Now showing 1 - 10 of 19
  • Publication
    Epidemic modelling of bovine tuberculosis in cattle herds and badgers in Ireland
    Bovine tuberculosis, a disease that affects cattle and badgers in Ireland, was studied via stochastic epidemic modeling using incidence data from the Four Area Project (Griffin et al., 2005). The Four Area Project was a large scale field trial conducted in four diverse farming regions of Ireland over a five-year period (1997-2002) to evaluate the impact of badger culling on bovine tuberculosis incidence in cattle herds. Based on the comparison of several models, the model with no between-herd transmission and badger-to-herd transmission proportional to the total number of infected badgers culled was best supported by the data. Detailed model validation was conducted via model prediction, identifiability checks and sensitivity analysis. The results suggest that badger-to-cattle transmission is of more importance than between-herd transmission and that if there was no badger-to-herd transmission, levels of bovine tuberculosis in cattle herds in Ireland could decrease considerably.
      52
  • Publication
    Epithelium-on Corneal Cross-linking for Progressive Keratoconus: Two-year Outcomes
    (Jaypee Brothers Medical Publishing, 2018-12) ; ;
    Corneal cross-linking (CXL) has been established as a successful treatment tool for the treatment of progressive keratoconus in terms of slowing or halting progressive corneal steepening and thinning and even on some occasions, reversing the steepening. To date the Dresden epithelium-off protocol is regarded as the gold standard and the epithelium-on (epi-on) approaches have met with less success. Both doctors and patients would welcome an epi-on CXL procedure that provided good outcomes as the morbidity with epi-on CXL is so much less and the safety is enhanced. Patient comfort is greater with the epi-on techniques when compared to epi-off. This study looked at 82 eyes that had documented progression of keratoconus and then underwent epi-on CXL using the CXLO system. The results show that corneal steepening can be halted and even reversed over a 2-year follow-up period with no complications noted. Over the 24 months post treatment on average there was a decrease in all keratometry values, BAD and ISV when compared to before treatment with IHD being marginally increased. Further studies over a longer follow-up period are required but recent publications using the same approach are validating the findings seen in this study.
      249
  • Publication
    Spatio-Temporal Modelling of TB in Cattle Herds
    (UCLA Department of Statistics, 2012-08)
    We examine spatial association of bovine TB in cattle herds using data from Ireland. Badgers (Meles meles), a protected species under the Wildlife Act 1976 (OAG 2012), have been implicated in the spread of the disease in cattle. Current disease control policies include reactive culling (in response to TB outbreaks) of badgers in the index and neighbouring farms. Kelly and More (2011) using generalized linear geostatistical models, established that TB clusters in cattle herds and estimated the practical spatial ranges at which this occurs. Here this work is extended by taking into account possible anisotropy. Changes in spatial association over two time periods are also examined. The results have direct implications for establishing scale and direction in reactive culling. They are also of import regarding the evaluation of vaccines for badgers and cattle.
      98
  • Publication
    Towards reliable spatial prediction
    (ECOSTA Econometrics and Statistics, 2018-12-16) ;
    Estimation of the variogram and associated parameters in spatial analysis is important for assessing spatial dependence and in predicting values of the measured variable at unsampled locations i.e. kriging. A simulation study is implemented to compare the performance of (i) Gaussian restricted maximum likelihood (REML) estimation, (ii) curve-fitting by ordinary least squares and (iii) nonparametric Shapiro-Botha estimation for estimating the covariance structure of a stationary Gaussian spatial process and a spatial process with t-distributed margins. Processes with Matern covariance functions are considered and the parameters estimated are the nugget, partial sill and practical range. Both parametric and nonparametric bootstrap distributions of the estimators are computed and compared to the true marginal distributions of the estimators. Gaussian REML is the estimator of choice for both Gaussian and t-distributed data and all choices of Matern variogram. However, accurate estimation of the Matern shape parameter is critical to achieving a good fit while this does not affect the Shapiro-Botha estimator. The parametric and nonparametric bootstrap both performed well, the latter being better for the Shapiro-Botha estimates. A numerical example, obtained from environmental monitoring, is included to illustrate the application of the methods and the bootstrap.
      53
  • Publication
    Joint Spatio-Temporal Modeling of Mycobacterium bovis Infections in Badgers and Cattle - Results from the Irish Four Area Project
    (De Gruyter, 2013-06)
    In Ireland and in the UK, bovine tuberculosis(bTB) infects cattle and wildlife badgers (Meles meleslinnaeus) and badgers contribute to the spread of the disease in cattle. Isotropic and anisotropic spatio-temporalmodels are fitted to cattle herd and badger settbTB incidence data from the Four Area Project using sequences of linear geostatistical models. An association was found between the spatial distribution of the disease in cattle and badgers in two of three areas. The limited association may be due to irregularity of sett territories,fragmentation of farms, TB-test insensitivity, temporal lags associated with transmission or non-spatial transmission. A statistical methodology is outlined whereby hypotheses related to spatial correlation structure may be tested.
      283
  • Publication
    Spatio-temporal modeling of TB in cattle herds
    (Journal of Environmental Statistics, 2012-08)
    We examine spatial association of bovine TB in cattle herds using data from Ireland. Badgers (Meles meles), a protected species under the Wildlife Act 1976 (OAG 2012), have been implicated in the spread of the disease in cattle. Current disease control policies include reactive culling (in response to TB outbreaks) of badgers in the index and neighbouring farms. Kelly and More (2011) using generalized linear geostatistical models, established that TB clusters in cattle herds and estimated the practical spatial ranges at which this occurs. Here this work is extended by taking into account possible anisotropy. Changes in spatial association over two time periods are also examined. The results have direct implications for establishing scale and direction in reactive culling. They are also of import regarding the evaluation of vaccines for badgers and cattle.
      291
  • Publication
    A simulation comparison of estimators of spatial covariance parameters and associated bootstrap percentiles
    (UCLA Department of Statistics, 2018-09) ;
    A simulation study is implemented to study estimators of the covariance structure of a stationary Gaussian spatial process and a spatial process with t-distributed margins. The estimators compared are Gaussian restricted maximum likelihood (REML) and curve-fitting by ordinary least squares and by the nonparametric Shapiro-Botha approach. Processes with Matérn covariance functions are considered and the parameters estimated are the nugget, partial sill and practical range. Both parametric and nonparametric bootstrap distributions of the estimators are computed and compared to the true marginal distributions of the estimators. Gaussian REML is the estimator of choice for both Gaussian and t-distributed data and all choices of the Matérn covariance structure. However, accurate estimation of the Matérn shape parameter is critical to achieving a good fit while this does not affect the Shapiro-Botha estimator. The parametric bootstrap performed well for all estimators although it tended to be biased downward. It was slightly better than the nonparametric bootstrap for Gaussian data, equivalent to it for t-distributed data and worse overall for the Shapiro-Botha estimates. A numerical example, obtained from environmental monitoring, is included to illustrate the application of the methods and the bootstrap.
      449
  • Publication
    A neural network analysis of Lifeways cross-generation imputed data
    (BioMed Central, 2018-12-14)
    Objectives: Neural networks are a powerful statistical tool that use nonlinear regression type models to obtain predictions. Their use in the Lifeways cross-generation study that examined body mass index (BMI) of children, among other measures, is explored here. Our aim is to predict the BMI of children from that of their parents and maternal and paternal grandparents. For comparison purposes, linear models will also be used for prediction. A complicating factor is the large amount of missing data. The missing data may be imputed and we examine the effects of different imputation methods on prediction. An analysis using neural networks (and also linear models) that uses all available data without imputation is also carried out, and is the gold standard by which the analyses with imputed data sets are compared. Results: Neural network models performed better than linear models and can be used as a data analytic tool to detect nonlinear and interaction effects. Using neural networks the BMI of a child can be predicted from family members to within roughly 2.84 units. Results between the imputation methods were similar in terms of mean squared error, as were results based on imputed data compared to un-imputed data.
      211
  • Publication
    Spatial clustering of TB-infected cattle herds prior to and following proactive badger removal
    (Cambridge University Press, 2011-08) ;
    Bovine tuberculosis (TB) is primarily a disease of cattle. In both Ireland and the UK, badgers (Meles meles) are an important wildlife reservoir of infection. This paper examined the hypothesis that TB is spatially correlated in cattle herds, established the range of correlation and the effect, if any, of proactive badger removal on this. We also re-analysed data from the Four Area Project in Ireland, a large-scale intervention study aimed at assessing the effect of proactive badger culling on bovine TB incidence in cattle herds, taking possible spatial correlation into account. We established that infected herds are spatially correlated (the scale of spatial correlation is presented), but at a scale that varies with time and in different areas. Spatial correlation persists following proactive badger removal.
      408Scopus© Citations 17
  • Publication
    Characterizing dependence of Irish sitka spruce stands using spatio-temporal sum-metric models
    Individual tree dependence in forest plots is spatially dependent and changes over time, and the magnitude of spatial dependence may also change over time, particularly in stands subjected to thinning. Models for tree dependence in the literature have been mainly restricted to either spatial models or temporal models. We extend these to spatio-temporal models. The data are from three long-term, repeatedly measured, experimental plots of Sitka spruce (Picea sitchensis [Bong.] Carr.) in Co. Wicklow, Ireland, with thinning treatments of unthinned, 40% thinned, and 50% thinned, respectively. A model for tree by diameter at breast height, over all locations in each plot and all time points, was fitted with fixed covariates and with a sum-metric spatio-temporal variogram for the covariance structure. In the variogram, the spatial correlation component followed a wave function (due to competition at small distances). The correlation over time also followed a wave variogram, whereas the spatio-temporal anisotropy captured the space-time interaction. The models indicate, once fixed effects are accounted for, that spatial variability and correlation are more important than temporal. Models were fitted to plots with three different treatments to demonstrate that model parameters differed by thinning type but were consistent in their interpretation with thinning type. The models show that describing spatial dependence is important for understanding the nature of tree growth and its prediction.
      301Scopus© Citations 1