Evidence map›Paper›PMID 38343865›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Quantifying the impact of pre-vaccination titre and vaccination history on influenza vaccine immunogenicity.

David Hodgson, Stephany Sánchez-Ovando, Louise Carolan, Yi Liu, A Jessica Hadiprodjo, Annette Fox, Sheena G Sullivan, Adam J Kucharski

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

David HodgsonCenter of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0002-5585-8974
Stephany Sánchez-OvandoDepartment of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0003-1389-2506
Louise CarolanWHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Yi LiuDepartment of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0002-2157-8368
A Jessica HadiprodjoDepartment of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Annette FoxDepartment of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0002-0565-7146
Sheena G SullivanDepartment of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0002-0856-0294
Adam J KucharskiCenter of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0001-8814-9421
The Royal Melbourne Hospital · AULondon School of Hygiene & Tropical Medicine · GB

Funding

VIRAL AND IMMUNE CONSEQUENCES OF EARLY HIV1 THERAPYU01AI041534 · NIAID · AARON DIAMOND AIDS RESEARCH CENTER · PI MARKOWITZ, MARTIN H · 1997 to 2006
$10.1M
NIAID NIH HHS U01 AI041534Wellcome Trust
6 · The paper itself

Abstract

Epidemiological studies suggest that heterogeneity in influenza vaccine antibody response is associated with host factors, including pre-vaccination immune status, age, gender, and vaccination history. However, the pattern of reported associations varies between studies. To better understand the underlying influences on antibody responses, we combined host factors and vaccine-induced in-host antibody kinetics from a cohort study conducted across multiple seasons with a unified analysis framework. We developed a flexible individual-level Bayesian model to estimate associations and interactions between host factors, including pre-vaccine HAI titre, age, sex, vaccination history and study setting, and vaccine-induced HAI titre antibody boosting and waning. We applied the model to derive population-level and individual effects of post-vaccine antibody kinetics for vaccinating and circulating strains for A(H1N1) and A(H3N2) influenza subtypes. We found that post-vaccine HAI titre dynamics were significantly influenced by pre-vaccination HAI titre and vaccination history and that lower pre-vaccination HAI titre results in longer durations of seroprotection (HAI titre equal to 1:40 or higher). Consequently, for A(H1N1), our inference finds that the expected duration of seroprotection post-vaccination was 171 (95% Posterior Predictive Interval[PPI] 128-220) and 159 (95% PPI 120-200) days longer for those who are infrequently vaccinated (<2 vaccines in last five years) compared to those who are frequently vaccinated (2 or more vaccines in the last five years) at pre-vaccination HAI titre values of 1:10 and 1:20 respectively. In addition, we found significant differences in the empirical distributions that describe the individual-level duration of seroprotection for A(H1N1) circulating strains. In future, studies that rely on serological endpoints should include the impact of pre-vaccine HAI titre and prior vaccination status on seropositivity and seroconversion estimates, as these significantly influence an individual's post-vaccination antibody kinetics.

Indexed as

Antibody kineticsmathematical modellingseasonal influenzavaccination

Identifiers

PMID38343865
PMCPMC10854332
OpenAlexW4391270145

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.