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Prev Med Rep ; 27: 101771, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1740104

ABSTRACT

Carceral facilities are high-risk settings for COVID-19 transmission. Factors associated with COVID-19 vaccine acceptance and hesitancy among incarcerated individuals are poorly understood, especially among jail residents. Here, we conducted a retrospective review of electronic health record (EHR) data on COVID-19 vaccine uptake in custody and additionally administered a survey to assess reasons for vaccine hesitancy, sources of COVID-19 information, and medical mistrust among residents of four Northern California jails. We performed multivariate logistic regression to determine associations with vaccine acceptance. Of 2,564 jail residents offered a COVID-19 vaccine between March 19, 2021 and June 30, 2021, 1,441 (56.2%) accepted at least one dose. Among vaccinated residents, 497 (34.5%) had initially refused. Vaccine uptake was higher among older individuals, women, those with recent flu vaccination, and those living in shared housing. Among 509 survey respondents, leading reasons for vaccine hesitancy were concerns around side effects and suboptimal efficacy, with cost and the need for an annual booster being other hypothetical deterrents to vaccination. Vaccine hesitancy was also associated with mistrust of medical personnel in and out of jail, although this association varied by race/ethnicity. Television and friends/family were the most common and most trusted sources of COVID-19 information, respectively. Overall, vaccine acceptance was much lower among jail residents than the local and national general population. Interventions to increase vaccination rates in this setting should utilize accessible and trusted sources of information to address concerns about side effects and efficacy, while working to mitigate medical and institutional mistrust among residents.

2.
Sci Rep ; 12(1): 889, 2022 01 18.
Article in English | MEDLINE | ID: covidwho-1630723

ABSTRACT

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.


Subject(s)
COVID-19 , Gene Expression Regulation , RNA, Messenger/blood , SARS-CoV-2/metabolism , Acute Disease , COVID-19/blood , COVID-19/mortality , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies
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