Evidence map›Paper›PMID 40341525›Full record

ArticleNature communications2025

A mathematical model of H5N1 influenza transmission in US dairy cattle.

Thomas Rawson, Christian Morgenstern, Edward S Knock, Joseph Hicks, Anh Pham, Guillaume Morel, Aurelio Cabezas Murillo, Michael W Sanderson, Giovanni Forchini, Richard FitzJohn and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Avian influenza overview December 2024-March 2025.EFSA journal. European Food Safety Authority · 2025
    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

12 authors.

Thomas RawsonMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK. t.rawson@imperial.ac.uk.ORCID http://orcid.org/0000-0001-8182-4279
Christian MorgensternMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-3735-1130
Edward S KnockMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-1135-9652
Joseph HicksMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.
Anh PhamMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.
Guillaume MorelMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.ORCID http://orcid.org/0009-0001-5462-1027
Aurelio Cabezas MurilloWorld Animal Health Information and Analysis Department, World Organisation for Animal Health, Paris, France.
Michael W SandersonCenter for Outcomes Research and Epidemiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.ORCID http://orcid.org/0000-0001-5965-906X
Giovanni ForchiniMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.
Richard FitzJohnMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.
Katharina HauckMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-3138-4169
Neil FergusonMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.

Funding

RCUK | Medical Research Council (MRC) MR/X020258/1Wellcome TrustWellcome Trust (Wellcome) 220900/Z/20/Z
6 · The paper itself

Abstract

2024 saw a novel outbreak of H5N1 avian influenza in US dairy cattle. Limited surveillance data has made determining the true scale of the epidemic difficult. We present a stochastic metapopulation transmission model that simulates H5N1 influenza transmission through individual dairy cows in 35,974 herds in the continental US. Transmission is enabled through the movement of cattle between herds, as indicated from Interstate Certificates of Veterinary Inspection data. We estimate the rates of under-reporting by state and present the anticipated rates of positivity for cattle tested at the point of exportation over time. We investigate the impact of intervention methods on the underlying epidemiological dynamics, demonstrating that current interventions have had insufficient impact, preventing only a mean 175.2 reported outbreaks. Our model predicts that the majority of the disease burden is, as of January 2025, concentrated within West Coast states. We quantify the uncertainty in the scale of the epidemic, highlighting the most pressing data streams to capture, and which states are expected to see outbreaks emerge next, with Arizona and Wisconsin at greatest risk. Our model suggests that dairy outbreaks will continue to occur in 2025, and that more urgent, farm-focused, biosecurity interventions and targeted surveillance schemes are needed.

Indexed as

Cattle DiseasesInfluenza A Virus, H5N1 SubtypeModels, TheoreticalAnimalsCattleDairyingDisease OutbreaksFemaleUnited States

Identifiers

PMID40341525
PMCPMC12062519

What OpenQuestion holds

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LicenceCC BY
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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.