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1.
Sci Rep ; 12(1): 273, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1612208

ABSTRACT

The coronavirus pandemic has disproportionally impacted racial and ethnic minority communities in the United States. Patterns of these disparities may be changing over time as outbreaks occur in different communities. Utilizing electronic health record data from the US Department of Veterans Affairs (VA), we estimated odds ratios, stratified by time period and region, for testing positive among 1,313,402 individuals tested for SARS-CoV-2 between February 12, 2020 and August 16, 2021 at VA medical facilities. We adjusted for personal characteristics (sex, age, rural/urban residence, VA facility) and a wide range of clinical characteristics that have been evaluated in prior SARS-CoV-2 reports and could potentially explain racial/ethnic disparities in SARS-CoV-2. Our study found racial and ethnic disparities for testing positive were most pronounced at the beginning of the pandemic and decreased over time. A key finding was that the disparity among Hispanic individuals attenuated but remained elevated, while disparities among Asian individuals reversed by March 1, 2021. The variation in racial and ethnic disparities in SARS-CoV-2 positivity by time and region, independent of underlying health status and other demographic characteristics in a nationwide cohort, provides important insight for strategies to prevent further outbreaks.


Subject(s)
COVID-19/epidemiology , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , Female , Humans , Male , Middle Aged , Risk Factors , Rural Population , SARS-CoV-2/isolation & purification , United States/epidemiology , Urban Population , Young Adult
2.
Int J Environ Res Public Health ; 18(24)2021 12 13.
Article in English | MEDLINE | ID: covidwho-1572470

ABSTRACT

COVID-19 disparities by area-level social determinants of health (SDH) have been a significant public health concern and may also be impacting U.S. Veterans. This retrospective analysis was designed to inform optimal care and prevention strategies at the U.S. Department of Veterans Affairs (VA) and utilized COVID-19 data from the VAs EHR and geographically linked county-level data from 18 area-based socioeconomic measures. The risk of testing positive with Veterans' county-level SDHs, adjusting for demographics, comorbidities, and facility characteristics, was calculated using generalized linear models. We found an exposure-response relationship whereby individual COVID-19 infection risk increased with each increasing quartile of adverse county-level SDH, such as the percentage of residents in a county without a college degree, eligible for Medicaid, and living in crowded housing.


Subject(s)
COVID-19 , Veterans , Humans , Retrospective Studies , SARS-CoV-2 , Social Determinants of Health , United States/epidemiology , United States Department of Veterans Affairs
3.
PLoS Med ; 18(10): e1003807, 2021 10.
Article in English | MEDLINE | ID: covidwho-1484840

ABSTRACT

BACKGROUND: We examined whether key sociodemographic and clinical risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality changed over time in a population-based cohort study. METHODS AND FINDINGS: In a cohort of 9,127,673 persons enrolled in the United States Veterans Affairs (VA) healthcare system, we evaluated the independent associations of sociodemographic and clinical characteristics with SARS-CoV-2 infection (n = 216,046), SARS-CoV-2-related mortality (n = 10,230), and case fatality at monthly intervals between February 1, 2020 and March 31, 2021. VA enrollees had a mean age of 61 years (SD 17.7) and were predominantly male (90.9%) and White (64.5%), with 14.6% of Black race and 6.3% of Hispanic ethnicity. Black (versus White) race was strongly associated with SARS-CoV-2 infection (adjusted odds ratio [AOR] 5.10, [95% CI 4.65 to 5.59], p-value <0.001), mortality (AOR 3.85 [95% CI 3.30 to 4.50], p-value < 0.001), and case fatality (AOR 2.56, 95% CI 2.23 to 2.93, p-value < 0.001) in February to March 2020, but these associations were attenuated and not statistically significant by November 2020 for infection (AOR 1.03 [95% CI 1.00 to 1.07] p-value = 0.05) and mortality (AOR 1.08 [95% CI 0.96 to 1.20], p-value = 0.21) and were reversed for case fatality (AOR 0.86, 95% CI 0.78 to 0.95, p-value = 0.005). American Indian/Alaska Native (AI/AN versus White) race was associated with higher risk of SARS-CoV-2 infection in April and May 2020; this association declined over time and reversed by March 2021 (AOR 0.66 [95% CI 0.51 to 0.85] p-value = 0.004). Hispanic (versus non-Hispanic) ethnicity was associated with higher risk of SARS-CoV-2 infection and mortality during almost every time period, with no evidence of attenuation over time. Urban (versus rural) residence was associated with higher risk of infection (AOR 2.02, [95% CI 1.83 to 2.22], p-value < 0.001), mortality (AOR 2.48 [95% CI 2.08 to 2.96], p-value < 0.001), and case fatality (AOR 2.24, 95% CI 1.93 to 2.60, p-value < 0.001) in February to April 2020, but these associations attenuated over time and reversed by September 2020 (AOR 0.85, 95% CI 0.81 to 0.89, p-value < 0.001 for infection, AOR 0.72, 95% CI 0.62 to 0.83, p-value < 0.001 for mortality and AOR 0.81, 95% CI 0.71 to 0.93, p-value = 0.006 for case fatality). Throughout the observation period, high comorbidity burden, younger age, and obesity were consistently associated with infection, while high comorbidity burden, older age, and male sex were consistently associated with mortality. Limitations of the study include that changes over time in the associations of some risk factors may be affected by changes in the likelihood of testing for SARS-CoV-2 according to those risk factors; also, study results apply directly to VA enrollees who are predominantly male and have comprehensive healthcare and need to be confirmed in other populations. CONCLUSIONS: In this study, we found that strongly positive associations of Black and AI/AN (versus White) race and urban (versus rural) residence with SARS-CoV-2 infection, mortality, and case fatality observed early in the pandemic were ameliorated or reversed by March 2021.


Subject(s)
COVID-19/mortality , Population Surveillance , Rural Population/trends , United States Department of Veterans Affairs/trends , Urban Population/trends , Aged , COVID-19/diagnosis , COVID-19/economics , Cohort Studies , Female , Humans , Male , Middle Aged , Mortality/trends , Population Surveillance/methods , Risk Factors , Socioeconomic Factors , United States/epidemiology
4.
Public Health Rep ; 136(4): 483-492, 2021.
Article in English | MEDLINE | ID: covidwho-1171653

ABSTRACT

OBJECTIVE: COVID-19 disproportionately affects racial/ethnic minority groups in the United States. We evaluated characteristics associated with obtaining a COVID-19 test from the Veterans Health Administration (VHA) and receiving a positive test result for COVID-19. METHODS: We conducted a retrospective cohort analysis of 6 292 800 veterans in VHA care at 130 VHA medical facilities. We assessed the number of tests for SARS-CoV-2 administered by the VHA (n = 822 934) and the number of positive test results (n = 82 094) from February 8 through December 28, 2020. We evaluated associations of COVID-19 testing and test positivity with demographic characteristics of veterans, adjusting for facility characteristics, comorbidities, and county-level area-based socioeconomic measures using nested generalized linear models. RESULTS: In fully adjusted models, veterans who were female, Black/African American, Hispanic/Latino, urban, and low income and had a disability had an increased likelihood of obtaining a COVID-19 test, and veterans who were Asian had a decreased likelihood of obtaining a COVID-19 test. Compared with veterans who were White, veterans who were Black/African American (risk ratio [RR] = 1.23; 95% CI, 1.19-1.27) and Native Hawaiian/Other Pacific Islander (RR = 1.13; 95% CI, 1.05-1.21) had an increased likelihood of receiving a positive test result. Hispanic/Latino veterans had a 43% higher likelihood of receiving a positive test result than non-Hispanic/Latino veterans did. CONCLUSIONS: Although veterans have access to subsidized health care at the VHA, the increased risk of receiving a positive test result for COVID-19 among Black and Hispanic/Latino veterans, despite receiving more tests than White and non-Hispanic/Latino veterans, suggests that other factors (eg, social inequities) are driving disparities in COVID-19 prevalence.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/ethnology , SARS-CoV-2/isolation & purification , Veterans , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , Female , Humans , Male , Middle Aged , Odds Ratio , Retrospective Studies , Social Determinants of Health/ethnology , Socioeconomic Factors , United States/epidemiology , Young Adult
5.
JAMA Netw Open ; 4(4): e214347, 2021 04 01.
Article in English | MEDLINE | ID: covidwho-1168797

ABSTRACT

Importance: A strategy that prioritizes individuals for SARS-CoV-2 vaccination according to their risk of SARS-CoV-2-related mortality would help minimize deaths during vaccine rollout. Objective: To develop a model that estimates the risk of SARS-CoV-2-related mortality among all enrollees of the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants: This prognostic study used data from 7 635 064 individuals enrolled in the VA health care system as of May 21, 2020, to develop and internally validate a logistic regression model (COVIDVax) that predicted SARS-CoV-2-related death (n = 2422) during the observation period (May 21 to November 2, 2020) using baseline characteristics known to be associated with SARS-CoV-2-related mortality, extracted from the VA electronic health records (EHRs). The cohort was split into a training period (May 21 to September 30) and testing period (October 1 to November 2). Main Outcomes and Measures: SARS-CoV-2-related death, defined as death within 30 days of testing positive for SARS-CoV-2. VA EHR data streams were imported on a data integration platform to demonstrate that the model could be executed in real-time to produce dashboards with risk scores for all current VA enrollees. Results: Of 7 635 064 individuals, the mean (SD) age was 66.2 (13.8) years, and most were men (7 051 912 [92.4%]) and White individuals (4 887 338 [64.0%]), with 1 116 435 (14.6%) Black individuals and 399 634 (5.2%) Hispanic individuals. From a starting pool of 16 potential predictors, 10 were included in the final COVIDVax model, as follows: sex, age, race, ethnicity, body mass index, Charlson Comorbidity Index, diabetes, chronic kidney disease, congestive heart failure, and Care Assessment Need score. The model exhibited excellent discrimination with area under the receiver operating characteristic curve (AUROC) of 85.3% (95% CI, 84.6%-86.1%), superior to the AUROC of using age alone to stratify risk (72.6%; 95% CI, 71.6%-73.6%). Assuming vaccination is 90% effective at preventing SARS-CoV-2-related death, using this model to prioritize vaccination was estimated to prevent 63.5% of deaths that would occur by the time 50% of VA enrollees are vaccinated, significantly higher than the estimate for prioritizing vaccination based on age (45.6%) or the US Centers for Disease Control and Prevention phases of vaccine allocation (41.1%). Conclusions and Relevance: In this prognostic study of all VA enrollees, prioritizing vaccination based on the COVIDVax model was estimated to prevent a large proportion of deaths expected to occur during vaccine rollout before sufficient herd immunity is achieved.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Health Planning/methods , Health Priorities/statistics & numerical data , Mass Vaccination , Veterans/statistics & numerical data , Aged , Area Under Curve , Comorbidity , Female , Humans , Logistic Models , Male , Middle Aged , Prognosis , ROC Curve , Risk Assessment , Risk Factors , SARS-CoV-2 , United States
6.
PLoS One ; 15(7): e0236554, 2020.
Article in English | MEDLINE | ID: covidwho-680636

ABSTRACT

The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient's clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care Assessment Need (CAN) score is an existing risk assessment tool within the Veterans Health Administration (VA), and produces a score from 0 to 99, with a higher score correlating to a greater risk. The model was originally designed for the nonacute outpatient setting and is automatically calculated from structured data variables in the electronic health record. This multisite retrospective study of 6591 Veterans diagnosed with COVID-19 from March 2, 2020 to May 26, 2020 was designed to assess the utility of repurposing the CAN score as objective and automated risk assessment tool to promptly enhance clinical decision making for Veterans diagnosed with COVID-19. We performed bivariate analyses on the dichotomized CAN 1-year mortality score (high vs. low risk) and each patient outcome using Chi-square tests of independence. Logistic regression models using the continuous CAN score were fit to assess its predictive power for outcomes of interest. Results demonstrated that a CAN score greater than 50 was significantly associated with the following outcomes after positive COVID-19 test: hospital admission (OR 4.6), prolonged hospital stay (OR 4.5), ICU admission (3.1), prolonged ICU stay (OR 2.9), mechanical ventilation (OR 2.6), and mortality (OR 7.2). Repurposing the CAN score offers an efficient way to risk-stratify COVID-19 Veterans. As a result of the compelling statistical results, and automation, this tool is well positioned for broad use across the VA to enhance clinical decision-making.


Subject(s)
Coronavirus Infections/therapy , Electronic Health Records , Pneumonia, Viral/therapy , Risk Assessment/methods , Adverse Outcome Pathways , COVID-19 , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Decision Making , Female , Hospitals, Veterans , Humans , Logistic Models , Male , Middle Aged , Needs Assessment , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Retrospective Studies , Treatment Outcome , United States , United States Department of Veterans Affairs
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