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Methodology to estimate natural- and vaccine-induced antibodies to SARS-CoV-2 in a large geographic region.
DeSantis, Stacia M; León-Novelo, Luis G; Swartz, Michael D; Yaseen, Ashraf S; Valerio-Shewmaker, Melissa A; Talebi, Yashar; Brito, Frances A; Ross, Jessica A; Kohl, Harold W; Messiah, Sarah E; Kelder, Steve H; Wu, Leqing; Zhang, Shiming; Aguillard, Kimberly A; Gonzalez, Michael O; Omega-Njemnob, Onyinye S; Lakey, David; Shuford, Jennifer A; Pont, Stephen; Boerwinkle, Eric.
  • DeSantis SM; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • León-Novelo LG; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Swartz MD; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Yaseen AS; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Valerio-Shewmaker MA; The University of Texas Health Science Center at Houston, School of Public Health, Brownsville Campus, Brownsville, Texas, United States of America.
  • Talebi Y; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Brito FA; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Ross JA; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Kohl HW; The University of Texas at Austin, Austin, Texas, United States of America.
  • Messiah SE; The University of Texas Health Science Center at Houston, School of Public Health, Dallas Campus, Dallas, Texas, United States of America.
  • Kelder SH; Center for Pediatric Population Health, UTHealth School of Public Health and Children's Health System of Texas, Dallas, Texas, United States of America.
  • Wu L; The University of Texas Health Science Center at Houston, School of Public Health, Austin Campus, Austin, Texas, United States of America.
  • Zhang S; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Aguillard KA; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Gonzalez MO; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Omega-Njemnob OS; The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, United States of America.
  • Lakey D; The University of Texas Health Science Center at Houston, School of Public Health, Austin Campus, Austin, Texas, United States of America.
  • Shuford JA; The University of Texas System and the University of Texas at Tyler Health Science Center, Tyler, Texas, United States of America.
  • Pont S; Texas Department of State Health Services, Austin, Texas, United States of America.
  • Boerwinkle E; The University of Texas Health Science Center at Houston, School of Public Health, Austin Campus, Austin, Texas, United States of America.
PLoS One ; 17(9): e0273694, 2022.
Article in English | MEDLINE | ID: covidwho-2021937
ABSTRACT
Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data. Specifically, we conducted a longitudinal statewide serological survey with 88,605 participants 5 years or older with 3 prospective blood draws beginning September 30, 2020. Along with state vaccination data, as of October 31, 2021, the estimated percentage of those 5 years or older with naturally occurring antibodies to SARS-CoV-2 in Texas is 35.0% (95% CI = (33.1%, 36.9%)). This is 3× higher than, state-confirmed COVID-19 cases (11.83%) for all ages. The percentage with naturally occurring or vaccine-induced antibodies (total seroprevalence) is 77.42%. This methodology is integral to pandemic preparedness as accurate estimates of seroprevalence can inform policy-making decisions relevant to SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0273694

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0273694