Evidence map›Paper›PMID 41134898›Full record

ArticleScience advances2025

Lightweight multiscale early warning system for influenza A spillovers.

Tommaso Alfonsi, Anna Bernasconi, Matteo Chiara, Stefano Ceri

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tommaso AlfonsiDepartment of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.ORCID 0000-0002-4707-8425
Anna BernasconiDepartment of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.ORCID 0000-0001-8016-5750
Matteo ChiaraDepartment of Biosciences, Università degli Studi di Milano, Via Celoria 26, 20133, Milan, Italy.ORCID 0000-0003-3983-4961
Stefano CeriDepartment of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.ORCID 0000-0003-0671-2415

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spillovers of zoonotic Influenza A viruses (IAVs) into farmed animals and humans have the potential to trigger epidemics or even global pandemics. We introduce FluWarning, a highly efficient and elegant computational method based on anomaly detection of codon bias and dinucleotide composition for early identification of divergent viral HA segments. We applied FluWarning to the 2009 influenza pandemic as a test case. FluWarning successfully identified the emergence of pdm09, the virus that caused the pandemic, with warnings preceding the observed global spread. Applied to H5N1 specimens collected between 2019 and 2025, FluWarning flagged genotypes D1.1 and B3.13, both associated with recent spillovers in dairy cows in the United States. In summary, FluWarning is an effective, lightweight, multiscale warning system for IAVs, detecting spillovers with few available sequences.

Indexed as

Influenza A virusInfluenza, HumanAnimalsCattleHumansInfluenza A Virus, H5N1 SubtypePandemicsPhylogeny

Identifiers

PMID41134898
PMCPMC12551695

What OpenQuestion holds

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LicenceCC BY-NC
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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.