Predicting vaccine effectiveness against severe COVID-19 over time and against variants: a meta-analysis

Deborah Cromer, Megan Steain, Arnold Reynaldi, Timothy E. Schlub, Shanchita R. Khan, Sarah C. Sasson, Stephen J. Kent, David S. Khoury, Miles P. Davenport

Research output: Contribution to journalArticleResearchpeer-review

46 Citations (Scopus)

Abstract

Vaccine protection from symptomatic SARS-CoV-2 infection has been shown to be strongly correlated with neutralising antibody titres; however, this has not yet been demonstrated for severe COVID-19. To explore whether this relationship also holds for severe COVID-19, we performed a systematic search for studies reporting on protection against different SARS-CoV-2 clinical endpoints and extracted data from 15 studies. Since matched neutralising antibody titres were not available, we used the vaccine regimen, time since vaccination and variant of concern to predict corresponding neutralising antibody titres. We then compared the observed vaccine effectiveness reported in these studies to the protection predicted by a previously published model of the relationship between neutralising antibody titre and vaccine effectiveness against severe COVID-19. We find that predicted neutralising antibody titres are strongly correlated with observed vaccine effectiveness against symptomatic (Spearman ρ = 0.95, p < 0.001) and severe (Spearman ρ = 0.72, p < 0.001 for both) COVID-19 and that the loss of neutralising antibodies over time and to new variants are strongly predictive of observed vaccine protection against severe COVID-19.

Original languageEnglish
Article number1633
Number of pages9
JournalNature Communications
Volume14
Issue number1
DOIs
Publication statusPublished - Dec 2023

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