William Wint

Cattle movements and bovine tuberculosis in Great Britain

For 20 years, bovine tuberculosis (BTB) has been spreading in Great Britain (England, Wales and Scotland) and is now endemic in the southwest and parts of central England and in southwest Wales, and occurs sporadically elsewhere. Although its transmission pathways remain poorly understood, the diseases distribution was previously modelled statistically by using environmental variables and measures of their seasonality. Movements of infected animals have long been considered a critical factor in the spread of livestock diseases, as reflected in strict import/export regulations, the extensive movement restrictions imposed during the 2001 foot-and-mouth disease outbreak, the tracing procedures after a new case of BTB has been confirmed and the Governments recently published strategic framework for the sustainable control on BTB. Since January 2001 it has been mandatory for stock-keepers in Great Britain to notify the British Cattle Movement Service of all cattle births, movements and deaths. Here we show that movements as recorded in the Cattle Tracing System data archive, and particularly those from areas where BTB is reported, consistently outperform environmental, topographic and other anthropogenic variables as the main predictor of disease occurrence. Simulation distribution models for 2002 and 2003, incorporating all predictor categories, are presented and used to project distributions for 2004 and 2005.

Characteristics of cattle movements in Britain - an analysis of records from the Cattle Tracing System

This paper reviews the main temporal and spatial characteristics of cattle movements in Britain, based on an analysis of records in the British Cattle Movement Service’s Cattle Tracing System (CTS) database, focusing on the period 2001 to 2003, during which notifi cation of cattle movements was mandatory. Movements vary weekly and seasonally according to the production cycle, with peaks in late spring (April) and early autumn ( October), and an average 1·63 million farm-to-farm movements per month, equivalent to 19·6 million per annum. The geographical distribution of these movements appears to be relatively stable from year to year, with the great majority of animals moving less than 100 km per journey, although many tens of thousands move over far greater distances of up to 1000 km. The procedures developed to extract, match, geo-reference, analyse and display movement records have greatly enhanced the utility of the CTS database, in that it is now feasible to assess, monitor and map the spatial dynamics and geographical distribution of cattle movements, and provide this information in standardized format on a regular basis.

Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs

The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification.

Using Random Forest to Improve the Downscaling of Global Livestock Census Data.

Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural populations.

Climate Change and Public Health Policy: Translating the Science

Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character.

The Programme Against African Trypanosomiasis Information System (Paatis)

The Programme against African Trypanosomiasis (PAAT) was established in 1995 and is managed by a joint secretariat composed of FAO, OAU/IBAR, IAEA and WHO. The programme aims to provide direction and focus to the control of trypanosomiasis within the broader context of food security, human health, rural development and sustainable agriculture. This paper describes the PAAT-Information System (PAATIS) which aims to assist decision-support for prioritisation of tsetse control areas and control strategy, thereby facilitating direct contact between programmes and providing a common source of information on tsetse and trypanosomiasis. The system is aimed at a broad range of users and will be available as a beta on a packaged CD-ROM. It will then be widely distributed for evaluation and to generate feedback. The final version will be upgraded on a regular basis and will be complimented by the activities of the PAAT email forum and the PAAT website.

Farming on the edge: farmer attitudes to bovine tuberculosis in newly endemic areas

Defras recent strategy to eradicate bovine tuberculosis (bTB) establishes three spatial zones: high-risk areas (HRAs) and low-risk areas, and an area referred to as ‘the edge’, which marks the areas where infection is spreading outwards from the HRA. Little is known about farmers in the edge area, their attitudes towards bTB and their farming practices. This paper examines farmers’ practices and attitudes towards bTB in standardised epidemiologically defined areas. A survey was developed to collect data on farmer attitudes, behaviours, practices and environmental conditions as part of an interdisciplinary analysis of bTB risk factors. Survey items were developed from a literature review and focus groups with vets and farmers in different locations within the edge area. A case-control sampling framework was adopted with farms sampled from areas identified as recently endemic for bTB. 347 farmers participated in the survey including 117 with bTB, representing a 70per cent response rate. Results show that farmers believe they are unable to do anything about bTB but are keen for the government intervention to help control the spread of bTB.

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

An understanding of the factors that affect the spread of endemic bovine tuberculosis (bTB) is critical for the development of measures to stop and reverse this spread. Analyses of spatial data need to account for the inherent spatial heterogeneity within the data, or else spatial autocorrelation can lead to an overestimate of the significance of variables. This study used three methods of analysis—least-squares linear regression with a spatial autocorrelation term, geographically weighted regression (GWR) and boosted regression tree (BRT) analysis—to identify the factors that influence the spread of endemic bTB at a local level in England and Wales. The linear regression and GWR methods demonstrated the importance of accounting for spatial differences in risk factors for bTB, and showed some consistency in the identification of certain factors related to flooding, disease history and the presence of multiple genotypes of bTB. This is the first attempt to explore the factors associated with the spread of endemic bTB in England and Wales using GWR. This technique improves on least-squares linear regression approaches by identifying regional differences in the factors associated with bTB spread. However, interpretation of these complex regional differences is difficult and the approach does not lend itself to predictive models which are likely to be of more value to policy makers. Methods such as BRT may be more suited to such a task. Here we have demonstrated that GWR and BRT can produce comparable outputs.

Mapping disease data: A usability test of an internet based system of disease status disclosure

Disease maps are important tools in the management of disease. By communicating risk, disease maps can help raise awareness of disease and encourage farmers and veterinarians to employ best practice to eliminate the spread of disease. However, despite the importance of disease maps in communicating risk and the existence of various online disease maps, there are few studies that explicitly examine their usability. Where disease maps are complicated to use, it seems that they are unlikely to be used effectively. The paper outlines an attempt to create an open access, online, searchable map of incidents of bovine tuberculosis in England and Wales, and analyzes its usability among veterinarians. The paper describes the process of creating the map before describing the results of a series of usability trials. Results show the map to score highly on different measures of usability. However, the trials also revealed a number of social and technical limitations and challenges facing the use of online disease maps, including reputational dangers, role confusion, data accuracy, and data representation. The paper considers the challenges facing disease maps and their potential role in designing new methodologies to evaluate the effectiveness of disease prevention initiatives.