We detected influenza D virus in 18 nasal swab samples from cattle in Ireland that were clinically diagnosed with respiratory disease. Specimens were obtained from archived samples received for routine diagnosis during 2014–2016. Sequencing showed that viruses from Ireland clustered with virus sequences obtained in Europe within the D/swine/OK/1334/2011 clade.

SUMMARY: Q fever (Coxiella burnetii) is a zoonotic disease of increasing public health importance. The objective of this study was to estimate the prevalence of, and risk factors associated with, exposure to C. burnetii in cattle in the Republic of Ireland. Bulk-tank milk samples from 290 dairy herds and 1659 sera from 332 dairy and beef herds, randomly sampled, were tested by indirect ELISA to detect antibodies to C. burnetii. In total, 37·9% of bulk-milk sample herds and 1·8% of sera (from 6·9% of herds) were antibody positive. Of risk factors tested using logistic regression analysis, only large herd size (bulk-milk analysis) and dairy breed (serum analysis) significantly increased the odds of being positive for antibodies to C. burnetii. Herds with positive milk or serum samples were randomly distributed throughout the Republic of Ireland and no clustering was observed. The use of an ELISA to test bulk-milk samples collected by randomized stratified sampling is a cost-effective method by which national herd prevalence can be estimated by active surveillance.

A new Irish bovine tuberculosis (bTB) eradication strategy was launched in 2021. The strategy was formulated following extensive discussions with stakeholders, formal reviews of several aspects of the existing bTB policy and relevant inputs from the latest scientific research projects. A stakeholder discussion body, the TB Forum, had been established in 2018 and this continues under the new strategy, supported by three working groups (scientific, financial and implementation). The strategy sets out actions to address cattle-to-cattle and badger-to-cattle bTB transmission, along with actions to improve farm biosecurity and empower farmers to make their own choices to reduce bTB risk.Large scale vaccination of badgers has been rolled out under the new strategy, with over 20,000 km² covered by the vaccination programme and 6,586 badgers captured in vaccination areas in 2021. Vaccination efforts have been complemented by intensive communications campaigns, including a web enabled software application (“app”) enabling farmers to report the location of badger setts.Cattle which test inconclusive to the tuberculin skin test have been re-tested using a gamma interferon blood test since April 2021, enabling truly infected cattle to be identified more effectively due to the higher sensitivity of this test. An enhanced oversight process has been put in place for herds experiencing extended or repeat bTB breakdowns. Whole genome sequencing is being used to investigate links between breakdowns, with the results supporting operational decision making in case management.Communications, including biosecurity advice, are co-designed with stakeholders, in order to improve their effectiveness. A programme involving veterinary practitioners providing tailored biosecurity bTB advice to their clients was established in 2021 and was rolled out nationally during 2022.A core element of the new strategy is the continual improvement of policies in response to changing bTB risks, informed by scientific research and then implemented with stakeholder consultation.

The IFN-γ (interferon gamma) assay is used in Ireland as an ancillary diagnostic test to the single intradermal comparative tuberculin test (SICTT) to maximise the detection of Mycobacterium bovis infected animals (bTB) in cattle herds. Understanding the relationships between herd and animal risk factors and IFN-γ test results is critical to enable the development and evaluation of policy measures on how best to use the test. In this study, we set out to characterise Irish herds with IFN-γ test positive animals in terms of herd size, number of SICTT reactors and number of IFN-γ positive tests, and to evaluate the IFN-γ test in terms of the test cut-off values. The results showed that larger herds with more SICTT reactors were likely to have more IFN-γ positives in the herd, and herds with an IFN-γ test positive animal that was also positive for bTB lesions at post-mortem had higher numbers of IFN-γ positive animals in the herd. Raising the cut-off values for the IFN-γ test only marginally decreased the combined sensitivity of the IFN-γ and the SICTT for diagnosis of bTB lesioned animals. The analysis has provided valuable information on the performance of the IFN-γ test as it is used under current bTB infection levels in Ireland.

Bovine tuberculosis (bTB) outbreaks, caused by Mycobacterium bovis infection, are a costly animal health challenge. Understanding factors associated with the duration of outbreaks, known as breakdowns, could lead to better disease management policy development. We undertook a retrospective observational study (2012–2018) and employed Finite Mixture Models (FMM) to model the outcome parameter, and to investigate how factors were associated with duration for differing subpopulations identified. In addition to traditional risk factors (e.g., herd size, bTB history), we also explored farm geographic area, parcels/farm fragmentation, metrics of intensity via nitrogen loading, and whether herds were designated controlled beef finishing units (CBFU) as potential risk factors for increased duration. The final model fitted log-normal distributions, with two latent classes (k) which partitioned the population into a subpopulation around the central tendency of the distribution, and a second around the tails of the distribution. The latter subpopulation included longer breakdowns of policy interest. Increasing duration was positively associated with recent (<3 years) TB history and the number of reactors disclosed, (log) herd size, beef herd-type relative to other herd types, number of land parcels, area, being designated a CBFU (“feedlot”) and having high annual inward cattle movements within the “tails” subpopulation. Breakdown length was negatively associated with the year of commencement of breakdown (i.e., a decreasing trend) and non-significantly with the organic nitrogen produced on the farm (N kg/hectare), a measure of stocking density. The latter finding may be due to confounding effects with herd size and area. Most variables contributed only moderately to explaining variation in breakdown duration, that is, they had moderate size effects on duration. Herd-size and CBFU had greater effect sizes on the outcome. The findings contribute to evidence-based policy formation in Ireland.

Bovine tuberculosis (bTB) remains a significant endemic pathogen of cattle herds, despite multi-decadal control programmes being in place in several countries. Understanding the risks of future bTB breakdown (BD) and the associated characteristics of herds and index breakdowns could help inform risk categorisation. Such risk categories could then contribute to tailored management and policies. Here, we estimated the future risk of herd BD for the cohort of herds that were derestricted during 2013 in Ireland using multivariable logit regression models, with a dominance analysis approach. One third of herds that were derestricted in 2013 experienced a breakdown during the follow-up five year period (1469/4459; 33%). BD length was a significant predictor of future risk, primarily driven by long BDs > 230 days relative to short BDs < 130 days (OR 95%CI: 1.157–1.851), as was having had a previous BD (OR 95%CI: 1.012–1.366). Herd-size was the dominant predictor of future risk (accounted for 46% of predicted variance), suggesting significant increase in risk of future breakdown with increasing (log) herd-size (OR 95%CI: 1.378–1.609). There was significant spatial variation in future risk across counties, and it was the second most dominant predictor of future risk (25% of predicted variance). The size of index breakdowns was not a strong predictor of future risk over a 5-year period. These findings can inform a risk-based policy development.