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1.
BMC Public Health ; 21(1): 2255, 2021 12 11.
Article in English | MEDLINE | ID: covidwho-1571753

ABSTRACT

BACKGROUND: Understanding health care experiences during the COVID-19 pandemic may provide insights into patient needs and inform policy. The objective of this study was to describe health care experiences by race and social determinants of health. METHODS: We conducted a telephone survey (July 6, 2020-September 4, 2021) among 9492 Black and White participants in the longitudinal REasons for Geographic And Racial Differences in Stroke cohort study, age 58-105 years, from the continental United States. Among participants with symptoms of COVID-19, outcomes were: 1. Sought care or advice for the illness; 2. Received a SARS-CoV-2 test for the illness; and 3. Tested positive. Among participants without symptoms of COVID-19, outcomes were: 1. Wanted a test; 2. Wanted and received a test; 3. Did not want but received a test; and 4. Tested positive. We examined these outcomes overall and in subgroups defined by race, household income, marital status, education, area-level poverty, rural residence, Medicaid expansion, public health infrastructure ranking, and residential segregation. RESULTS: The average age of participants was 76.8 years, 36% were Black, and 57% were female. Among participants with COVID-19 symptoms (n = 697), 74% sought care or advice for the illness, 50% received a SARS-CoV-2 test, and 25% had a positive test (50% of those tested). Among participants without potential COVID-19 symptoms (n = 8795), 29% wanted a SARS-CoV-2 test, 22% wanted and received a test, 8% did not want but received a test, and 1% tested positive; a greater percentage of participants who were Black compared to White wanted (38% vs 23%, p < 0.001) and received tests (30% vs 18%, p < 0.001) and tested positive (1.4% vs 0.8%, p = 0.005). CONCLUSIONS: In this national study of older US adults, many participants with potential COVID-19 symptoms and asymptomatic participants who desired testing did not receive COVID-19 testing.


Subject(s)
COVID-19 , Adult , Aged , Aged, 80 and over , COVID-19 Testing , Cohort Studies , Delivery of Health Care , Female , Humans , Middle Aged , Pandemics , SARS-CoV-2 , Social Determinants of Health , United States/epidemiology
2.
J Am Med Inform Assoc ; 27(11): 1721-1726, 2020 11 01.
Article in English | MEDLINE | ID: covidwho-1024117

ABSTRACT

Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, scientific community still lacks a secure and privacy-preserving infrastructure to support auditable data sharing and facilitate automated and legally compliant federated analysis on an international scale. Existing health informatics systems do not incorporate the latest progress in modern security and federated machine learning algorithms, which are poised to offer solutions. An international group of passionate researchers came together with a joint mission to solve the problem with our finest models and tools. The SCOR Consortium has developed a ready-to-deploy secure infrastructure using world-class privacy and security technologies to reconcile the privacy/utility conflicts. We hope our effort will make a change and accelerate research in future pandemics with broad and diverse samples on an international scale.


Subject(s)
Biomedical Research , Computer Security , Coronavirus Infections , Information Dissemination , Pandemics , Pneumonia, Viral , Privacy , COVID-19 , Humans , Information Dissemination/ethics , Internationality , Machine Learning
3.
Transfusion ; 61(4): 1047-1052, 2021 04.
Article in English | MEDLINE | ID: covidwho-999171

ABSTRACT

BACKGROUND: Convalescent plasma is used as a treatment for COVID-19. Only limited data describe the efforts to recruit COVID-19 convalescent plasma (CCP) donors. We describe our experience engaging persons recovered from COVID-19 to donate CCP. STUDY DESIGN AND METHODS: We performed a retrospective analysis of the CCP recruitment for an 11-hospital health system in Houston, Texas. We sought CCP donations from: a) "volunteers" responding to advertisements in social media, press releases, and websites and b) "referred" individuals directed to the program or identified from hospitalization records. We determined the proportions of donor candidates who passed initial telephone health screening, who qualified after diagnostic testing, who presented to the regional CCP donation center, and who completed CCP donation. RESULTS: There were 900 CCP donor candidates, including 363 volunteers and 537 referred donors. Of 360 contacted volunteers, 186 (5.7%) were excluded by interview; 133 were referred for additional diagnostic screening, 97 completed donor antibody and antigen testing, and 87 were qualified for CCP donation, resulting in 35 CCP donations (9.7% of initial telephone contacts). Among 533 referred donors, 448 (84.1%) were excluded by interview, 71 were referred for additional screening, 48 completed donor antibody and antigen testing, and 40 were qualified for CCP donation, resulting in one CCP donation (0.2% of initial telephone contacts). CONCLUSION: In this community, screening of a high number of candidates yielded a limited number of CCP donations. These observations have important implications for CCP donor recruitment and community pandemic planning.


Subject(s)
Blood Donors , COVID-19/immunology , COVID-19/therapy , Convalescence , Donor Selection , Pandemics , SARS-CoV-2/immunology , Adult , Humans , Immunization, Passive , Male , Middle Aged , Retrospective Studies
4.
J Community Health ; 45(4): 696-701, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-526762

ABSTRACT

The pandemic of novel Coronavirus (SARS-CoV-2) is currently spreading rapidly across the United States. We provide a comprehensive overview of COVID-19 epidemiology across the state of Texas, which includes vast rural & vulnerable communities that may be disproportionately impacted by the spread of this new disease. All 254 Texas counties were included in this study. We examined the geographic variation of COVID-19 from March 1 through April 8, 2020 by extracting data on incidence and case fatality from various national and state datasets. We contrasted incidence and case fatality rates by county-level demographic and healthcare resource factors. Counties which are part of metropolitan regions, such as Harris and Dallas, experienced the highest total number of confirmed cases. However, the highest incidence rates per 100,000 population were in found in counties of Donley (353.5), Castro (136.4), Matagorda (114.4) and Galveston (93.4). Among counties with greater than 10 cases, the highest CFR were observed in counties of Comal (10.3%), Hockley (10%), Hood (10%), and Castro (9.1%). Counties with the highest CFR (> 10%) had a higher proportion of non-Hispanic Black residents, adults aged 65 and older, and adults smoking, but lower number of ICU beds per 100,000 population, and number of primary care physicians per 1000 population. Although the urban areas of Texas account for the majority of COVID-19 cases, the higher case-fatality rates and low health care capacity in rural areas need attention.


Subject(s)
Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , COVID-19 , Coronavirus Infections/mortality , Coronavirus Infections/transmission , Humans , Incidence , Mortality , Pneumonia, Viral/mortality , Pneumonia, Viral/transmission , Rural Population/statistics & numerical data , Texas/epidemiology , Urban Population/statistics & numerical data
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