ArticleMicrobiology spectrum2026
Prior immunity to seasonal influenza A(H3N2) virus confers varying levels of cross-protection against challenge with clade 2.3.4.4b A(H5N1), A(H7N9), or A(H9N2) virus in a ferret model.
Article in Microbiology spectrum, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Limited added benefit of seasonal influenza vaccination before A(H5) vaccination in mice and ferrets challenged with A(H5N1).Emerging microbes & infections · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Evaluating how prior immunity to seasonal influenza viruses influences subsequent zoonotic influenza A virus (IAV) infection in animal models is critical for pandemic preparedness. In this study, we investigated the cross-protective effect of pre-existing A(H3N2) immunity in ferrets challenged with three distinct subtypes of zoonotic IAVs: low pathogenic A(H7N9) and A(H9N2) viruses, and highly pathogenic clade 2.3.4.4b A(H5N1) virus. Our results show that A(H3N2) preimmunity conferred some protection against A(H5N1) and A(H9N2) virus infection, as evidenced by more rapid viral clearance in the upper respiratory tract, reduced virus shedding in the nasal wash on select days post-inoculation, and a lowered frequency of viral detection in specific tissues compared with naive animals. In contrast, A(H3N2) preimmunity provided minimal cross-protection against A(H7N9) infection, as weight loss and viral dissemination in tissues were not significantly reduced in A(H3N2) preimmune ferrets relative to naive animals. These findings highlight the variable breadth and magnitude of cross-protection elicited by prior seasonal IAV immunity against zoonotic influenza virus challenges in the ferret model. Seasonal influenza A(H3N2) preimmunity provided differing levels of cross-protection against zoonotic influenza A virus infections in ferrets. IMPORTANCE: Understanding how pre-existing influenza immunity shapes susceptibility to zoonotic IAV infections is essential for risk assessment and pandemic preparedness. By evaluating the extent and magnitude of cross-protection conferred by A(H3N2) preimmunity against three distinct zoonotic subtypes-A(H5N1), A(H7N9), and A(H9N2)-in the ferret model, we show that HA or NA relatedness to the priming A(H3N2) virus is not sufficient to predict cross-protection outcomes. Notably, A(H3N2) preimmunity provided some protection against clade 2.3.4.4b A(H5N1) virus infection despite sharing neither an HA within the same phylogenetic group nor an NA within the same subtype, whereas cross-protection against A(H7N9), which shares a group 2 HA, was limited. These findings underscore the need to evaluate both humoral and cell-mediated immunity against multiple viral antigens when assessing cross-protection elicited by seasonal influenza viruses.
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.