Recommendations for estimating and reporting vaccine effectiveness by time since vaccination: a COVID-19 case study

Estimating COVID-19 vaccine effectiveness (VE) by time since vaccination (TSV) is essential for understanding how protection may change over time and enables meaningful comparisons across studies. This is important for accurate comparisons of VE against different SARS-CoV-2 variants/sublineages, across age groups, during different periods post vaccination campaign, or by vaccine type/brand. We provide recommendations for case-control VE studies on estimating and reporting VE analyses by TSV, with the aim of improving quality of these estimates. Our recommendations cover study design and pre-analysis considerations, descriptive analyses, choice of categories of TSV, categorical and continuous modelling approaches, and best practices for reporting VE by TSV. Using a real-life case-control study, we apply these recommendations, and include accompanying statistical scripts in R and Stata. These recommendations will serve as a practical resource for researchers conducting VE analyses by TSV. We encourage ongoing refinement of them through input from other study groups.

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Publication Details

Journal
American Journal of Epidemiology
Published
2025-11-15
DOI
https://doi.org/10.1093/aje/kwaf254
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Recommendations for estimating and reporting vaccine effectiveness by time since vaccination: a COVID-19 case study

Heather Whitaker, Ivan Mlinarić, Simon de Lusignan, Mariëtte Hooiveld et al.
American Journal of Epidemiology
COVID-19 epidemiological studies
article

Recommendations for estimating and reporting vaccine effectiveness by time since vaccination: a COVID-19 case study

Heather Whitaker, Ivan Mlinarić, Simon de Lusignan, Mariëtte Hooiveld, Nick Andrews, Mihaela Lazăr, Lisa Domegan, Shirley Masse, Chris Robertson, Marta Valenciano, Francisco del Pozo, Esther Kissling, Lucia Pastore Celentano, Susana Monge, Naoma William, Gloria Pérez‐Gimeno, Luca Basile, Ana Paula Rodrigues, Vincent Enouf, Niel Hens, Adam Meijer, Sanja Filipović, Itziar Casado, Philippe Beutels, Alexandra Nunes, Sabrina Bacci, Ausenda Machado, Angela MC Rose, Alain Moren, Neus Latorre‐Margalef, Maximilian Rieß, Theresa Enkirch, Joan O’Donnell, Răzvan Popescu, Mirjam J. Knol, Noémie Sève, Iván Martínez‐Baz, Maja Ilić, Mark Hamilton, Raquel Guiomar, Adele McKenna, on behalf of I-MOVE-COVID- and ECDC primary care study teams, Olivia-Carmen Timnea
article en

Abstract

Estimating COVID-19 vaccine effectiveness (VE) by time since vaccination (TSV) is essential for understanding how protection may change over time and enables meaningful comparisons across studies. This is important for accurate comparisons of VE against different SARS-CoV-2 variants/sublineages, across age groups, during different periods post vaccination campaign, or by vaccine type/brand. We provide recommendations for case-control VE studies on estimating and reporting VE analyses by TSV, with the aim of improving quality of these estimates. Our recommendations cover study design and pre-analysis considerations, descriptive analyses, choice of categories of TSV, categorical and continuous modelling approaches, and best practices for reporting VE by TSV. Using a real-life case-control study, we apply these recommendations, and include accompanying statistical scripts in R and Stata. These recommendations will serve as a practical resource for researchers conducting VE analyses by TSV. We encourage ongoing refinement of them through input from other study groups.

American Journal of Epidemiology
National Security Agency (US), Public Health Agency of Sweden (SE), Université de Corse Pascal Paoli (FR), University of Antwerp (BE), Inserm (FR), Institut Pasteur (FR), University of Strathclyde (GB), Université Paris Cité (FR), Instituto de Salud Carlos III (ES), Health Service Executive (IE), Sorbonne Université (FR), University of Oxford (GB), Instituto de Salud Pública de Navarra (ES), Institute of Public Health Bengaluru (IN), Hrvatski zavod za javno zdravstvo (HR), National Institute for Public Health and the Environment (NL), Helicon Foundation (US), Netherlands Institute for Health Services Research (NL), Institutul Cantacuzino (RO), National Institute of Research and Development for Biological Sciences (RO), Infectious Diseases Institute (UG), Public Health Scotland (GB), National Institute of Public Health (LA), Health Protection Surveillance Centre (IE), Institut Pierre Louis d‘Épidémiologie et de Santé Publique (FR), Instituto Nacional de Saúde (MZ), National Institute of Health Dr. Ricardo Jorge (PT), Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (ES), Agencia de Salud Pública de Barcelona (ES), Institut de Recherche pour le Développement (FR), UK Health Security Agency (GB), European Centre for Disease Prevention and Control (SE), Royal College of General Practitioners (GB), Hasselt University (BE)
Openalex Percentile: Top 61%
COVID-19 epidemiological studies
DOIOpen Access PDFOpenAlex
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