Preprint: Quantifying H5N1 Outbreak Potential and Control Effectiveness in High-Risk Agricultural Populations

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Officially, since early 2024 the United States has reported 70 human infections with HPAI H5N1, with 67 (95.7%) linked directly to livestock (cattle or poultry) or animal (wild bird) exposure.  In 3 cases, the exposure has not been determined. 

This doesn't include 7 additional cases - locally confirmed but not verified by the CDC's labs - which are listed as `probable' cases'. 

Nor does it include the 2nd, strongly suspected case in Missouri - the 8 asymptomatic and/or mild cases retrospectively identified by serological testing of dairy workers - or the 3 asymptomatic veterinarians (out of 150 tested) who volunteered for testing at a veterinary conference last September and showed antibodies to the H5N1 virus.

Of note, most of those who tested positive via serology could not recall a significant flu-like illness, suggesting some percentage of cases are  asymptomatic or only mildly symptomatic. 

While no new cases have been confirmed since last February, there are many gaps in our surveillance; including that many farm workers are undocumented and are often afraid to seek testing or treatment for mild or even moderate flu-like illnesses.  

As with all illnesses, passive surveillance always struggles to pick up more than just the tip of the pyramid.  It is not uncommon to see 100 unreported cases for each confirmed case. 

Credit CDC

We've previously seen estimates from the UK (see UK Novel Flu Surveillance: Quantifying TTD) that it could take between 3 and 10 weeks - and anywhere between a few dozen to a few thousand community cases - before community spread would become apparent to authorities. 

A year ago the ECDC issued guidance for member nations on Enhanced Influenza Surveillance to Detect Avian Influenza Virus Infections in the EU/EEA During the Inter-Seasonal Period., which cautioned: 

Sentinel surveillance systems are important for the monitoring of respiratory viruses in the EU/EEA, but these systems are not designed and are not sufficiently sensitive to identify a newly emerging virus such as avian influenza in the general population early enough for the purpose of implementing control measures in a timely way.

So, while the recent lull in human cases may be reassuring, it may not fully reflect the situation on the ground.  

All of which brings us to a new preprint, from researchers at the University of Bristol and the UK's Health Security Agency, which looks at the potential for H5N1 avian influenza outbreaks - and the effectiveness of control measures - among high-risk agricultural populations in the UK. 

While the authors grant that:

Although the current global public health risk is low, reassortment between avian and human seasonal influenza viruses could result in antigenic changes that facilitate human-to-human transmission, potentially transitioning the situation to the next phase (14). This emphasises the need for continuous surveillance and the development of effective control strategies. 

This is a mathematical modeling study based on contact survey data from high-risk (mostly poultry) agricultural workers in the UK.  As with all models, it relies on a number of assumptions - some of which may not hold true - including:

• that symptomatic individuals will isolate themselves on the first day

• that contacts identified through tracing will fully comply with isolation requirements and that the tracing itself is efficient and comprehensive

• that the rate of asymptomatic infection is constant across all age groups

• that the virus remains stable, and epidemiological parameters (e.g., incubation period, R0, and % asymptomatic) remains constant

• that all infections are from close human-to-human contact, excluding fomite or environmental exposures in agricultural settings

While there is a lot to unpack in this study, their primary conclusion is that current control measures (contact tracing, self-isolation) may be insufficient to control outbreaks, and more attention need be paid to detecting asymptomatic infections.

Asymptomatic infections limit the effectiveness of contact tracing and self-isolation, and they are optimally identified and controlled through asymptomatic testing programmes, which have previously shown to be successful at detecting cases (36).

Reintroducing such programmes could enhance current interventions by improving detection of asymptomatic infections. 

This is obviously a tough sell, and previous attempts to do so in the UK have met with considerable resistance (see Pilot of asymptomatic swabbing of humans following exposures to confirmed avian influenza A(H5) in avian species in England, 2021/2022). 

While this study suggests that - with aggressive testing, contact tracing, and isolation procedures - small outbreaks of H5N1 among farm workers can probably be contained, we've seen considerable resistance from farmers both here in the United States and from governments around the globe.  

Due to its length, and technical nature, I've only posted the abstract. Follow the link to read the study in its entirety.  

Quantifying H5N1 outbreak potential and control effectiveness in high-risk agricultural populations

Izel Avkan, Suzanne Gokool, Louise Smith, Genevieve Clapp, Rachel Cox,Amy C Thomas,Ellen Brooks-Pollock
doi: https://doi.org/10.1101/2025.07.22.25331905This article is a preprint and has not been certified by peer review 

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Abstract

Avian influenza is a global public health threat. Since 2021, the ongoing H5N1 panzootic has brought a major shift in H5Nx epidemiology, including unprecedented spread, wide host range and lack of seasonality. Infections in marine mammals, wildlife and livestock have heightened concern for human-to-human transmission and pandemic potential. 

Contact tracing and self-isolation are used as public health measures in the UK to manage contacts of confirmed human cases of avian influenza. In this study, we aimed to estimate potential outbreak sizes and evaluate the effectiveness of contact tracing and self-isolation in managing community outbreaks of H5N1 following spillover from birds to people. 

We characterised contact patterns from an underrepresented agricultural population at high risk of avian influenza exposure through contact with birds (Avian Contact Study). Informed by these realistic social contact data, we modelled outbreak sizes using a stochastic branching process model. Most simulations resulted in small-scale outbreaks, ranging from 0 to 10 cases.

When the basic reproduction number was 1.1, contact tracing and self-isolation reduced the average outbreak size from 41 cases (95% Confidence Interval (CI): 37-46 cases) to 7 cases (95% CI: 6 8 cases), preventing, on average, 8 out of every 10 infections.

However, controls became less effective in reducing the outbreak size when a higher proportion of cases were asymptomatic.

Overall, our findings suggest that contact tracing and self-isolation can be effective at preventing zoonotic infections. Increasing awareness, encouraging self-isolation, and detecting asymptomatic cases through routine surveillance are important components of zoonotic infection containment strategies.

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