A mathematical model of H5N1 influenza transmission in US dairy cattle

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.

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Publication Details

Journal
Nature Communications
Published
2025-05-08
DOI
https://doi.org/10.1038/s41467-025-59554-z
Citations
4
Primary Topic
Animal Disease Management and Epidemiology
Type
article
Field-Weighted Citation Impact
7.61

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article

A mathematical model of H5N1 influenza transmission in US dairy cattle

Duc Anh Pham, Giovanni Forchini, Neil M. Ferguson, Richard G. FitzJohn et al.
4 citations
Nature Communications
Animal Disease Management and Epidemiology
7.61
article

A mathematical model of H5N1 influenza transmission in US dairy cattle

Duc Anh Pham, Giovanni Forchini, Neil M. Ferguson, Richard G. FitzJohn, Katharina Hauck, Christian Morgenstern, Thomas Rawson, Mike Sanderson, Joseph T. Hicks, Edward Knock, Aurelio H. Cabezas, Guillaume Morel
article en
4 citations

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.

Nature CommunicationsVol. 16(1)
Kansas State University (US), Imperial College London (GB), Umeå University (SE), Organisation Mondiale de la Santé Animale (FR)
Wellcome Trust, National Institute for Health and Care Research, Imperial College London, Medical Research Council, European and Developing Countries Clinical Trials Partnership
Good health and well-being
Openalex Percentile: Top 3%
Animal Disease Management and Epidemiology
7.61
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