Regional and temporal characteristics of bovine tuberculosis of cattle in Great Britain

Abstract

Bovine tuberculosis (TB) is a chronic disease in cattle that causes a serious food security challenge to the agricultural industry in terms of dairy and meat production. Spatio-temporal disease analysis in terms of time trends and geographic disparities of disease dynamics can provide useful insights into the overall efficiency of control efforts as well as the relative efficiency of different management measures towards eradication. In GB, Scotland has had a risk based surveillance testing policy under which high risk herds are tested frequently, and in September 2009 was officially declared as TB free. Wales have had an annual or more frequent testing policy for all cattle herds since January 2010, while in England several herds are still tested every 4 years except some high TB prevalence areas where annual testing is applied. Time series analysis using publicly available data for total tests on herds, total cattle slaughtered, new herd incidents, and herds not TB free, were analysed globally for GB and locally for the constituent regions of Wales, Scotland, West, North, and East England. After detecting trends over time, underlying regional differences were compared with the testing policies in the region. Total cattle slaughtered are decreasing in Wales, Scotland and West England, but increasing in the North and East English regions. New herd incidents, i.e., disease incidence, are decreasing in Wales, Scotland, West English region, but increasing in North and East English regions. Herds not TB free, i.e., disease prevalence, are increasing in West, North, and East English regions, while they are decreasing in Wales and Scotland. Total cattle slaughtered were positively correlated with total tests in the West, North, and East English regions, with high slopes of regression indicating that additional testing is likely to facilitate the eradication of the disease. There was no correlation between total cattle slaughtered and total tests on herds in Wales indicating that herds are tested frequent enough in order to detect all likely cases and so control TB. The main conclusion of the analysis conducted here is that more frequent testing is leading to lower TB infections in cattle both in terms of TB prevalence as well as TB incidence.

A big-data spatial, temporal and network analysis of bovine tuberculosis between wildlife (badgers) and cattle

“…Cattle have an infection cycle within the year lasting 6 months possibly corresponding to winter housing lasting four months (Moustakas & Evans, 2016) and a longer term oscillation of around three to three and half years. The negative cycle of 37 months in cattle is likely to derive from cattle testing: in the analysis we have averaged several scenarios, these included annual testing when the percentage of infected herds is > 1% and testing every four years (48 months) when infected herds are 0.2% or less according to EU directives.…”

“…There are also additional financial and other costs for the farming community and the society in general (Enticott, 2001) despite the fact that it rarely poses a threat to humans (Torgerson & Torgerson, 2008). Efforts have been made since the Second World War to reduce the impact of the disease, while these were initially successful and the disease reached a minimum in the 1970s it has been increasing in both incidence and prevalence since then (Abernethy et al, 2013;Moustakas & Evans, 2016).…”

Using geographically weighted regression to explore the spatially heterogeneous spread of bovine tuberculosis in England and Wales

“…Both have applied different policies which have been designed to suit the level of risk in those areas such as increased testing and testing of contiguous herds following an incident where environmental or wildlife transmission is likely, or using a more sensitive test in low incidence areas to ensure the disease is eliminated before it becomes endemic. Recently, regional differences in a number of measures of bTB have been examined and have provided information on the effectiveness of bTB control polices in different areas (Moustakas and Evans 2016), but the reasons behind the spatial heterogeneity of bTB are not well understood.…”

Spatio-temporal data mining in ecological and veterinary epidemiology

“…Understanding the spread of any disease is a highly complex and interdisciplinary exercise as biological, social, geographic, economic, and medical factors may shape the way a disease moves through a population and optionsfor its eventual control or eradication (Moustakas and Evans 2016a;Oleś et al 2012). Disease spread poses a serious threat in animal and plant health and has implications for ecosystem functioning and species extinctions (Fisher et al 2012) as well as implications in society through food security and potential disease spread in humans (Graham et al 2008;Tomley and Shirley 2009).…”