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A framework for monitoring population immunity to SARS-CoV-2.
Lopman, Benjamin A; Shioda, Kayoko; Nguyen, Quan; Beckett, Stephen J; Siegler, Aaron J; Sullivan, Patrick S; Weitz, Joshua S.
  • Lopman BA; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA. Electronic address: blopman@emory.edu.
  • Shioda K; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.
  • Nguyen Q; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
  • Beckett SJ; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
  • Siegler AJ; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
  • Sullivan PS; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
  • Weitz JS; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA; School of Physics, Georgia Institute of Technology, Atlanta, GA. Electronic address: jsweitz@gatech.edu.
Ann Epidemiol ; 63: 75-78, 2021 11.
Article in English | MEDLINE | ID: covidwho-1363868
ABSTRACT
In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccination being the safe pathway. However, measuring the contribution to population immunity from vaccination or natural infection is non-trivial. Historical COVID-19 case counts and vaccine coverage are necessary information but are not sufficient to approximate population immunity. Here, we consider the nuances of measuring each and propose an analytical framework for integrating the necessary data on cumulative vaccinations and natural infections at the state and national level. To guide vaccine roll-out and other aspects of control over the coming months, we recommend analytics that combine vaccine coverage with local (e.g. county-level) history of case reports and adjustment for waning antibodies to establish local estimates of population immunity. To do so, the strategic use of minimally-biased serology surveys integrated with vaccine administration data can improve estimates of the aggregate level of immunity to guide data-driven decisions to re-open safely and prioritize vaccination efforts.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2021 Document Type: Article