Now showing 1 - 10 of 18
- PublicationThe effect of growth rate on reproductive outcomes in replacement dairy heifers in seasonally calving, pasture-based systemsThe effect of average daily gain (ADG) on reproductive outcomes in replacement dairy heifers was investigated. All heifers were managed in the typical Irish spring calving, pasture-based system, where the herd calves in 1 block between January and April and the majority of the diet comprises grazed grass. Heifer calves (n = 399) from 7 herds were weighed at birth and at the beginning of the breeding season, and ADG was calculated. Service dates and pregnancy diagnosis results were recorded, and conception dates were calculated. Days open (DO) was defined as the number of days between the beginning of the breeding season and conception. Genetic data were retrieved from the Irish Cattle Breeding Federation database. A Cox proportional hazard model was constructed to identify variables with a significant effect on DO. An accelerated failure time model was used to predict survival curves and median survival times for different combinations of the significant variables. The ADG ranged from 0.41 to 0.91 kg/d, with a median of 0.70 kg/d. Frailty effect of farm within year, maintenance subindex of the economic breeding index, and ADG had a significant effect on DO. Derived from the final accelerated failure time model, the predicted median DO for a heifer with an ADG of 0.40, 0.70, or 0.90 kg/d aged 443 d at the beginning of the breeding season and with a maintenance subindex in the second tercile were 27, 16, and 11 d, respectively.
257Scopus© Citations 6
- PublicationChanging epidemiology of the tick-borne bovine parasite, Babesia divergensBovine babesiosis is caused by the tick-borne blood parasite, Babesia divergens. A survey of veterinary practitioners and farmers in Ireland in the 1980’s revealed an annual incidence of 1.7% associated with considerable economic losses. However, two subsequent surveys in the 1990’s indicated a decline in clinical babesiosis. In order to determine whether any such changes have affected the incidence of bovine babesiosis in Ireland, a questionnaire survey of farmers and veterinarians was carried out and compared against data from previous surveys.
- PublicationA HACCP-based approach to mastitis control in dairy herds. Part 1: DevelopmentHazard Analysis and Critical Control Points (HACCP) systems are a risk based preventive approach developed to increase levels of food safety assurance. This is part 1 of a pilot study on the development, implementation and evaluation of a HACCP-based approach for the control of good udder health in dairy cows. The paper describes the use of a novel approach based on a deconstruction of the infectious process in mastitis to identify Critical Control Points (CCPs) and develop a HACCP-based system to prevent and control mastitis in dairy herds. The approach involved the creation of an Infectious Process Flow Diagram, which was then cross-referenced to two production process flow diagrams of the milking process and cow management cycle. The HACCP plan developed, may be suitable for customisation and implementation on dairy farms. This is a logical, systematic approach to the development of a mastitis control programme that could be used as a template for the development of control programmes for other infectious diseases in the dairy herd.
- PublicationEradicating BVD, reviewing Irish programme data and model predictions to support prospective decision makingBovine Viral Diarrhoea is an infectious production disease of major importance in many cattle sectors of the world. The infection is predominantly transmitted by animal contact. Postnatal infections are transient, leading to immunologically protected cattle. However, for a certain window of pregnancy, in utero infection of the foetus results in persistently infected (PI) calves being the major risk of BVD spread, but also an efficient target for controlling the infection. There are two acknowledged strategies to identify PI animals for removal: tissue tag testing (direct; also known as the Swiss model) and serological screening (indirect by interpreting the serological status of the herd; the Scandinavian model). Both strategies are effective in reducing PI prevalence and herd incidence. During the first four years of the Irish national BVD eradication programme (2013–16), it has been mandatory for all newborn calves to be tested using tissue tag testing. During this period, PI incidence has substantially declined. In recent times, there has been interest among stakeholders in a change to an indirect testing strategy, with potential benefit to the overall programme, particularly with respect to cost to farmers. Advice was sought on the usefulness of implementing the necessary changes. Here we review available data from the national eradication programme and strategy performance predictions from an expert system model to quantify expected benefits of the strategy change from strategic, budgetary and implementation points of view. Key findings from our work include (i) drawbacks associated with changes to programme implementation, in particular the loss of epidemiological information to allow real-time monitoring of eradication progress or to reliably predict time to eradication, (ii) the fact that only 25% of the herds in the Irish cattle sector (14% beef, 78% dairy herds) would benefit financially from a change to serosurveillance, with half of these participants benefiting by less than EUR 75 per annum at herd level or an average of EUR 1.22 per cow, and (iii) opportunities to enhance the effectiveness of the current programme, particularly in terms of time to eradication, through enforced compliance with PI removal as currently outlined in programme recommendations. The assembled information provides scientific arguments, contributing to an informed debate of the pros and cons of a change in eradication strategy in Ireland.
462Scopus© Citations 30
- PublicationEstimation of the serial interval and proportion of pre-symptomatic transmission events of COVID-19 in Ireland using contact tracing dataThe serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms. Results After data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The median serial interval was 4 days, mean serial interval was 4.0 (95% confidence intervals 3.7, 4.3) days, whilst the 25th and 75th percentiles were 2 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector. Conclusions Whilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.
136Scopus© Citations 3
- PublicationIncubation period of COVID-19: a rapid systematic review and meta-analysis of observational researchObjectives: The aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19. Design: Rapid systematic review and meta-analysis of observational research. Setting: International studies on incubation period of COVID-19. Participants: Searches were carried out in PubMed, Google Scholar, Embase, Cochrane Library as well as the preprint servers MedRxiv and BioRxiv. Studies were selected for meta-analysis if they reported either the parameters and CIs of the distributions fit to the data, or sufficient information to facilitate calculation of those values. After initial eligibility screening, 24 studies were selected for initial review, nine of these were shortlisted for meta-analysis. Final estimates are from meta-analysis of eight studies. Primary outcome measures: Parameters of a lognormal distribution of incubation periods. Results: The incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters (95% CIs) of 1.63 (95% CI 1.51 to 1.75) and 0.50 (95% CI 0.46 to 0.55), respectively. The corresponding mean (95% CIs) was 5.8 (95% CI 5.0 to 6.7) days. It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates (95% CIs) resulted in a median incubation period of 5.1 (95% CI 4.5 to 5.8) days, whereas the 95th percentile was 11.7 (95% CI 9.7 to 14.2) days. Conclusions: The choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Accordingly, we present an R Shiny app that facilitates updating these estimates as new data become available.
239Scopus© Citations 235
- PublicationThe impact of removal of the seasonality formula on the eligibility of Irish herds to supply raw milk for processing of dairy productsBackground: The dairy industry in Ireland is expanding rapidly, with a focus on the production of high quality milk. Somatic cell counts (SCC) are an important indicator both of udder health and milk quality. Milk sold by Irish farmers for manufacture must comply with EU regulations. Irish SCC data is also subject to a monthly seasonal adjustment, for four months from November to February, on account of the seasonality of milk production in Ireland. In a recent study, however, there was no evidence of a dilution effect on SCC with increasing milk yield in Irish dairy cattle. The aim of this paper is to estimate the impact of removal of the seasonality formula on the eligibility of Irish herds to supply raw milk for processing of dairy products. Methods: Bulk tank SCC data from 2013 were collected from 14 cooperatives in Ireland. The geometric mean of SCC test results was calculated for each calendar month. We then calculated the number of herds and volume of milk supplied falling in three SCC categories (400,000 cells/mL) in Ireland during 2013 based on their geometric mean SCC every month. Each herd was assigned an ‘eligibility to supply’ status (always compliant, under warning (first warning, second warning, third warning) and liable for suspension) each month based on their 3-month rolling geometric mean, using methods as outlined in EU and Irish legislation. Two methods were used to calculate the 3-month rolling geometric mean. We then determined the number of herds and volume of milk supplied by ‘eligibility to supply’ status in Ireland during 2013. All calculations were conducted with and without the seasonality adjustment. Results: The analyses were performed on 2,124,864 records, including 1,571,363 SCC test results from 16,740 herds. With the seasonality adjustment in place, 860 (5.1%) or 854 (5.1%) of herds should have been liable for suspension during 2013 if calculation method 1 or 2, respectively, had been used. If the seasonality adjustment were removed, it is estimated that the number of herds liable for suspension would increase from 860 to 974 (13.2% increase) using calculation method 1, or from 854 to 964 (12.9% increase) using calculation method 2. Conclusions: The modelled impact of such removal would be relatively minor, based on available data, regardless of the method used to calculate the 3-month rolling geometric mean. The focus of the current study was quite narrow, effectively from July to December 2013. Therefore, the results are an underestimate of the total number of herds liable for suspension during 2013. They may also underestimate the true percentage change in herds liable for suspension, with the removal of the seasonality formula. A national herd identifier was lacking from a sizeable percentage of the 2013 bulk tank SCC data, but will be needed if these data are to be meaningfully used for this or other purposes.
245Scopus© Citations 2
- PublicationDevelopment of a syndromic surveillance system for Irish dairy cattle using milk recording dataIn 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.
- PublicationThe prevalence, temporal and spatial trends in bulk tank equivalent milk fat depression in Irish milk recorded herds.Milk fat is important in terms of economic value and in its potential to provide information concerning cow diet and health. Under current milk payment schemes in Ireland farmer income is directly linked to milk fat production.
374Scopus© Citations 7
- PublicationHerd-level risk factors associated with Leptospira Hardjo seroprevalence in Beef/Suckler herds in the Republic of IrelandBackground: The aim of the present study was to investigate risk factors for herd seropositivity to Leptospira Hardjo in Irish suckler herds. Herds were considered eligible for the study if they were unvaccinated and contained ≥ 9 breeding animals of beef breed which were ≥ 12 months of age. The country was divided into six regions using county boundaries. Herd and individual animal prevalence data were available from the results of a concurrent seroprevalence study. Herds were classified as either "Free from Infection" or "Infected" based on a minimum expected 40% within-herd prevalence. Questionnaires were posted to 320 farmers chosen randomly from 6 regions, encompassing 25 counties, of the Republic of Ireland. The questionnaire was designed to obtain information about vaccination; reproductive disease; breeding herd details; the presence of recognized risk factors from previous studies; and husbandry on each farm. Data collected from 128 eligible herds were subjected to statistical analysis. Results: Following the use of Pearson's Chi-Square Test, those variables associated with a herd being "infected" with a significance level of P < 0.2 were considered as candidates for multivariable logistic regression modelling. Breeding herd size was found to be a statistically significant risk factor after multivariable logistic regression. The odds of a herd being positive for leptospiral infection were 5.47 times higher (P = 0.032) in herds with 14 to 23 breeding animals compared with herds with ≤ 13 breeding animals, adjusting for Region, and 7.08 times higher (P = 0.033) in herds with 32.6 to 142 breeding animals. Conclusions: Breeding herd size was identified as a significant risk factor for leptospiral infection in Irish suckler herds, which was similar to findings of previous studies of leptospirosis in dairy herds.
301Scopus© Citations 17