Exploring the Risk Posed by Animals with An Inconclusive Reaction to the Bovine Tuberculosis Skin Test in England and Wales

The single intradermal comparative cervical tuberculin (SICCT) test is the primary test for ante-mortem diagnosis of bovine tuberculosis (TB) in England and Wales. When an animal is first classified as an inconclusive reactor (IR) using this test, it is not subject to compulsory slaughter, but it must be isolated from the rest of the herd. To understand the risk posed by these animals, a case-control study was conducted to measure the association between IR status of animals and the odds of them becoming a reactor to the SICCT at a subsequent test. The study included all animals from herds in which only IR animals were found at the first whole herd test in 2012 and used data from subsequent tests up until the end of 2016. Separate mixed-effects logistic regression models were developed to examine the relationship between IR status and subsequent reactor status for each risk area of England and for Wales, adjusting for other explanatory variables. The odds of an animal becoming a subsequent reactor during the study period were greater for IR animals than for negative animals in the high-risk area (odds ratio (OR): 6.85 (5.98–7.86)) and edge area (OR: 8.79 (5.92–13.04)) of England and in Wales (OR: 6.87 (5.75–8.22)). In the low-risk area of England, the odds were 23 times greater, although the confidence interval around this estimate was larger due to the smaller sample size (11–48, p < 0.001). These findings support the need to explore differential controls for IR animals to reduce the spread of TB, and they highlight the importance of area-specific policies

The "business" of dentistry: Consumers' (patients') criteria in the selection and evaluation of dental services

The dimensions of patient-centred care include not only clinical effectiveness and patient safety, but, importantly, the preferences of patients as consumers of healthcare services. A total of 249 participants were included in the study, with a balanced population proportional representation by age, gender, ethnicity and geographic region of New Zealand. An online questionnaire was used to identify participants' decision-making process, and what factors and barriers for participants to seek dental treatment. Cross-tabulations, Spearman correlation analysis and Pearson Chi-Square analysis were used for the statistical analyses. Three most common reasons for visit were check-up (77%), clean (57%) and relief of pain 36%). A desire to treat a perceived problem was the most common encouraging factor to seek dental care. Cost was the most common barrier to seeking dental services. The majority of participants attended a private practice (84%), with convenience of location and referral from professionals the most likely to influence their choice. Participants felt the most important trait a dental practitioner could demonstrate was to discuss treatment options with them before any treatment. Dental check-up, teeth cleaning and relief of pain were the most common reasons for patients to choose dental services. Cost and ethnicity of the consumers had a significant impact on how dental services were perceived and sought. Dental practitioners may need to reorientate how they express value of oral health practice, not just in regard to communication with patients, but also with government funding agencies

An introduction to overviews of reviews: planning a relevant research question and objective for an overview.

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND: Overviews of systematic reviews are a relatively new approach to synthesising evidence, and research methods and associated guidance are developing. Within this paper we aim to help readers understand key issues which are essential to consider when taking the first steps in planning an overview. These issues relate to the development of clear, relevant research questions and objectives prior to the development of an overview protocol. METHODS: Initial discussions and key concepts for this paper were formed during a workshop on overview methods at the 2016 UK Cochrane Symposium, at which all members of this author group presented work and contributed to wider discussions. Detailed descriptions of the various key features of overviews and their different objectives were created by the author group based upon current evidence (Higgins J, Green S. Cochrane Handbook Syst Rev Interv. 2011;4:5, Pollock M, et al. Sys Rev. 2016;5:190-205, Pollock A, et al. Cochrane overviews of reviews: exploring the methods and challenges. UK and Ireland: Cochrane Symposium; 2016, Pieper D, et al. Res Syn Meth. 2014;5:187-99, Lunny C, et al. Sys Rev. 2016;5:4-12, Hartling L, et al. Comparing multiple treatments: an introduction to overviews of reviews. In 23rd Cochrane Colloquium; 2015, Hartling L, et al. Plos One. 2012;7:1-8, Ballard M, Montgomery P. Res Syn Meth. 2017;8:92-108) and author experiences conducting overviews. RESULTS: Within this paper we introduce different types of overviews and suggest common research questions addressed by these overviews. We briefly reflect on the key features and objectives of the example overviews discussed. CONCLUSIONS: Clear decisions relating to the research questions and objectives are a fundamental first step during the initial planning stages for an overview. Key stakeholders should be involved at the earliest opportunity to ensure that the planned overview is relevant and meaningful to the potential end users of the overview. Following best practice in common with other forms of systematic evidence synthesis, an overview protocol should be published, ensuring transparency and reducing opportunities for introduction of bias in the conduct of the overview.Research conducted by Harriet Hunt referred to within this paper [38] was supported as part of doctoral programme funding by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South West Peninsula (PenCLAHRC). The overview conducted by Pollock [3] was supported by a project grant from the Chief Scientist Office of the Scottish Government. The overview conducted by McClurg [5] was supported by a project grant by the Physiotherapy Research Foundation. Alex Pollock is employed by the Nursing, Midwifery and Allied Health Professions (NMAHP) Research Unit, which is supported by the Chief Scientist Office of the Scottish Government. Pauline Campbell is supported by the Chief Nurses Office of the Scottish Government. The overview conducted by Estcourt [7] was supported by an NIHR Cochrane Programme Grant for the Safe and Appropriate Use of Blood Components. The overview conducted by Brunton [10] was commissioned by the Department of Health as part of an ongoing programme of work on health policy research synthesis

Assessing the effects of the first 2 years of industry-led badger culling in England on the incidence of bovine tuberculosis in cattle in 2013–2015

Culling badgers to control the transmission of bovine tuberculosis (TB) between this wildlife reservoir and cattle has been widely debated. Industry-led culling began in Somerset and Gloucestershire between August and November 2013 to reduce local badger populations. Industry-led culling is not designed to be a randomised and controlled trial of the impact of culling on cattle incidence. Nevertheless, it is important to monitor the effects of the culling and, taking the study limitations into account, perform a cautious evaluation of the impacts. A standardised method for selecting areas matched to culling areas in factors found to affect cattle TB risk has been developed to evaluate the impact of badger culling on cattle TB incidence. The association between cattle TB incidence and badger culling in the first two years has been assessed. Descriptive analyses without controlling for confounding showed no association between culling and TB incidence for Somerset, or for either of the buffer areas for the first two years since culling began. A weak association was observed in Gloucestershire for Year 1 only. Multivariable analysis adjusting for confounding factors showed that reductions in TB incidence were associated with culling in the first two years in both the Somerset and Gloucestershire intervention areas when compared to areas with no culling (IRR: 0.79, 95%CI: 0.72-0.87, p<0.001 and IRR: 0.42, 95%CI: 0.34-0.51, p<0.001 respectively). An increase in incidence was associated with culling in the 2 km buffer surrounding the Somerset intervention area (IRR: 1.38, 95%CI: 1.09-1.75, p=0.008), but not in Gloucestershire (IRR: 0.91, 95%CI: 0.77-1.07, p=0.243). As only two intervention areas with two years’ of data are available for analysis, and the biological cause-effect relationship behind the statistical associations is difficult to determine, it would be unwise to use these findings to develop generalisable inferences about the effectiveness of the policy at present

Data-driven identification of parametric partial differential equations

In this work we present a data-driven method for the discovery of parametric partial differential equations (PDEs), thus allowing one to disambiguate between the underlying evolution equations and their parametric dependencies. Group sparsity is used to ensure parsimonious representations of observed dynamics in the form of a parametric PDE, while also allowing the coefficients to have arbitrary time series, or spatial dependence. This work builds on previous methods for the identification of constant coefficient PDEs, expanding the field to include a new class of equations which until now have eluded machine learning based identification methods. We show that group sequentially thresholded ridge regression outperforms group LASSO in identifying the fewest terms in the PDE along with their parametric dependency. The method is demonstrated on four canonical models with and without the introduction of noise

Nonlinear parametric models of viscoelastic fluid flows

Reduced-order models have been widely adopted in fluid mechanics, particularly in the context of Newtonian fluid flows. These models offer the ability to predict complex dynamics, such as instabilities and oscillations, at a considerably reduced computational cost. In contrast, the reduced-order modeling of non-Newtonian viscoelastic fluid flows remains relatively unexplored. This work leverages the sparse identification of nonlinear dynamics algorithm to develop interpretable reduced-order models for viscoelastic flows. In particular, we explore a benchmark oscillatory viscoelastic flow on the four-roll mill geometry using the classical Oldroyd-B fluid. This flow exemplifies many canonical challenges associated with non-Newtonian flows, including transitions, asymmetries, instabilities, and bifurcations arising from the interplay of viscous and elastic forces, all of which require expensive computations in order to resolve the fast timescales and long transients characteristic of such flows. First, we demonstrate the effectiveness of our data-driven surrogate model to predict the transient evolution and accurately reconstruct the spatial flow field for fixed flow parameters. We then develop a fully parametric, nonlinear model capable of capturing the dynamic variations as a function of the Weissenberg number. While the training data is predominantly concentrated on a limit cycle regime for moderate Wi, we show that the parameterized model can be used to extrapolate, accurately predicting the dominant dynamics in the case of high Weissenberg numbers. The proposed methodology represents an initial step in the field of reduced-order modeling for viscoelastic flows with the potential to be further refined and enhanced for the design, optimization, and control of a wide range of non-Newtonian fluid flows using machine learning and reduced-order modeling techniques