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Author Notes:

Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, Tel.: 404-606-3958

School of Biological Sciences, Georgia Institute of Technology, Atlanta, Tel.: 404-385-6169

Author Patrick Sullivan is the Editor in Chief of Annals of Epidemiology. This article was reviewed and handled by an independent editor. Dr. Sullivan was not involved in the editorial decision of the submission.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Subjects:

Research Funding:

This work was supported by the National Science Foundation (2032082/2032084), National Institute General Medical Sciences (R01 GM124280) and the US National Institute of Allergy and Infectious Diseases (3R01AI143875-02S1).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Public, Environmental & Occupational Health
  • Herd Immunity
  • Vaccines
  • SARS-CoV-2
  • Covid-19
  • Serology
  • INFECTION

A framework for monitoring population immunity to SARS-CoV-2

Tools:

Journal Title:

ANNALS OF EPIDEMIOLOGY

Volume:

Volume 63

Publisher:

, Pages 75-78

Type of Work:

Article | Final Publisher PDF

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.

Copyright information:

© 2021 Elsevier Inc. All rights reserved.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/rdf).
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