylum centres during the first wave of the pandemic in Switzerland. Specifically, it aimed to identify the risk factors associated with a positive anti-SARS-CoV-2 seroprevalence test after the first semi-confinement period (16 March to 27 April 2020) amongst asylum seekers and refugees living in centres.

Methods

This research is part of SérocoVID, a seroepidemiologic study of SARS-CoV-2 infection conducted in the canton of Vaud, Switzerland. Migrants living in two asylum centres, one known to have had an epidemic outbreak, were invited to participate in this study. Anti-SARS-CoV-2 IgG and IgA antibodies targeting the spike viral protein were measured in all participants using a Luminex immunoassay. Each participant also completed a questionnaire measuring socio-demographic characteristics, medical history (comorbidities, smoking status, BMI, flu-like symptoms), health literacy, public health recommendations (wearing a masque in a public area, social distancing and hands cleaning), behaviours and exposures (daily life activities, number of contacts weekly). The association of these independent variables with the serologic test result were estimated using a multivariable logistic regression model.

Findings

A total of 124 participants from the two asylum centres took part in the study (Centre 1, n = 82; Centre 2, n = 42). The mean participation rate was 36.7%. The seroprevalence in Centres 1 and 2 were 13% [95% CI 0.03, 0.14] and 50% [0.34, 0.65], respectively. Next, 40.63% of SARS-CoV-2 positive people never developed symptoms (asymptomatic cases), and no one had severe forms of the Covid-19 disease requiring hospitalisation. Participants report high compliance with public health measures, especially hygiene rules (96.3% of positive answers) and social distancing (88.7%). However, only 11.3% said they always wore a masque in public. After adjusting for individual characteristics, infection risk was lower amongst people with high health literacy (aOR 0.16, p = 0.007 [0.04, 0.60]) and smokers (aOR 0.20, p = 0.013 [0.06, 0.69]).

Conclusion

Despite the lack of severe complications of Covid-19 disease in this study, findings suggest that developing targeted public health measures, especially for the low health literacy population, would be necessary to limit the risk of outbreaks in asylum centres and improve this population's safety. Further investigations and qualitative approach are required to understand more finely how living conditions, risks and behaviours such as tobacco consumption, and the adoption of protective measures impact SARS-CoV-2 infection.

Comparison of infection-induced and vaccine-induced immunity against COVID-19 in patients with cirrhosis

BACKGROUND AND AIMS

Immunity to SARS-CoV-2 can be infection or vaccine-induced. Cirrhosis is associated with vaccine hyporesponsiveness, but whether there is decreased immunity after SARS-CoV-2 infection in unvaccinated patients with cirrhosis is unknown.The objective of our study was to compare infection-induced and vaccine-induced immunity against COVID-19 among patients with cirrhosis.

METHODS

This was a retrospective cohort study among US Veterans with cirrhosis between November 27, 2020, and November 16, 2021, comparing a vaccine-induced immunity group, defined as participants without a documented SARS-CoV-2 infection but fully vaccinated with two doses of an mRNA vaccine, and infection-associated immunity group, defined as unvaccinated participants who had a positive SARS-CoV-2 polymerase chain reaction (PCR). Both groups were propensity score matched for observed characteristics, including location, and the date of the immunity acquiring event, to control for the community prevalence of COVID-19 variants. The outcome was a positive SARS-CoV-2 PCR more than 60 days after previous infection in the infection-induced, or after full vaccination in the vaccine-induced immunity group.

RESULTS

We compared 634 participants in the infection-induced immunity group with 27,131 participants in the vaccine-induced immunity group using inverse propensity of treatment weighting. Vaccine-induced immunity was associated with a reduced odds of developing SARS-CoV-2 infection (adjusted hazard ratio [aHR], 0.18; 95% confidence interval [CI], 0.16-0.20, p < 0.0001). On multivariable logistic regression, vaccine-induced immunity was associated with reduced odds of developing symptomatic (adjusted odds ratio [aOR], 0.36; 95% CI, 0.33-0.41, p < 0.0001), moderate/severe/critical (aOR, 0.27; 95% CI, 0.22-0.31, p < 0.0001), and severe or critical COVID-19 (aOR, 0.20; 95% CI, 0.16-0.26, p < 0.001), compared with infection-induced immunity.

CONCLUSIONS

In participants with cirrhosis, vaccine-induced immunity is associated with reduced risk of developing COVID-19, compared with infection-induced immunity.

The effects of department of Veterans Affairs medical centers on socio-economic outcomes: Evidence from the Paycheck Protection Program

Do medical facilities also help advance improvements in socio-economic outcomes? We focus on Veterans, a vulnerable group over the COVID-19 pandemic who have access to a comprehensive healthcare network, and the receipt of funds from the Paycheck Protection Program (PPP) between April and June as a source of variation. First, we find that Veterans received 3.5% more loans and 6.8% larger loans than their counterparts (p < 0.01), controlling for a wide array of zipcode characteristics. Second, we develop models to predict the number of PPP loans awarded to Veterans, finding that the inclusion of local VA medical center characteristics adds almost as much explanatory power as the industry and occupational composition in an area and even more than the education, race, and age distribution combined. Our results suggest that VA medical centers can play an important role in helping Veterans thrive even beyond addressing their direct medical needs.

Immune profiles to distinguish hospitalized versus ambulatory COVID-19 cases in older patients

A fraction of patients with COVID-19 develops severe disease requiring hospitalization, while the majority, including high-risk individuals, experience mild symptoms. Severe disease has been associated with higher levels of antibodies and inflammatory cytokines but often among patients with diverse demographics and comorbidity status. This study evaluated hospitalized vs. ambulatory patients with COVID-19 with demographic risk factors for severe COVID-19: median age of 63, >80% male, and >85% black and/or Hispanic. Sera were collected four to 243 days after symptom onset and evaluated for binding and functional antibodies as well as 48 cytokines and chemokines. SARS-CoV-2-specific antibody levels and functions were similar in ambulatory and hospitalized patients. However, a strong correlation between anti-S2 antibody levels and the other antibody parameters, along with higher IL-27 levels, was observed in hospitalized but not ambulatory cases. These data indicate that antibodies against the relatively conserved S2 spike subunit and immunoregulatory cytokines such as IL-27 are potential immune determinants of COVID-19.

Asylum Seekers' Responses to Government COVID-19 Recommendations: A Cross-sectional Survey in a Swiss Canton

Asylum seekers face multiple language, cultural and administrative barriers that could result in the inappropriate implementation of COVID-19 measures. This study aimed to explore their knowledge and attitudes to recommendations about COVID-19. We conducted a cross-sectional survey among asylum seekers living in the canton of Vaud, Switzerland. We used logistic regressions to analyze associations between knowledge about health recommendations, the experience of the pandemic and belief to rumors, and participant sociodemographic characteristics. In total, 242 people participated in the survey, with 63% of men (n = 150) and a median age of 30 years old (IQR 23-40). Low knowledge was associated with linguistic barriers (aOR 0.36, 95% CI 0.14-0.94, p = 0.028) and living in a community center (aOR 0.43, 95% CI 0.22-0.85, p = 0.014). Rejected asylum seekers were more likely to believe COVID-19 rumors (aOR 2.81, 95% CI 1.24-6.36, p = 0.013). This survey underlines the importance of tailoring health recommendations and interventions to reach asylum seekers, particularly those living in community centers or facing language barriers.

Use of COVID-19 testing in the first year of the COVID-19 pandemic among cohorts of people at the intersection of drug use and HIV

People living with (PLWH) and at risk for HIV and people who use drugs (PWUD) are at heightened risk for health consequences of COVID-19 because of compromised immunity and high comorbidities. We studied their use of COVID-19 testing during the first year of the COVID-19 pandemic. Eight NIDA funded cohorts across North America in the Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO) administered multiple waves of a COVID-19 survey. Respondents were at least 18 years of age, half PLWH, and many active substance users. Wave one of the COVID-19 survey was May-November, 2020 and wave two October 2020-April 2021. Associations of COVID-19 testing with demographics, socio-demographics, substance use, and HIV-status were assessed. Of the 3762 responses from 2331 individuals, half reported ever COVID-19 testing (49.1 %), with 4.3 % reporting a positive test (163/3762 surveys=4.3 %) and 41.5 % of people reporting current symptoms reported having been tested. In multivariable analysis adjusting for age, sex, and cohort type associations with COVID-19 testing included African American/Black identification compared to Caucasian/white (adjusted odds ratio (AOR)= 0.68; 95 % confidence interval (CI) 0.53, 0.88); being unemployed (AOR=0.61; 95 % CI 0.51, 0.73), and living with HIV (AOR=0.76; 95 % CI0.65, 0.90). Findings from these C3PNO COVID-19 modules suggests that in the first year of the pandemic COVID-19 testing was not broadly accessed by these marginalized populations including PLWH and those unemployed. Factors associated with not testing may also parallel those for vaccination and identify populations needing better access to COVID-19 prevention.

COVID-19 Vaccine Hesitancy among U.S. Veterans Experiencing Homelessness in Transitional Housing

Little is known about COVID-19 vaccine hesitancy and acceptance among individuals experiencing homelessness, despite their higher risk for morbidity and mortality from SARS-CoV-2. This study examines COVID-19 vaccination attitudes and uptake among U.S. military Veterans experiencing homelessness enrolled in transitional housing programs funded by the U.S. Department of Veterans Affairs (VA). Telephone interviews were conducted with 20 Veterans in California, Florida, Iowa, Kentucky, and Massachusetts, USA (January-April 2021). A rapid analysis approach was used to identify and enumerate commonly occurring themes. Although 60% of interviewed Veterans either received the COVID-19 vaccine or were willing to do so, one-third expressed hesitancy to get vaccinated. COVID-19 vaccination attitudes (e.g., belief that the vaccines were inadequately tested), military experience, beliefs about influenza and other vaccines, and sources of information emerged as influential factors for COVID-19 vaccination uptake or hesitancy. Veterans in VA-funded homeless transitional housing programs are generally willing to be vaccinated. However, a substantial minority is reluctant to take the vaccine due to concerns about the COVID-19 vaccine and distrust of authority. Recommendations for increasing uptake include utilizing Veteran peers, homeless service providers, and healthcare providers as trusted messengers to improve confidence in the vaccine.

Differences in COVID-19 testing and adverse outcomes by race, ethnicity, sex, and health system setting in a large diverse US cohort

BACKGROUND

Racial/ethnic disparities during the first six months of the COVID-19 pandemic led to differences in COVID-19 testing and adverse outcomes. We examine differences in testing and adverse outcomes by race/ethnicity and sex across a geographically diverse and system-based COVID-19 cohort collaboration.

METHODS

Observational study among adults (≥18 years) within six US cohorts from March 1, 2020 to August 31, 2020 using data from electronic health record and patient reporting. Race/ethnicity and sex as risk factors were primary exposures, with health system type (integrated health system, academic health system, or interval cohort) as secondary. Proportions measured SARS-CoV-2 testing and positivity; attributed hospitalization and death related to COVID-19. Relative risk ratios (RR) with 95% confidence intervals quantified associations between exposures and main outcomes.

RESULTS

5,958,908 patients were included. Hispanic patients had the highest proportions of SARS-CoV-2 testing (16%) and positivity (18%), while Asian/Pacific Islander patients had the lowest portions tested (11%) and White patients had the lowest positivity rates (5%). Men had a lower likelihood of testing (RR = 0.90 [0.89-0.90]) and a higher positivity risk (RR = 1.16 [1.14-1.18]) compared to women. Black patients were more likely to have COVID-19-related hospitalizations (RR = 1.36 [1.28-1.44]) and death (RR = 1.17 [1.03-1.32]) compared with White patients. Men were more likely to be hospitalized (RR = 1.30 [1.16-1.22]) or die (RR = 1.70 [1.53-1.89]) compared to women. These racial/ethnic and sex differences were reflected in both health system types.

CONCLUSIONS

This study supports evidence of disparities by race/ethnicity and sex during the COVID-19 pandemic that persisted even in healthcare settings with reduced barriers to accessing care. Further research is needed to understand and prevent the drivers that resulted in higher burdens of morbidity among certain Black patients and men.

Assessment of Practices Affecting Racial and Ethnic COVID-19 Vaccination Equity in 10 Large US Cities

CONTEXT

In the United States, COVID-19 vaccines have been unequally distributed between different racial and ethnic groups. Public reporting of race and ethnicity data for COVID-19 vaccination has the potential to help guide public health responses aimed at promoting vaccination equity. However, there is evidence that such data are not readily available.

OBJECTIVES

This study sought to assess gaps and discrepancies in COVID-19 vaccination reporting in 10 large US cities in July 2021.

DESIGN, SETTING, AND PARTICIPANTS

For the 10 cities selected, we collected COVID-19 vaccination and population data using publicly available resources, such as state health department Web sites and the US Census Bureau American Community Survey. We examined vaccination plans and news sources to identify initial proposals and evidence of implementation of COVID-19 vaccination best practices.

MAIN OUTCOME MEASURE

We performed quantitative assessment of associations of the number of vaccination best practices implemented with COVID-19 racial and ethnic vaccination equity. We additionally assessed gaps and discrepancies in COVID-19 vaccination reporting between states.

RESULTS

Our analysis did not show that COVID-19 vaccination inequity was associated with the number of vaccination best practices implemented. However, gaps and variation in reporting of racial and ethnic demographic vaccination data inhibited our ability to effectively assess whether vaccination programs were reaching minority populations.

CONCLUSIONS

Lack of consistent public reporting and transparency of COVID-19 vaccination data has likely hindered public health responses by impeding the ability to track the effectiveness of strategies that target vaccine equity.

Third dose of COVID-19 mRNA vaccine appears to overcome vaccine hyporesponsiveness in patients with cirrhosis

BACKGROUND & AIMS

Cirrhosis is associated with immune dysregulation and hyporesponsiveness to several vaccines including those against COVID-19. Our aim was to compare outcomes between patients with cirrhosis who received 3 doses of either the Pfizer BNT162b2 mRNA or Moderna mRNA-1273 vaccines to a propensity-matched control group of patients at similar risk of infection who received 2 doses.

METHODS

This was a retrospective cohort study of patients with cirrhosis who received 2 or 3 doses of a COVID-19 mRNA vaccine at the Veterans Health Administration. Participants who received 3 doses of the vaccine (n = 13,041) were propensity score matched with 13,041 controls who received 2 doses, and studied between July 18, 2021 and February 11, 2022, when B.1.617.2 (delta) and B.1.1.529 (omicron) were the predominant variants. Outcomes were aggregated as all cases with COVID-19, symptomatic COVD-19, with at least moderate COVID-19, or severe or critical COVID-19.

RESULTS

Receipt of the third dose of a COVID-19 mRNA vaccine was associated with an 80.7% reduction in COVID-19 (95% CI 39.2-89.1, p <0.001), an 80.4% reduction in symptomatic COVID-19, an 80% reduction in moderate, severe or critical COVID-19, (95% CI 34.5-87.6%, p = 0.005), a 100% reduction in severe or critical COVID-19 (95% CI 99.2-100.0, p = 0.01), and a 100% reduction in COVID-19-related death (95% CI 99.8-100.0, p = 0.007). The magnitude of reduction in COVID-19 was greater with the third dose of BNT 162b2 than mRNA-1273 and among participants with compensated rather than decompensated cirrhosis.

CONCLUSIONS

Administration of a third dose of a COVID-19 mRNA vaccine was associated with a more significant reduction in COVID-19 in patients with cirrhosis than in the general population, suggesting that the third dose can overcome vaccine hyporesponsiveness in this population.

LAY SUMMARY

Cirrhosis is associated with decreased responsiveness to several vaccines, including those against COVID-19. In this study of 26,082 participants with cirrhosis during the delta and omicron surge, receipt of the third dose of the vaccine was associated with an 80% reduction in COVID-19, a 100% reduction in severe/critical COVID-19, and a 100% reduction in COVID-19-related death. These findings support the importance of a third dose of mRNA vaccine among patients with cirrhosis.

COVID-19 Incidence and Death Rates in the Southern Region of the United States: A Racial and Ethnic Association

The SARS-CoV-2 virus responsible for the COVID-19 pandemic continues to spread worldwide, with over half a billion cases linked to over 6 million deaths globally. COVID-19 has impacted populations unequally based on income, age, race, sex, and geographical location. This study aimed to characterize COVID-19 incidence and death rate trends in six states of the southern region of the USA and to understand the demographic and racial differences in its incidence and death rates. Data for the study were collected from the COVID-19 Data tracker of the Centers for Disease Control and Prevention for the following southern states: Alabama (AL), Florida (FL), Georgia (GA), Louisiana (LA), Mississippi (MS), and Tennessee (TN). The results showed a significant geographical variation in the COVID-19 cases and related deaths. Significant variations in COVID-19 cases and death rates were observed among different races and ethnic groups. The highest number of COVID-19 cases were observed among the Hispanic and Black populations, and the highest death rates were found among non-Hispanic Blacks and Whites. The southern states included in this paper showed a high number of COVID-19 cases and high death rates during the study period. These increased rates may result from the low socioeconomic status and large minority populations.