#18,473
Based on limited (and at times hamstrung) surveillance & reporting, just over 1,050 dairy herds (the size of which are not provided) - across 17 states - have reported positive infections with H5N1 over the past 13 months.
Since testing is largely voluntary, and only lactating dairy cows are usually tested, we really don't know how widespread the virus is in American livestock. Many dairy farmers - fearing loss of income or the stigma of infection - simply prefer a `Don't test, don't tell' strategy.
There are reportedly over 36,000 dairy farms in the United States. Last summer the USDA set up a voluntary dairy herd testing program, which they describe as:
The Dairy Herd Status Program is a voluntary program that offers dairy producers the option to monitor their herds via weekly bulk milk samples before moving them across State lines, without having to test each individual animal. This helps support ongoing HPAI testing to better understand the virus, reduce the risk of further spread, and meet movement restrictions.
As of April 25th, 2025 the USDA reports only 100 herds have been enrolled. That's 1 in 360 herds, or just 0.27%.
In states where testing has been the most rigorous (e.g. Colorado & California), the percentage of herds infected has ranged from 50%-70%, Idaho is currently at 25%, while the other 14 states have reported far lower percentages.
The assumption by the USDA has long been that the B3.13 genotype entered dairy cattle via a single spillover from birds - a little more than a year ago in Texas - and was then spread to other states by the interstate transport of infected cattle.
Last February, two states (Nevada & Arizona) reported dairy herds infected with a new H5N1 genotype (see APHIS Statement On HPAI Genotype D.1 In Arizona Dairy Cattle). APHIS described this as a `third spillover' and that it `. . . may indicate an increased risk of HPAI introduction into dairies through wild bird exposure.'
Last March, however, in Virology: Detection of Antibodies Against Influenza A Viruses in Cattle, we learned that evidence of (non-H5) IAV infection was common across a wide sampling of serum samples taken in 2023 and early 2024.For the past year, we've seen a reluctance to test beef cattle for H5N1, using the rationale that cattle are generally not susceptible to IAV infection, and H5 has a special affinity for lactating cows.
Of particular note, this study found that IAV infection isn't limited to lactating dairy cows. Male cattle (bulls and steers) were just as likely to carry antibodies to IAV as cows and heifers.
Over the past year we've seen spillovers of H5N1 into goats, alpacas, pigs, and most recently a sheep in the UK. Despite very limited surveillance, we've also seen hundreds of peridomestic animals (cats, foxes, mice, etc.) infected in and around dairy farms and in the wild.
It seems likely we are only seeing the tip of the H5N1 iceberg.
All of which brings us to a lengthy, and at times highly technical, article from researchers at the MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK, that attempts to model, and quantify the spread of H5N1 in US dairy cattle.
As mathematical models are only as good as the data you feed into them, the parsimonious release of data has forced many assumptions to be made. This is a problem that extends far beyond just cattle herds (see Nature: Lengthy Delays in H5N1 Genome Submissions to GISAID).
The main takeaway from this report, however, is that significant under-reporting of H5N1 in dairy herds is likely.
The authors write:
The model projects that the majority of the initial national disease burden is focused within West Coast states, due to their existing trade patterns with Texas, and the size of their respective dairy industries. However, East Coast states are not without risk of currently housing infected herds, as our model suggests that a considerable degree of under-reporting is misrepresenting the true size of the epidemic.
A clear result from Fig. 2 and Table 1 is that some states are particularly likely to be home to infected herds, but have yet to identify and report infections. Most notable are Arizona, Wisconsin, Indiana, and Florida. Arizona has the largest mean herd size in the country (Supplementary Material Section 1), and extensive trade connections with Texas and California (Supplementary Material Section 2.4)—states particularly burdened with infection. Wisconsin, while farther from the epidemic epicenter, has the largest number of dairy herds in the country—6216.
While Florida has a modestly sized dairy sector, and is located on the east coast, it has one of the highest mean herd sizes in the country, as their industry is predominantly made up of a few very large holdings. It also imports more cattle from Texas than its neighbors. Indiana presents itself as having a high likelihood of probable infection due both to having a very high number of dairy herds, but also due to its frequent trading links with Wisconsin.
I've only reproduced the abstract and a few excerpts below. Follow the link to read the report in its entirety. I'll have a postscript when you return.
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, Katharina Hauck & Neil Ferguson
Nature Communications volume 16, Article number: 4308 (2025) Cite this article
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.
(SNIP)
In this study, we estimate the true size of the current epidemic via a stochastic metapopulation transmission model capturing 9,308,707 milk cows distributed across 35,974 herds across the 48 continental US states, as counted in the 2022 agricultural census11. Epidemiological parameters are estimated by fitting to outbreak data via a Bayesian evidence synthesis approach22. The movement of cattle between herds and states is captured using probabilistic outputs of the US Animal Movement Model (USAMM)23 and verified using actual 2016 ICVI data14. Mechanistic modeling assumptions are made relating the probability of detecting and reporting an infected herd proportional to the number of infected cattle and total population size of the herd, irrespective of the US state they reside in.
The model successfully simulates outbreaks for US states that have frequently reported outbreaks, such as California. We estimate the rates of under-reporting by state, by comparing the number of confirmed outbreaks with model simulated trajectories, and present the anticipated rates of positivity for cattle tested upon leaving each state over time. We further use this model to interrogate the impact of intervention methods to date on the underlying epidemiological dynamics, and quantify the extent of uncertainty in the scale of the current epidemic, highlighting the most pressing data streams to capture.
(SNIP)
In conclusion, our model demonstrates that we cannot definitively conclude that the current number of reported outbreaks is a true representation of the scale of the current H5N1 influenza epidemic in dairy cattle.
Significant under-reporting is likely, and the differences in dairy herd population distributions across states have aided in spreading disease across the west coast. Current mandatory interventions are insufficient for controlling the spread of disease, and voluntary testing and interventions are severely under-utilised. Significant increases in testing are urgently required to reduce the uncertainty of model projections and provide decision-makers with a more accurate picture of the true scale of the national epidemic.
(Continue . . . )
The good news is that there is still no sign of human-to-human transmission of the virus, although the regrettable lack of testing limits our ability to make definitive statements.
Meanwhile, the continued lack of nationwide, aggressive testing of livestock (and humans) - now more than a year into this crisis - leaves us vulnerable to being blindsided by this highly mutable H5 virus.
