Evidence map›Paper›PMID 42724695›Full record

ArticleFrontiers in veterinary science2026

Vaccinating wild badgers against bovine tuberculosis: an overview of 16 years of vaccine delivery in England.

Andrew Robertson, Clare H Benton

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2026. 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

2 authors.

Andrew Robertson *Department for Environment, Food and Rural Affairs, Bristol, United Kingdom.
Clare H Benton *Animal and Plant Health Agency, National Wildlife Management Centre, Gloucestershire, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The European badger ( Methods: Here we provide a comprehensive overview of 16 years of badger vaccination delivery in England, summarizing national deployment trends, geographical expansion, recorded welfare-related observations, operational efficiency in government led programmes, and the effects of culling history on trapping success. Results: From 2010 to 25 there were 84,085 trap nights, resulting in 25,692 vaccine doses administered to wild badgers in England. Visual welfare assessments by lay vaccinators recorded >99% of badgers as normal for demeanor, respiration, condition, and movement. Minor injuries such as abrasions to the forelimbs were recorded in 4.2% of badgers with serious injuries extremely rare (0.03% of captures) and veterinary callouts required in only 0.04% of events. Trapping efficiency varied by month and trap location and was significantly higher in unculled populations, than those where culling had recently taken place. In post-cull areas, trapping success increased steadily with time, which may suggest partial population recovery and increasing trap encounter rates. Discussion: These results show that badger vaccination in England has expanded substantially and can be delivered across diverse landscapes, including areas recently subject to culling. While vaccination using traps is unlikely to become a landscape-wide tool due to costs and logistical constraints, it can act as a targeted intervention in areas where badgers contribute meaningfully to disease transmission. These findings provide robust operational evidence to inform policy and support the strategic deployment of badger vaccination as part of England's evolving bTB control strategy.

Indexed as

badgerBCGbovine tuberculosisMycobacterium bovisvaccinationwildlife disease

Identifiers

PMID42724695
PMCPMC13560776

What OpenQuestion holds

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Registered trials

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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.