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

Autor: Stephen J. Beckett, Benjamin A. Lopman, Quan Nguyen, Aaron J Siegler, Patrick S. Sullivan, Kayoko Shioda, Joshua S. Weitz
Rok vydání: 2021
Předmět:
Zdroj: Annals of Epidemiology
ISSN: 1047-2797
DOI: 10.1016/j.annepidem.2021.08.013
Popis: 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 building up population immunity, with vaccination representing 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.
Databáze: OpenAIRE
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