Evidence map›Paper›PMID 41460789›Full record

ArticlePLOS global public health2025

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

Izel Avkan, Suzanne Gokool, Louise E Smith, Genevieve Clapp, Rachel Cox, Amy C Thomas, Ellen Brooks-Pollock

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Izel AvkanPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.ORCID https://orcid.org/0009-0001-0977-4622
Suzanne GokoolUKHSA, United Kingdom Health Security Agency, London, United Kingdom.ORCID https://orcid.org/0000-0002-8451-7044
Louise E SmithBehavioural Science and Insights Unit, United Kingdom Health Security Agency, London, United Kingdom.
Genevieve ClappPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Rachel CoxSchool of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.
Amy C ThomasPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Ellen Brooks-PollockPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID41460789
PMCPMC12747336

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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.