Progress with enhancing veterinary surveillance in the United Kingdom

What can equine surveillance learn from surveillance of other species?

Mary-Ellen Lloyd Tivey of the Royal Veterinary College, suggests that greater collaboration and encouraging engagement from horse owners and vets is key to strengthening scanning surveillance in equine populations.

D2R2: an evidence-based decision support tool to aid prioritisation of animal health issues for government funding

An evidence-based decision support tool, 'D2R2', has been developed by Defra. It contains a wide range of standardised information about exotic and endemic diseases held in 'disease profiles'. Each profile includes 40 criteria used for scoring, enabling D2R2 to provide relative priority rankings for every disease profiled. D2R2 also provides a range of reports for each disease and the functionality to explore the impact of changes in any criterion or weighting on a disease's ranking. These outputs aid the prioritisation and management of animal diseases by government. D2R2 was developed with wide stakeholder engagement and its design was guided by clear specifications. It uses the weighted scores of a limited number of criteria to generate impact and risk scores for each disease, and relies on evidence drawn from published material wherever possible and maintained up to date. It allows efficient use of expertise, as maintained disease profiles reduce the need for on call, reactive, expert input for policy development and enables rapid simultaneous access to the same information by multiple parties, for example during exotic disease outbreaks. The experience in developing D2R2 has been shared internationally to assist others with their development of disease prioritisation and categorisation systems.

Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies

An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)'s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak.

Diseases at the livestock-wildlife interface: status, challenges, and opportunities in the United States

In the last half century, significant attention has been given to animal diseases; however, our understanding of disease processes and how to manage them at the livestock-wildlife interface remains limited. In this study, we conduct a systematic review of the scientific literature to evaluate the status of diseases at the livestock-wildlife interface in the United States. Specifically, the goals of the literature review were three fold: first to evaluate domestic animal diseases currently found in the United States where wildlife may play a role; second to identify critical issues faced in managing these diseases at the livestock-wildlife interface; and third to identify potential technical and policy strategies for addressing these issues. We found that of the 86 avian, ruminant, swine, poultry, and lagomorph diseases that are reportable to the World Organization for Animal Health (OIE), 53 are present in the United States; 42 (79%) of these have a putative wildlife component associated with the transmission, maintenance, or life cycle of the pathogen; and 21 (40%) are known to be zoonotic. At least six of these reportable diseases-bovine tuberculosis, paratuberculosis, brucellosis, avian influenza, rabies, and cattle fever tick (vector control)-have a wildlife reservoir that is a recognized impediment to eradication in domestic populations. The complex nature of these systems highlights the need to understand the role of wildlife in the epidemiology, transmission, and maintenance of infectious diseases of livestock. Successful management or eradication of these diseases will require the development of cross-discipline and institutional collaborations. Despite social and policy challenges, there remain opportunities to develop new collaborations and new technologies to mitigate the risks posed at the livestock-wildlife interface.

Mycobacterium bovis (bovine tuberculosis) infection in North American wildlife: current status and opportunities for mitigation of risks of further infection in wildlife populations

Mycobacterium bovis (M. bovis), the causative agent of bovine tuberculosis, has been identified in nine geographically distinct wildlife populations in North America and Hawaii and is endemic in at least three populations, including members of the Bovidae, Cervidae, and Suidae families. The emergence of M. bovis in North American wildlife poses a serious and growing risk for livestock and human health and for the recreational hunting industry. Experience in many countries, including the USA and Canada, has shown that while M. bovis can be controlled when restricted to livestock species, it is almost impossible to eradicate once it has spread into ecosystems with free-ranging maintenance hosts. Therefore, preventing transmission of M. bovis to wildlife may be the most effective way to mitigate economic and health costs of this bacterial pathogen. Here we review the status of M. bovis infection in wildlife of North America and identify risks for its establishment in uninfected North American wildlife populations where eradication or control would be difficult and costly. We identified four common risk factors associated with establishment of M. bovis in uninfected wildlife populations in North America, (1) commingling of infected cattle with susceptible wildlife, (2) supplemental feeding of wildlife, (3) inadequate surveillance of at-risk wildlife, and (4) unrecognized emergence of alternate wildlife species as successful maintenance hosts. We then propose the use of integrated and adaptive disease management to mitigate these risk factors to prevent establishment of M. bovis in susceptible North American wildlife species.

Impact of regulatory perturbations to disease spread through cattle movements in Great Britain

During the past decade the British livestock industry has suffered from several major pathogen outbreaks, and a variety of regulatory and disease control measures have been applied to the movement of livestock with the express aim of mitigating the spread of infection. The Rapid Analysis and Detection of Animal-related Risks (RADAR) project, which has been collecting data on the movement of cattle since 1998, provides a relatively comprehensive record of how these policies have influenced the movement of cattle between animal holdings, markets, and slaughterhouses in Britain. Many previous studies have focused on the properties of the network that can be derived from these movements – treating farms as nodes and movements as directed (and potentially weighted) edges in the network. However, of far greater importance is how these policy changes have influenced the potential spread of infectious diseases. Here we use a stochastic fully individual-based model of cattle in Britain to assess how the epidemic potential has varied from 2000 to 2009 as the pattern of movements has changed in response to legislation and market forces. Our simulations show that the majority of policy changes lead to significant decreases in the epidemic potential (measured in multiple ways), but that this potential then increases through time as cattle farmers modify their behaviour in response. Our results suggest that the cattle industry is likely to experience boom-bust dynamics, with the actions that farmers take during epidemic-free periods to maximise their profitability likely to increase the potential for large-scale epidemics to occur.

Demographics of cattle movements in the United Kingdom

BACKGROUND

The United Kingdom (UK) government has been recording the births, deaths, and movements of cattle for the last decade. Despite reservations about the accuracy of these data, they represent a large and valuable body of information about the demographics of the UK cattle herd and its contact structure. In this article, a range of demographic data about UK cattle, and particularly their movements, are presented, as well as yearly trends in the patterns of movements.

RESULTS

A clear seasonal pattern is evident in the number of movements of cattle, as are the reductions in movement volume due to foot and mouth disease outbreaks in 2001 and 2007. The distribution of ages of cattle at their time of death is multimodal, and the impact of the over thirty months rule is marked. Most movements occur between agricultural holdings, markets, and slaughterhouses, and there is a non-random pattern to the types of holdings movements occur between. Most animals move only a short distance and a few times in their life. Most movements between any given pair of holdings only occurred once in the last 10 years, but about a third occurred between 2 and 10 times in that period. There is no clear trend to movement patterns in the UK since 2002.

CONCLUSIONS

Despite a substantial number of regulatory interventions during the last decade, movement patterns show no clear trend since 2002. The observed patterns in the repeatability of movements, the types of holdings involved in movements, the distances and frequencies of cattle movements, and the batch sizes involved give an insight into the structure of the UK cattle industry, and could act as the basis for a predictive model of livestock movements in the UK.

Development of the England Wildlife Health Strategy--a framework for decision makers

Diseases in wildlife have been recognised as having the potential to affect human health, livestock health and species conservation. In order to assess and respond to these potential risks in an effective and a proportionate way, the UK Government initiated development of the Wildlife Health Strategy to provide a framework for decision making. The England Wildlife Health Strategy (EWHS) has been developed through extensive consultation. Discussions and negotiations with government departments, agencies, non-governmental public bodies and wildlife organisations were held to obtain advice and input on specific and specialised aspects of wildlife health. A series of workshops to investigate the application of innovative science to wildlife health policy contributed further. A formal public consultation was held that proposed a range of actions to implement the strategy. A summary of responses to this consultation was published in October 2007. The EWHS was published in June 2009 and provides a framework for a generic four-stage approach to wildlife health that can be adopted by decision makers both within and outside government.

Insights from unifying modern approximations to infections on networks

Networks are increasingly central to modern science owing to their ability to conceptualize multiple interacting components of a complex system. As a specific example of this, understanding the implications of contact network structure for the transmission of infectious diseases remains a key issue in epidemiology. Three broad approaches to this problem exist: explicit simulation; derivation of exact results for special networks; and dynamical approximations. This paper focuses on the last of these approaches, and makes two main contributions. Firstly, formal mathematical links are demonstrated between several prima facie unrelated dynamical approximations. And secondly, these links are used to derive two novel dynamical models for network epidemiology, which are compared against explicit stochastic simulation. The success of these new models provides improved understanding about the interaction of network structure and transmission dynamics.

Individual identity and movement networks for disease metapopulations

The theory of networks has had a huge impact in both the physical and life sciences, shaping our understanding of the interaction between multiple elements in complex systems. In particular, networks have been extensively used in predicting the spread of infectious diseases where individuals, or populations of individuals, interact with a limited set of others-defining the network through which the disease can spread. Here for such disease models we consider three assumptions for capturing the network of movements between populations, and focus on two applied problems supported by detailed data from Great Britain: the commuter movement of workers between local areas (wards) and the permanent movement of cattle between farms. For such metapopulation networks, we show that the identity of individuals responsible for making network connections can have a significant impact on the infection dynamics, with clear implications for detailed public health and veterinary applications.

Representing the UK's cattle herd as static and dynamic networks

Network models are increasingly being used to understand the spread of diseases through sparsely connected populations, with particular interest in the impact of animal movements upon the dynamics of infectious diseases. Detailed data collected by the UK government on the movement of cattle may be represented as a network, where animal holdings are nodes, and an edge is drawn between nodes where a movement of animals has occurred. These network representations may vary from a simple static representation, to a more complex, fully dynamic one where daily movements are explicitly captured. Using stochastic disease simulations, a wide range of network representations of the UK cattle herd are compared. We find that the simpler static network representations are often deficient when compared with a fully dynamic representation, and should therefore be used only with caution in epidemiological modelling. In particular, due to temporal structures within the dynamic network, static networks consistently fail to capture the predicted epidemic behaviour associated with dynamic networks even when parameterized to match early growth rates.

Use of laboratory data to reduce the time taken to detect new diseases: VIDA to FarmFile

The analysis of laboratory data can provide information about the health of livestock populations; in Great Britain the Veterinary Investigation Diagnosis Analysis (VIDA) system has provided such data since 1975. However VIDA covers only known diagnoses, with limited epidemiological characterisation. The unexpected outbreak of bse showed that it was necessary to improve surveillance to detect new diseases, and a necessary update of the VIDA database for the millennium date change provided the opportunity. The information required to enhance the value of laboratory data was identified, a new form and database, 'FarmFile', were designed to record it, and they began to be used in 1999. The detection of new diseases depends on making comparisons with the expected or 'usual' levels of unexplained disease. The data are analysed quarterly to assess any changes in the levels of unexplained disease in different species, categorised in terms of clinical sign or body system, by comparison with previous years. No new diseases have been detected either through FarmFile or more traditional means since the new analyses started in earnest in 2004, but they have indicated that an unexplained event was not a new disease of concern, and developments continue to improve the system's sensitivity and specificity.