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Investigation of the association between the Enferplex bovine tuberculosis antibody test and the future risk of bovine tuberculosis in irish cattle in infected herds: a pilot field study

2023-08-17, Madden, Jamie M., Casey-Bryars, Miriam, More, Simon John, Barrett, Damien J., Gormley, Eamonn, Ryan, Eoin Gerard

The Single Intradermal Comparative Tuberculin Test (SICTT) and the interferon-gamma (IFN-γ) assay are the approved diagnostic tests for bovine tuberculosis (bTB) in Ireland. The aim of this pilot study was to explore if there was any added diagnostic benefit from applying the Enferplex bTB test (an antibody test) in severe bTB herd breakdowns after the removal of cattle that had tested positive to the SICTT and the IFN-γ test. In addition to the normal bTB testing and management protocols, the animals in these herds that tested negative to SICTT and the IFN-γ test were followed forward for a period of two years. All animals were tested by Enferplex at enrolment. The time to subsequent bTB detection (diagnosed with SICTT/IFN-γ tests or detection of visible lesions at routine slaughter) for animals that tested positive or negative to the Enferplex bTB test at the start of the study was compared using Kaplan–Meier survival curves and Cox based survival models. Of the 484 enrolled animals (from 11 herds), 171 (35.3%) and 151 (31.1%) initially tested positive in the Enferplex assay under the high sensitivity and high specificity interpretation settings respectively. The results of the survival analysis showed that there was no difference in the survival time to a positive diagnosis with bTB during the follow-up period between animals initially classified as positive and negative by the Enferplex test. Further research is warranted to explore the potential benefit of using the Enferplex test in other scenarios.

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Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland

2021-06-10, Madden, Jamie M., More, Simon John, Teljeur, Conor, Gleeson, Justin, Walsh, C. (Cathal), McGrath, Guy

Like most countries worldwide, the coronavirus disease (COVID-19) has adversely affected Ireland. The aim of this study was to (i) investigate the spatio-temporal trend of COVID-19 incidence; (ii) describe mobility trends as measured by aggregated mobile phone records; and (iii) investigate the association between deprivation index, population density and COVID-19 cases while accounting for spatial and temporal correlation. Standardised incidence ratios of cases were calculated and mapped at a high spatial resolution (electoral division level) over time. Trends in the percentage change in mobility compared to a pre-COVID-19 period were plotted to investigate the impact of lockdown restrictions. We implemented a hierarchical Bayesian spatio-temporal model (Besag, York and Mollié (BYM)), commonly used for disease mapping, to investigate the association between covariates and the number of cases. There have been three distinct “waves” of COVID-19 cases in Ireland to date. Lockdown restrictions led to a substantial reduction in human movement, particularly during the 1st and 3rd wave. Despite adjustment for population density (incidence ratio (IR) = 1.985 (1.915–2.058)) and the average number of persons per room (IR = 10.411 (5.264–22.533)), we found an association between deprivation index and COVID-19 incidence (IR = 1.210 (CI: 1.077–1.357) for the most deprived quintile compared to the least deprived). There is a large range of spatial heterogeneity in COVID-19 cases in Ireland. The methods presented can be used to explore locally intensive surveillance with the possibility of localised lockdown measures to curb the transmission of infection, while keeping other, low-incidence areas open. Our results suggest that prioritising densely populated deprived areas (that are at increased risk of comorbidities) during vaccination rollout may capture people that are at risk of infection and, potentially, also those at increased risk of hospitalisation.

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Spatial and network characteristics of Irish cattle movements

2020-10, Tratalos, Jamie A., Madden, Jamie M., McGrath, Guy, Graham, David A., Collins, Áine B., More, Simon John

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.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.

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

2022-07, Douglass, Alexander P., O'Grady, Luke, McGrath, Guy, Tratalos, Jamie A., More, Simon John, Madden, Jamie M., McAloon, Conor G., et al.

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.

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Prescribing and sales of intramammary antimicrobials in Ireland in 2019 and 2020: the role of milk purchasers

2022-11-19, More, Simon John, Madden, Jamie M., McAloon, Catherine I.

Background: In Ireland between 2008 and 2022, intramammary antimicrobial (AM) products could be prescribed by a veterinary practitioner under what was known as Schedule 8 (or remote) prescribing. Under this prescribing route, an annual herd visit was not required when criteria were met as outlined in Animal Remedies Regulation 2007 to 2017 (statutory instruments No. 786/2007 and 558/2017). Under this prescribing route, the responsibilities of the milk purchaser, the farmer and the veterinary practitioner were each outlined, and a written mastitis control programme (MCP) was required. Milk purchasers implemented MCPs on participating farms (so-called MCP herds) with support from veterinary practitioner(s) who undertook Schedule 8 prescribing of intramammary AM tubes. This study seeks a clearer understanding of the role of milk purchasers in the prescribing and sale of intramammary AM products in Ireland during 2019 and 2020, whilst this Regulation was in force. Specifically, the study sought insights into the role of milk purchasers in the prescribing and sale of intramammary AM products in the Irish dairy industry during 2019 and 2020, using anonymised and highly aggregated milk purchaser data. The study also provided insights into milk quality among supplying herds during this period. Methods: For this study, we had access to anonymised, highly aggregated data from all milk purchasers that operated a MCP on at least some of their supplying herds during 2019 or 2020. Data collection was undertaken by the Department of Agriculture, Food and Marine. Data analysis was primarily descriptive. Results: Data were available on 11 milk purchasers (64.7% of all) and 13,251 supplying herds. Of these, 52% were MCP herds. The quality of milk from supplying herds varied significantly by month, year and milk purchaser. During 2019 and 2020, there was a single Schedule 8 prescriber (a private veterinary practitioner prescribing intramammary AMs as part of a MCP), on average, for 549.3 herds. The sale of intramammary AM products through milk purchasers represented 15.2% and 26.9% of national sales in in-lactation and dry cow tubes, respectively. There was an overall 2% increase in sales through milk purchasers between 2019 and 2020. Few European Medicines Agency (EMA) category B (‘Restrict’) intramammary AM products were sold by milk purchasers. For both in-lactation and dry cow tubes, there was a statistically significant association between EMA classification and route of sale (through milk purchasers or otherwise).

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

2022-04, Casey-Bryars, Miriam, Tratalos, Jamie A., Graham, David A., Guelbenzu Gonzalo, Maria, Barrett, Damien J., O'Grady, Luke, Madden, Jamie M., McGrath, Guy, More, Simon John

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 posteradication 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.

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Presymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

2021-06-28, Casey, Miriam, Griffin, John M., McAloon, Conor G., Byrne, Andrew W., Madden, Jamie M., McEvoy, David, Collins, Áine B., Hunt, Kevin, Barber, Ann, Butler, Francis, Lane, Elizabeth, O'Brien, Kirsty, Wall, Patrick G., Walsh, Kieran, More, Simon John

Objective To estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset.Setting/design Secondary analysis of international published data.Data sources Meta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately.Participants Data from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020.Methods Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated.Outcome measures Transmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission.Results Based on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from −2.6 (95% CI −3.0 to –2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%).Conclusions There is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context.

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

2021-11, Madden, Jamie M., McGrath, Guy, Sweeney, James, Murray, Gerard M., Tratalos, Jamie A., More, Simon John

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.