An observational study of ear-tagged calf mortality (1 to 100 days) on Irish dairy farms and associations between biosecurity practices and calf mortality on farms participating in a Johne's disease control program.

Postnatal mortality among replacement stock has a detrimental effect on the social, economic, and environmental sustainability of dairy production. Calf mortality rates vary between countries and show differences in temporal trends; most, however, are characterized by high levels of between-farm variability. Explaining this variation can be difficult because herd-level information on management practices relevant to calf health is often not available. The Irish Johne's Control Programme (IJCP) contains a substantial on-farm monitoring program called the Veterinary Risk Assessment and Management Plan (VRAMP). Although this risk assessment is largely focused on factors relevant to the transmission of paratuberculosis, many of its principles are good practice biocontainment policies that are also advocated for the protection of calf health. The objectives of this study were (1) to quantify mortality in ear-tagged Irish dairy calves between 2016 and 2020 using both survival and risk approaches, (2) to determine risk factors for 100-d cumulative mortality hazard in ear-tagged Irish dairy calves between 2016 and 2020, (3) to determine whether 100-d cumulative mortality hazard was higher in ear-tagged calves within herds registered in the IJCP versus those that were not registered in the IJCP and whether there were differences between these cohorts over time, and (4) within IJCP herds, to determine whether VRAMP score or changes in VRAMP score were associated with 100-d cumulative mortality hazard. Excluding perinatal mortality, the overall 100-d cumulative mortality hazard was 4.1%. Calf mortality was consistently underestimated using risk approaches that did not account for calf censoring. Cox proportional hazards models showed that cumulative mortality hazard was greater in male calves; particularly, calves born to Jersey breed dams and those with a beef breed sire. Mortality hazard increased with increasing herd size, was highest in calves born in herds that contract-reared heifers, and lowest in those born in mixed dairy-beef enterprises. Mortality hazard decreased over time with the mortality hazard in 2020 being 0.83 times that of 2016. Mortality hazard was higher in IJCP-registered herds than nonregistered herds (hazard ratio 1.06, 95% CI 1.01-1.12), likely reflecting differences in herds that enrolled in the national program. However, we detected a significant interaction between IJCP status (enrolled vs. not enrolled) and year (hazard ratio 0.96, 95% CI 0.92-1.00), indicating that the decrease in mortality hazard between 2016 and 2020 was greater in IJCP herds versus non-IJCP herds. Finally, increasing VRAMP scores (indicating higher risk for paratuberculosis transmission) were positively associated with increased calf mortality hazard. Postnatal calf mortality rates in Irish dairy herds declined between 2016 and 2020. Our study suggests that implementation of recommended biocontainment practices to control paratuberculosis in IJCP herds was associated with a reduction in calf mortality hazard.

Modelling transmission of Mycobacterium avium subspecies paratuberculosis between Irish dairy cattle herds.

Bovine paratuberculosis is an endemic disease caused by Mycobacterium avium subspecies paratuberculosis (Map). Map is mainly transmitted between herds through movement of infected but undetected animals. Our objective was to investigate the effect of observed herd characteristics on Map spread on a national scale in Ireland. Herd characteristics included herd size, number of breeding bulls introduced, number of animals purchased and sold, and number of herds the focal herd purchases from and sells to. We used these characteristics to classify herds in accordance with their probability of becoming infected and of spreading infection to other herds. A stochastic individual-based model was used to represent herd demography and Map infection dynamics of each dairy cattle herd in Ireland. Data on herd size and composition, as well as birth, death, and culling events were used to characterize herd demography. Herds were connected with each other through observed animal trade movements. Data consisted of 13 353 herds, with 4 494 768 dairy female animals, and 72 991 breeding bulls. We showed that the probability of an infected animal being introduced into the herd increases both with an increasing number of animals that enter a herd via trade and number of herds from which animals are sourced. Herds that both buy and sell a lot of animals pose the highest infection risk to other herds and could therefore play an important role in Map spread between herds.

Epidemiology of age-dependent prevalence of Bovine Herpes Virus Type 1 (BoHV-1) in dairy herds with and without vaccination.

Many studies report age as a risk factor for BoHV-1 infection or seropositivity. However, it is unclear whether this pattern reflects true epidemiological causation or is a consequence of study design and other issues. Here, we seek to understand the age-related dynamics of BoHV-1 seroprevalence in seasonal calving Irish dairy herds and provide decision support for the design and implementation of effective BoHV-1 testing strategies. We analysed seroprevalence data from dairy herds taken during two Irish seroprevalence surveys conducted between 2010 and 2017. Age-dependent seroprevalence profiles were constructed for herds that were seropositive and unvaccinated. Some of these profiles revealed a sudden increase in seroprevalence between adjacent age-cohorts, from absent or low to close to 100% of seropositive animals. By coupling the outcome of our data analysis with simulation output of an individual-based model at the herd scale, we have shown that these sudden increases are related to extensive virus circulation within a herd for a limited time, which may then subsequently remain latent over the following years. BoHV-1 outbreaks in dairy cattle herds affect animals independent of age and lead to almost 100% seroconversion in all age groups, or at least in all animals within a single epidemiological unit. In the absence of circulating infection, there is a year-on-year increase in the age-cohort at which seroprevalence changes from low to high. The findings of this study inform recommendations regarding testing regimes in the context of contingency planning or an eradication programme in seasonal calving dairy herds.

Prevalence of Bovine Viral Diarrhoea Virus (BVDV), Bovine Herpes Virus 1 (BHV 1), Leptospirosis and Neosporosis, and associated risk factors in 161 Irish beef herds.

BACKGROUND: There are limited data available, in Ireland or elsewhere, to determine the extent of exposure to various endemic diseases among beef cows and factors associated with exposure to causative pathogens. The objectives of this study were to determine the herd and within herd prevalence of Bovine Viral Diarrhoea Virus (BVDV), Bovine Herpes Virus 1 (BHV-1), Leptospirosis and Neosporosis in a large scale study of commercial beef herds on the island of Ireland, and to examine herd level factors associated with exposure to these pathogens in these herds. RESULTS: The average number of cows tested per herd was 35.5 (median 30). Herd level seroprevalence to Bovine Herpesvirus-1(BHV-1), Bovine Viral-Diarrhoea Virus (BVDV), Leptospirosis and Neosporosis was 90%, 100%, 91% and 67%, respectively, while the mean within herd prevalence for the these pathogens was 40%, 77.7%, 65.7% and 5.7%, respectively. The study confirms that the level of seroconversion for the four pathogens of interest increases with herd size. There was also evidence that exposure to one pathogen may increase the risk of exposure to another pathogen. CONCLUSIONS: Herd level seroprevalences were in excess of 90% for BVDV, BHV-1 and Leptosporosis. Larger herds were subject to increased exposure to disease pathogens. This study suggests that exposure to several pathogens may be associated with the further exposure to other pathogens.

A visual representation of cattle movement in Ireland during 2016.

The aim of this study was to create a clear visual representation of the live movements of cattle in the Republic of Ireland over the course of the year 2016. The animation created can be viewed online: https://youtu.be/PTCdPMnenBw This animation was created to be a communication tool to enable stakeholders to appreciate the extent of high risk cattle movements (farm to farm, farm to market to farm) in the Republic of Ireland and to highlight the potential role that these movements may play in the spread of infectious diseases of cattle in Ireland from one farm to another.

The bovine tuberculosis cluster in north County Sligo during 2014-16.

BACKGROUND: Bovine tuberculosis (bTB, caused by infection with Mycobacterium bovis) is endemic in the Irish cattle population, and the subject of a national eradication programme since the late 1950s. During 2014, a substantial area-level bTB outbreak developing in north County Sligo, necessitating the need for an enhanced response. This paper describes this outbreak, the response that was undertaken and some lessons learned. RESULTS: In the north Sligo area between 2014 and 2016, 23 (31.9%) of restricted herds had 4 or more reactors to the single intradermal comparative tuberculin test (SICTT)/animals with bTB lesions disclosed during the restriction, and the majority (55.5%) of test-positive animals were identified as standard reactors to the SICTT. The herds restricted during 2014-16 were typically larger than other herds in the study area and introduced more animals during 2013. M. bovis was also detected in local badgers, but not deer. CONCLUSION: This paper describes a substantial outbreak in north County Sligo over a 3-year period. A coordinated area-based approach was a key feature of the outbreak, and substantial resources were applied to bring the outbreak under control. No definitive source was identified, nor reasons why a substantial number of herds were infected over a relatively short period. A coordinated regional approach was taken, and a number of lessons were learned including the need for urgency, for a team-based approach, for a consistent message when dealing with the public, for an area-based approach, for a degree of flexibility for the breakdown manager, and for molecular tools to assist in answering key questions relating to the source and spread of M. bovis to many herds during this bTB outbreak.

Computing metrics to inform selection of candidate areas for a regionalized approach to bovine tuberculosis eradication in Ireland.

We describe the computation of metrics to inform the selection of areas for a regionalised approach to bovine tuberculosis eradication in Ireland. Our aim was not to recommend suitable regions but to elucidate the criteria used in metric selection and comment on the diversity of metric values amongst regions. The 26 counties of Ireland were compared using 20 metrics, grouped into five categories: region size and cattle population, herd fragmentation, cattle movement, bovine TB testing, badger population and control. Fragmentation metrics, measuring the proportion of herds with land in at least two counties, varied considerably by county, from 1% to 24 %.  Between 25 % and 92 % of moves into herds came from a different county, illustrating the likely disruption in trade that a regionalized approach could entail. Cattle movement networks were combined with a risk model to calculate the proportion of moves which would be deemed risky under a risk-based trading regime and these results were compared to a more traditional approach based on the herd type and test history of each herd, with many fewer moves potentially restricted using the latter approach. We show how correlation between region size and some of the metrics complicates their interpretation.

Can Ingoing Contact Chains and other cattle movement network metrics help predict herd-level bovine tuberculosis in Irish cattle herds?

We used logistic regression to investigate whether the risk of an Irish cattle herd undergoing a bovine tuberculosis (bTB) breakdown increased with the size of the Ingoing Contact Chain (ICC) of previous herd to herd cattle movements, in a sequence up to eight moves back from the most recent, direct, movement into the herd. We further examined whether taking into account the bTB test history of each herd in the chain would improve model fit. We found that measures of cattle movements directly into the herd were risk factors for subsequent bTB restrictions, and the number of herds that animals were coming from was the most important of these. However, in contrast to a previous study in Great Britain, the ICC herd count at steps more remote than direct movements into the herd did not result in better fitting models than restricting the count to direct movements. Restricting the ICC counts to herds which had previously or would in the future test positive for bTB resulted in improved model fits, but this was not the case if only the previous test status was considered. This suggests that in many cases bTB infected animals are moving out of herds before being identified through testing, and that risk-based trading approaches should not rely solely on the previous test history of source herds as a proxy for future risk. Model fit was also improved by the inclusion of variables measuring bTB history of the herd, bTB in neighbouring herds, herd size, herd type, the movement network measures "in strength" and "betweenness", altitude, modelled badger abundance and county. Rainfall was not a good predictor. The most influential measures of bTB in nearby herds (a proxy for neighbourhood infection) were the proportion of herds with a history of bTB whose centroids were within 6 km, or whose boundaries were within 4 km, of the index herd. As well as informing national control and surveillance measures, our models can be used to identify areas where bTB rates are anomalously high, to prompt further investigation in these areas.

Inferring bovine tuberculosis transmission between cattle and badgers via the environment and risk mapping.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is one of the most challenging and persistent health issues in many countries worldwide. In several countries, bTB control is complicated due to the presence of wildlife reservoirs of infection, i.e. European badger (Meles meles) in Ireland and the UK, which can transmit infection to cattle. However, a quantitative understanding of the role of cattle and badgers in bTB transmission is elusive, especially where there is spatial variation in relative density between badgers and cattle. Moreover, as these two species have infrequent direct contact, environmental transmission is likely to play a role, but the quantitative importance of the environment has not been assessed. Therefore, the objective of this study is to better understand bTB transmission between cattle and badgers via the environment in a spatially explicit context and to identify high-risk areas. We developed an environmental transmission model that incorporates both within-herd/territory transmission and between-species transmission, with the latter facilitated by badger territories overlapping with herd areas. Model parameters such as transmission rate parameters and the decay rate parameter of M. bovis were estimated by maximum likelihood estimation using infection data from badgers and cattle collected during a 4-year badger vaccination trial. Our estimation showed that the environment can play an important role in the transmission of bTB, with a half-life of M. bovis in the environment of around 177 days. Based on the estimated transmission rate parameters, we calculate the basic reproduction ratio (R) within a herd, which reveals how relative badger density dictates transmission. In addition, we simulated transmission in each small local area to generate a first between-herd R map that identifies high-risk areas.

The Irish cattle population structured by enterprise type: overview, trade & trends.

BACKGROUND: The cattle sector is the most important economic production unit of the Irish farming and agri-food sector. Despite its relevance, there has been limited quantitative information about the structure of differing cattle production types and of the connections between them. This paper addresses this gap by providing, for the first time, an overview of the Irish cattle population structured by enterprise type. METHODS & RESULTS: We collected data from the cattle register for the period 2015 to 2019 and assigned registered herds to one of 18 different herd types using a recently published herd type classification approach. This allows, for the first time, to exploring changes in enterprise types and subtypes over time, and describing the movements between these subtypes and from these subtypes to slaughter. CONCLUSIONS: The overview and associated classification presented in this study will form the basis for a number of future comparative studies, including cross-sectoral assessments of profitability, estimation of the extent of animal health losses on Irish cattle farms or structural analysis of Greenhouse Gas (GHG) emissions across production systems.

Is there an association between road building and bovine tuberculosis herd risk? A three time-point study in Ireland, 2011-2019.

Bovine tuberculosis (bTB) is a chronic infectious disease caused by Mycobacterium bovis which results in a significant economic cost to cattle industries and governments where it is endemic. In Ireland, the European badger is the main wildlife reservoir of infection. In this study, we investigated whether (motorway) road construction was associated with an increased risk of bTB in associated cattle herds. For this study, we considered three observation periods: pre-construction (2011-2014), construction (2015-2017) and post-construction (2018-2019). We selected 1543 herds situated, based on proximity, between >50 m and <5 km of the roadworks, and extracted information about their herd-size, herd-type, inward animal movements, bTB history, and distance to the roadworks. Generalized linear mixed models were performed, whose outcome were whether a herd experienced a bTB breakdown with ≥1 or ≥3 standard reactor/s, respectively. Herds located at a distance of >3 km from the roadworks were found to be at reduced risk of a bTB breakdown over the construction period compared with those situated within 1 km of the roadworks for ≥1 reactor/s (>3 km and construction vs. <1 km: OR: 0.595, 95 % Confidence Interval (CI): 0.354-0.999) or ≥3 reactors (>3 km and construction vs. <1 km: OR: 0.431, 95 % CI: 0.174-1.067). Other previously reported risk factors such as inward movements, herd-size and herd-type were also associated with bTB risk in the final models (≥1 reactor/s and ≥3 reactors). These findings appear to be consistent with bTB breakdowns being a consequence as opposed to coincident to road construction, given the temporal and spatial consistency of the evidence. The potential for badger social group disturbance leading to the spatial spread of infection to cattle herds, as previously described in the United Kingdom, could be a hypothetical mechanism to explain these findings. However, our findings are not consistent with previous Irish studies, including recent work from another road construction project, albeit running alongside and cross over an existing road rather than construction of a new road as in this case, or experiences from national targeted badger removal. Further research is warranted to verify this pattern occurs elsewhere, and the underlying biological mechanism. Until further data are available, we recommend that badgers are vaccinated, as a precautionary measure, in advance of the commencement of major roadworks.

Development of a syndromic surveillance system for Irish dairy cattle using milk recording data.

In the last decade and a half, emerging vector-borne diseases have become a substantial threat to cattle across Europe. To mitigate the impact of the emergence of new diseases, outbreaks must be detected early. However, the clinical signs associated with many diseases may be nonspecific. Furthermore, there is often a delay in the development of new diagnostic tests for novel pathogens which limits the ability to detect emerging disease in the initial stages. Syndromic Surveillance has been proposed as an additional surveillance method that could augment traditional methods by detecting aberrations in non-specific disease indicators. The aim of this study was to develop a syndromic surveillance system for Irish dairy herds based on routinely collected milk recording and meteorological data. We sought to determine whether the system would have detected the 2012 Schmallenberg virus (SBV) incursion into Ireland earlier than conventional surveillance methods. Using 7,743,138 milk recordings from 730,724 cows in 7037 herds between 2007 and 2012, linear mixed-effects models were developed to predict milk yield and alarms generated with temporally clustered deviations from predicted values. Additionally, hotspot spatial analyses were conducted at corresponding time points. Using a range of thresholds, our model generated alarms throughout September 2012, between 4 and 6 weeks prior to the first laboratory confirmation of SBV in Ireland. This system for monitoring milk yield represents both a potentially useful tool for early detection of disease, and a valuable foundation for developing similar tools using other metrics.

Risk factors for detection of bovine viral diarrhoea virus in low-risk herds during the latter stages of Ireland's eradication programme.

BACKGROUND: A national programme to eradicate bovine viral diarrhoea (BVD) has been in place in Ireland since 2013. To inform decision making in the end stages of eradication, and support the development of post-eradication surveillance strategies, an understanding of risks of infection in a low prevalence system is required. METHODS: A case-control study design was implemented. The study population comprised bovine herds that had calves born and tested negative for BVD virus (BVDV) every year from 2013 to 2019 (n = 46,219 herds). We defined cases as herds which had one or more test positive calves for the first time in 2019 (n = 204). Controls (n = 816) were randomly sampled from the herds which remained test negative in 2019. The effects of herd size, management system, inward movements, including those of potential trojan dams (pregnant animals brought into the herd that could potentially be carrying infected calves in utero), and proximity to herds testing positive in the preceding year, were investigated. Network analysis approaches were used to generate variables measuring connections with test positive herds through inward cattle movements. A generalised linear mixed model, including a county-level random effect, was used to explore these risk factors. RESULTS: Our final model retained ln (herd size) (Odds Ratio (95% CI): 1.72 (1.40, 2.12)), distance from test positive herds (0.54 (0.44, 0.66) for each extra land-parcel boundary crossed to reach the closest herd which tested positive the preceding year), and ln (potential trojan dams + 1) (1.29 (1.05, 1.60)). The same variables were retained in the model where herds with confirmed transient infections only (n = 25) were excluded. CONCLUSIONS: Our findings suggest that care with biosecurity at farm boundaries and visitors and equipment entering the farm, and avoidance or careful risk assessment of purchasing potentially pregnant animals, may help prevent introduction of BVDV to low-risk herds. At policy level, consideration of herd size, proximity to test positive herds and purchasing patterns of potentially pregnant cattle may help target surveillance measures towards the end of the eradication programme.

Spatio-temporal models of bovine tuberculosis in the Irish cattle population, 2012-2019.

INTRODUCTION: Bovine tuberculosis (bTB) is an important zoonotic disease which has serious and sometimes fatal effects on both human and non-human animals. In many countries it is endemic in the cattle population and has a considerable economic impact through losses in productivity and impacts on trade. The incidence rate in Ireland varies by herd and location and it is hoped that statistical disease-mapping models accounting for both spatio-temporal correlation and covariates might contribute towards explaining this variation. METHODS: Ireland was divided into equally sized hexagons for computational efficiency (n = 997). Different spatio-temporal random-effects models (e.g. negative binomial Besag-York-Mollié) were explored, using comprehensive data from the national bTB eradication programme to examine the association between covariates and the number of bTB cattle. Leveraging a Bayesian framework, model parameter estimates were obtained using the integrated nested Laplace approximation (INLA) approach. Exceedance probabilities were calculated to identify spatial clusters of cases. RESULTS: Models accounting for spatial correlation significantly improved model fit in comparison to non-spatial versions where independence between regions was assumed. In our final model at hexagon level, the number of cattle (IR = 1.142, CrI: 1.108 - 1.177 per 1000), the capture of badgers (IR = 5.951, CrI: 4.482 - 7.912), percentage of forest cover (IR = 1.031, CrI: 1.020 - 1.042) and number of farm fragments (IR = 1.012, CrI: 1.009 - 1.015 per 10 fragments) were all associated with an increased incidence of bTB. Habitat suitability for badgers, percentage of dairy herds and the number of cattle movements into the herd were not. As an epidemiological tool and to suggest future work, an interactive online dashboard was developed to monitor disease progression and disseminate results to the general public. CONCLUSION: Accounting for spatial correlation is an important consideration in disease mapping applications and is often ignored in statistical models examining bTB risk factors. Over time, the same regions in Ireland generally show highest incidences of bTB and allocation of more resources to these areas may be needed to combat the disease. This study highlights national bTB incidence rates. Shifting from national level analysis to smaller geographical regions may help identify localised high-risk areas.

Combining expert knowledge and machine-learning to classify herd types in livestock systems.

A detailed understanding of herd types is needed for animal disease control and surveillance activities, to inform epidemiological study design and interpretation, and to guide effective policy decision-making. In this paper, we present a new approach to classify herd types in livestock systems by combining expert knowledge and a machine-learning algorithm called self-organising-maps (SOMs). This approach is applied to the cattle sector in Ireland, where a detailed understanding of herd types can assist with on-going discussions on control and surveillance for endemic cattle diseases. To our knowledge, this is the first time that the SOM algorithm has been used to differentiate livestock systems. In compliance with European Union (EU) requirements, relevant data in the Irish livestock register includes the birth, movements and disposal of each individual bovine, and also the sex and breed of each bovine and its dam. In total, 17 herd types were identified in Ireland using 9 variables. We provide a data-driven classification tree using decisions derived from the Irish livestock registration data. Because of the visual capabilities of the SOM algorithm, the interpretation of results is relatively straightforward and we believe our approach, with adaptation, can be used to classify herd type in any other livestock system.

A large-scale epidemiological model of BoHV-1 spread in the Irish cattle population to support decision-making in conformity with the European Animal Health Law.

We present a new modelling framework to address the evaluation of national control/surveillance programs planned in line with the European Animal Health Law (AHL) for livestock diseases. Our modelling framework is applied to the cattle sector in Ireland where there is need for policy support to design an optimal programme to achieve bovine herpesvirus type 1 (BoHV-1) free status under the AHL. In this contribution, we show how our framework establishes a regional model that is able to mechanistically reproduce the demography, management practices and transport patterns of an entire cattle population without being dependent on continuous livestock registry data. An innovative feature of our model is the inclusion of herd typing, thereby extending these beyond the categories of dairy, beef and mixed herds that are frequently considered in other regional modelling studies. This detailed representation of herd type-specific management facilitates comparative assessment of BoHV-1 eradication strategies targeting different production types with individual strategy protocols. Finally, we apply our model to support current discussions regarding the structure and implementation of a potential national BoHV-1 eradication programme in Ireland.

Spatial and network characteristics of Irish cattle movements.

Our aim was to examine, for the first time, the spatial and network characteristics of cattle movements between herds in the Republic of Ireland (ROI), to inform policy and research of relevance to the surveillance and management of disease in Irish cattle. We analysed movements in 2016 as discrete herd to herd pairings (degree), herd to herd pairings by date of move (contacts) and herd to herd pairings by date and individual animal (transfers), and looked at each of these as movements out of a herd (out degree, out contacts, out transfers) and into a herd (in degree, in contacts, in transfers). We found that the frequency distributions, by herd, of these six move types were all heavily right skewed but in the case of the 'out' data types more closely followed a log-normal than the scale free distribution often reported for livestock movement data. For each distinct herd to herd contact in a given direction, over 90 % occurred only once, whereas the maximum number of occurrences was 62. Herd-level Spearman rank correlations between inward moves (represented as in degree, in contacts, in transfers) and outward moves (out degree, out contacts, out transfers) were weak or even negative whereas correlations between different measures of outward moves or inward moves (e.g. out degree vs. out contacts, in transfers vs. in degree) were stronger. Correlations between these variables and the network measure betweenness varied between r = 0.513 and r = 0.587. Some herds took part in a relatively large number of movements whilst also retaining their cattle for long periods (> 100 days) between moves. In and out degree, contacts and transfers were mapped across Ireland on a 5 km grid, and additionally normalized per 1000 animals and per herd. We found considerable variation in the number of movements by county. Approximately half of transfers were conducted within a single county, but the number and distance of between county movements varied considerably by county of origin and county of destination, with the proportion of moves completed within a single county correlated with its size. Herds exchanging cattle via a market were generally further apart than when moves were made directly herd to herd. For contacts, the distances moved away from the herd were on average greater for origin herds in the west of ROI whereas distances moved to a herd were generally greater for destination herds in the centre-east and the north-west.

Quantifying the role of Trojan dams in the between-herd spread of bovine viral diarrhoea virus (BVDv) in Ireland.

A compulsory national programme to eradicate bovine viral diarrhoea virus (BVDv) began in Ireland on 1 January, 2013. The objective of the current study was to quantify the role of Trojan dams (animal(s) not persistently infected (PI) with BVDv but carrying PI foetus(es) and introduced to the herd while pregnant with the PI foetus(es)) in the farm-to-farm spread of BVDv in Ireland, and to identify herd-level risk factors for producing or introducing a Trojan dam. The study population included all BVD+ calves born in Ireland between 1 January, 2013 and 31 December, 2015, along with their dams. BVD+ calves included all calves on the national programme database with an initial positive or inconclusive virus test, without a confirmatory re-test (status BVDPOS) and those with an initial positive or inconclusive test and a positive confirmatory test (status BVDPI). The Trojan status of dams was determined after considering their history of movement and of potential BVDV exposure, relative to a defined window of susceptibility (WOS; days 30-120 of gestation). During 2013-15, there were 29,422 BVD+ birth events to dams that were not themselves BVD+, including 2526 (8.6%) most-likely attributable to Trojan dams. The percentage of these birth events attributable to Trojan dams was significantly different (P < 0.001) between years, being 7.1% in 2013, 9.2% in 2014 and 10.6% in 2015. During 2013, in 9.9% of herds with one or more BVD+ birth to non-BVD+ dams, at least one of these births was attributed to a Trojan dam. In 2014 and 2015, the percentages were 11.8% and 13.3%, respectively. In 2013, in 7.8% of herds with one or more BVD+ birth to non-BVD+ dams, all of these births were attributable to Trojan dams. In 2014 and 2015, the percentages were 9.2% and 10.7%, respectively. A logistic GEE regression identified dam parity, herd size and an interaction between herd type and season as significant predictors for the birth of a BVD+ calf to a Trojan dam. Significant predictors for the sale of a Trojan dam from BVD+ herds included those selling more than one pregnant female and those with more than 2 BVD+ animals in the herd. Introduction of pregnant adult females is a potential source of BVD+ births in BVD-free herds and may add to the burden of infection in non-BVD-free herds. Addressing this route of transmission will be critical for herds that are now free of infection and wish to continue to purchase animals without introducing it.

Potential infection-control benefit of measures to mitigate the risk posed by Trojan dams in the Irish BVD eradication programme.

In the epidemiology of Bovine Viral Diarrhoea (BVD), Trojan dams (animals that are not persistently infected (PI) with BVD (BVDv) virus but carrying PI foetuses) are a vehicle through which infection can be transmitted. We investigated the degree to which restricting movement of cattle from BVDv infected herds would prevent Trojan births in other herds (effectiveness) and the extent to which this would reduce other, non-Trojan, movements (proportionality). We focussed on Irish herds with BVD + animal(s) present during 2014 and/or 2015. The effect of restricting movements of female animals over 12 months of age from these herds was compared with data collected on Trojan dams that calved in 2015. Four different potential restriction lengths were considered, varying from the period when a BVD + animal was present in the herd, to extending this to 12 months after removal of the last BVD + animal. In terms of effectiveness, none of the four restriction measures evaluated was effective at preventing the movement of all Trojan dams. Between 18.3% and 37.3% of Trojan births in 2015 would have been prevented under the proposed measures, and all Trojan births would have been prevented in between 14.4% and 32.5% of herds with BVD + births. In terms of proportionality, between 4.4% and 15.4% of all females > 12 months of age that moved between herds during 2015 would have been prevented from moving, and between 3.5% and 10.1% of Irish herds with at least one such movement would have been affected. These results show how measures to control the movement of Trojan dams should be targeted in a way that fits the Irish context and reduces the spread of BVDv, without unduly impacting other trade.

Decision support beyond total savings-Eligibility and potential savings for individual participants from changes in the national surveillance strategy for bovine viral diarrhoea (BVD) in Ireland.

Surveillance and management of livestock diseases is often evaluated with reference to expected sector-wide costs. In contrast, we calculate losses or savings for individual herd owners of a change in monitoring strategy during a national cattle disease eradication programme: bovine viral diarrhoea (BVD) in Ireland. The alternative strategy differs in how the disease is identified; by its sample- rather than census-based approach; and by its greater cost per test. We examined the costs faced by each breeding herd if testing were conducted using serology on a sample of young stock, in contrast to the current method of tissue-tag testing of all newborn calves. Following best knowledge of the likely costs, the following input values were used: i) €2.50 per test for tissue-tag testing and €7.66 for serology, ii) serology conducted on a sample of 10 young stock per management group from either the 6-12 month or 9-18 month cohorts; iii) 3 scenarios for the number of management groups: one per herd (M∞), one per 100 cows (M100) and one per 50 cows (M50). We found that many herds would often not be able to supply a suitable sample of young stock for serology or would face higher testing costs than when using tissue tag testing. The largest number (25%) of herds would benefit from participating in the change if sampling were done in October. These could annually save between €2.1 million under M∞ and €0.8 million under M50 (€108 - €49 per herd). However, analysing herd-level data we found that 90% of all Irish breeding herds would save less than €1.42 per cow or €99 in total per annum under M∞, and €0.59 per cow or €36 in total under M50. In a sensitivity analysis, we allowed serology costs to vary between €2 and €10 per animal. Herds at the 10 t h percentile of most savings made from switching would save at most €155 (M∞ at €2 per serology test) but would not save anything under M50 at costs ≥ €10. We conclude that, under these assumptions, the expected reduction in testing costs for the majority of beneficiaries would barely outweigh the practical implications of the strategy switch or the risks to the eradication programme associated with sample based surveillance. This study does not assess the cost-effectiveness of alternatives post-eradication.