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

Communities in university mathematics

This paper concerns communities of learners and teachers that are formed, develop and interact in university mathematics environments through the theoretical lens of Communities of Practice. From this perspective, learning is described as a process of participation and reification in a community in which individuals belong and form their identity through engagement, imagination and alignment. In addition, when inquiry is considered as a fundamental mode of participation, through critical alignment, the community becomes a Community of Inquiry. We discuss these theoretical underpinnings with examples of their application in research in university mathematics education and, in more detail, in two Research Cases which focus on mathematics students' and teachers' perspectives on proof and on engineering students' conceptual understanding of mathematics. The paper concludes with a critical reflection on the theorising of the role of communities in university level teaching and learning and a consideration of ways forward for future research

Self-stabilised fractality of sea-coasts through damped erosion

Erosion of rocky coasts spontaneously creates irregular seashores. But the geometrical irregularity, in turn, damps the sea-waves, decreasing the average wave amplitude. There may then exist a mutual self-stabilisation of the waves amplitude together with the irregular morphology of the coast. A simple model of such stabilisation is studied. It leads, through a complex dynamics of the earth-sea interface, to the appearance of a stationary fractal seacoast with dimension close to 4/3. Fractal geometry plays here the role of a morphological attractor directly related to percolation geometry.Comment: 4 pages, 5 figure

Citizen Science 2.0 : Data Management Principles to Harness the Power of the Crowd

Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge – creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described

Smart cities in a smart world

Very often the concept of smart city is strongly related to the flourishing of mobile applications, stressing the technological aspects and a top-down approach of high-tech centralized control systems capable of resolving all the urban issues, completely forgetting the essence of a city with its connected problems. The real challenge in future years will be a huge increase in the urban population and the changes this will produce in energy and resource consumption. It is fundamental to manage this phenomenon with clever approaches in order to guarantee a better management of resources and their sustainable access to present and future generations. This chapter develops some considerations on these aspects, trying to insert the technological issues within a framework closer to planning and with attention to the social impact

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle