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Estimating conditional vaccine effectiveness
Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Netherlands
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510183/ https://www.ncbi.nlm.nih.gov/pubmed/36155868 http://dx.doi.org/10.1007/s10654-022-00911-3 |
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author | Ioannidis, John P. A. |
author_facet | Ioannidis, John P. A. |
author_sort | Ioannidis, John P. A. |
collection | PubMed |
description | Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less severe outcome is the protection offered against the severe outcome (e.g. death) among those who already sustained the less severe outcome (e.g. documented infection). The concept applies also to the protection offered by previous infection rather than vaccination. Formulas and a nomogram are provided here for calculating conditional effectiveness. Illustrative examples are presented from recent vaccine effectiveness studies, including situations where effectiveness for different outcomes changed at different pace over time. E(death | documented infection) is the percent decrease in the case fatality rate and E(death | infection) is the percent decrease in the infection fatality rate (IFR). Conditional effectiveness depends on many factors and should not be misinterpreted as a causal effect estimate. However, it may be used for better personalized communication of the benefits of vaccination, considering also IFR and epidemic activity in public health decision-making and communication. |
format | Online Article Text |
id | pubmed-9510183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-95101832022-09-26 Estimating conditional vaccine effectiveness Ioannidis, John P. A. Eur J Epidemiol Essay Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less severe outcome is the protection offered against the severe outcome (e.g. death) among those who already sustained the less severe outcome (e.g. documented infection). The concept applies also to the protection offered by previous infection rather than vaccination. Formulas and a nomogram are provided here for calculating conditional effectiveness. Illustrative examples are presented from recent vaccine effectiveness studies, including situations where effectiveness for different outcomes changed at different pace over time. E(death | documented infection) is the percent decrease in the case fatality rate and E(death | infection) is the percent decrease in the infection fatality rate (IFR). Conditional effectiveness depends on many factors and should not be misinterpreted as a causal effect estimate. However, it may be used for better personalized communication of the benefits of vaccination, considering also IFR and epidemic activity in public health decision-making and communication. Springer Netherlands 2022-09-26 2022 /pmc/articles/PMC9510183/ /pubmed/36155868 http://dx.doi.org/10.1007/s10654-022-00911-3 Text en © Springer Nature B.V. 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Essay Ioannidis, John P. A. Estimating conditional vaccine effectiveness |
title | Estimating conditional vaccine effectiveness |
title_full | Estimating conditional vaccine effectiveness |
title_fullStr | Estimating conditional vaccine effectiveness |
title_full_unstemmed | Estimating conditional vaccine effectiveness |
title_short | Estimating conditional vaccine effectiveness |
title_sort | estimating conditional vaccine effectiveness |
topic | Essay |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510183/ https://www.ncbi.nlm.nih.gov/pubmed/36155868 http://dx.doi.org/10.1007/s10654-022-00911-3 |
work_keys_str_mv | AT ioannidisjohnpa estimatingconditionalvaccineeffectiveness |