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Differentiation of SARS-CoV-2 naturally infected and vaccinated individuals in an inner-city emergency department
Evan J Beck; Yu-Hsiang Hsieh; Reinaldo E Fernandez; Gaby Dashler; Emily R Egbert; Shawn A Truelove; Caroline Garliss; Richard Wang; Evan M Bloch; Ruchee Shrestha; Joel N. Blankson; Andrea L Cox; Yukari C Manabe; Thomas Kickler; Richard Eric Rothman; Andrew D Redd; Aaron AR Tobian; Thomas C. Quinn; Oliver Laeyendecker.
Afiliação
  • Evan J Beck; NIAID
  • Yu-Hsiang Hsieh; Johns Hopkins University School of Medicine
  • Reinaldo E Fernandez; JHU
  • Gaby Dashler; Johns Hopkins
  • Emily R Egbert; Johns Hopkins University School of Medicine
  • Shawn A Truelove; Johns Hopkins Bloomberg School of Public Health
  • Caroline Garliss; Johns Hopkins Medicine
  • Richard Wang; Johns Hopkins University School of Medicine
  • Evan M Bloch; Johns Hopkins Medicine
  • Ruchee Shrestha; Johns Hopkins University School of Medicine
  • Joel N. Blankson; Johns Hopkins University School of Medicine
  • Andrea L Cox; Johns Hopkins University School of Medicine
  • Yukari C Manabe; Johns Hopkins University School of Medicine
  • Thomas Kickler; Johns Hopkins University School of Medicine
  • Richard Eric Rothman; Johns Hopkins Hospital
  • Andrew D Redd; NIAID/NIH
  • Aaron AR Tobian; Johns Hopkins Hospital
  • Thomas C. Quinn; NIAID and JHU
  • Oliver Laeyendecker; NIAID
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21264968
ABSTRACT
BackgroundEmergency Departments (EDs) can serve as surveillance sites for infectious diseases. Our purpose was to determine the burden of SARS-CoV-2 infection and prevalence of vaccination against COVID-19 among patients attending an urban ED in Baltimore City. MethodsUsing 1914 samples of known exposure status, we developed an algorithm to differentiate previously infected, vaccinated, and unexposed individuals using a combination of antibody assays. We applied this testing algorithm to 4360 samples ED patients obtained in the springs of 2020 and 2021. Using multinomial logistic regression, we determined factors associated with infection and vaccination. ResultsFor the algorithm, sensitivity and specificity for identifying vaccinated individuals was 100% and 99%, respectively, and 84% and 100% for naturally infected individuals. Among the ED subjects, seroprevalence to SARS-CoV-2 increased from 2% to 24% between April 2020 and March 2021. Vaccination prevalence rose to 11% by mid-March 2021. Marked differences in burden of disease and vaccination coverage were seen by sex, race, and ethnicity. Hispanic patients, though 7% of the study population, had the highest relative burden of disease (17% of total infections) but similar vaccination rates. Women and White individuals were more likely to be vaccinated than men or Black individuals (adjusted odds ratios [aOR] 1.35 [95% CI 1.02, 1.80] and aOR 2.26 [95% CI 1.67, 3.07], respectively). ConclusionsIndividuals previously infected with SARS-CoV-2 can be differentiated from vaccinated individuals using a serologic testing algorithm. SARS-CoV-2 exposure and vaccination uptake frequencies reflect gender, race and ethnic health disparities in this urban context. SummaryUsing an antibody testing algorithm, we distinguished between immune responses from SARS-CoV-2-infected and vaccinated individuals. When applied to blood samples from an emergency department in Baltimore, disparities in disease burden and vaccine uptake by sex, race, and ethnicity were identified.
Licença
cc0
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo diagnóstico / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo diagnóstico / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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