ArticleInfluenza and other respiratory viruses2025
Influenza Vaccine Effectiveness in Australia During 2017-2019.
Article in Influenza and other respiratory viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Influenza Vaccination Effectiveness Against Influenza-Associated Hospitalization in Children and the Effects of Repeated Vaccination.The Journal of infectious diseases · 2026Article
- Reproducible and later vaccine strain selection can improve vaccine match to A/H3N2 seasonal influenza viruses.NPJ vaccines · 2025Article
- Influenza Vaccine Effectiveness in Australia During 2017-2019.Influenza and other respiratory viruses · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundVaccine effectiveness (VE) estimates provide important post-marketing assessment of how well seasonal influenza vaccines prevent medically attended influenza disease. We present VE estimates for primary care in Australia for the 2017-2019 seasons.
methodsThe study used a test-negative design. Influenza VE was estimated from adjusted logistic regression models comparing the odds of vaccination among influenza-test-positive cases and test-negative non-cases. Estimates were made overall and separately by influenza type, subtype, lineage and clade and stratified by age group. Antigenic similarity of influenza viruses to vaccine strains was assessed using the haemagglutination inhibition assay, and phylogenetic analysis was performed on sequenced viruses.
resultsThe study included 2879, 1973 and 3371 general practice patients with swabs collected during 2017, 2018 and 2019 respectively. Influenza A(H3N2) was predominant in 2017 and 2019, while influenza A(H1N1)pdm09 predominated in 2018. VE was estimated at 37% (95% CI 22, 48) for the 2017 season, 53% (95% CI 33, 67) for 2018 and 50% (95% CI 40, 58) for 2019. In general, estimates were higher against A(H1N1)pdm09 and influenza B viruses and lower against A(H3N2) viruses. Across the three seasons, antigenic data identified a greater proportion of A(H1N1)pdm09 and influenza B viruses than A(H3N2) viruses as antigenically similar to the cell-propagated reference viruses. VE estimates by clade generally indicated higher VE among viruses in the same clade as the vaccine viruses.
conclusionsInfluenza VE varied across influenza seasons and by influenza type/subtype. Given the ongoing evolution of circulating influenza viruses, vaccine improvements are needed, especially for influenza A(H3N2).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.