Skip to main content
StreamVetree
Sign in
Large AnimalCase series / Retrospective2 min read · distilled by Vetree AI

Temporal and seasonal trends of bovine tuberculosis in the Irish cattle population (2008-2024).

Madden JM, Gormley E, Breslin P, Barrett D, Brock J, Tratalos JA, Griffin J, Horan M, Casey-Bryars M · The Veterinary record · 31 July 2026

Clinical bottom line

Expanding Irish dairy herd sizes correlate with a doubling of bovine tuberculosis cases from dairy farms since 2008.

Summary

This study examines temporal and seasonal trends in bovine tuberculosis (bTB) in Irish cattle from 2008 to 2024, focusing on identifying drivers of the increased disease burden observed since 2016. Using national surveillance data and negative binomial regression modeling, researchers analyzed changes in cattle demographics, herd management practices, and bTB burden at both herd and animal levels. Key findings reveal that while dairy herd numbers remained stable at approximately 12% of all herds, median dairy herd size expanded significantly from 119 to 172 animals. The proportion of national cattle housed in dairy herds increased from 23% to 34%. Most strikingly, the proportion of individual bTB cases originating from dairy farms doubled over the study period, with dairy herds accounting for 51% of all bTB cases in 2024 compared to 26% in 2008. The authors note potential misclassification biases across years due to policy changes in bTB case disclosure protocols. The substantial increase in bTB burden since 2015 temporally correlates with the expansion of median dairy herd size, suggesting that intensification of dairy production may be a contributing factor. These findings have important implications for targeted surveillance, testing protocols, and biosecurity measures, particularly within the dairy sector. The study serves as a foundational epidemiological analysis to guide further investigation into the multifactorial drivers of bTB resurgence in Ireland.

Large AnimalInternal MedicinePathology

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.