Decision Support Systems in Animal Health

Abstract

The safety of food derived from animals has received significant public media attention in recent times and it is likely that this trend will continue in the short to medium term future. Examples of diseases in humans arising from the consumption of animals or animal products at the centre of recent food safety scares include variant Creutzfeld-Jakob disease (Anonymous, 2000), Salmonella Typhimurium DT104 (Threlfall et al., 1994), Salmonella Enteritidis (Anderson, 1996) and Escherichia coli O157 (Rangel et al., 2005). Of additional concern to the general public are infectious diseases of livestock, particularly those that have required large numbers of animals to be pre-emptively slaughtered or culled as part of control and eradication measures. Since 2000 there have been a number of large outbreaks of infectious disease in farmed animal populations that have been managed using pre-emptive slaughter or culling. This approach to disease management has raised questions about the legitimacy, ethics and long term future of intensive farming practices. Examples include the outbreak of classical swine fever (CSF) in TheNetherlands in 2000 and foot-and-mouth disease (FMD) in the United Kingdom in 2001. Infectious disease has impacted heavily on the health and productivity of livestock populations in Southeast Asian countries in recent times. Highly pathogenic avian influenza (HPAI) H5N1 has emerged as a disease of international concern not only because of its ability to cause illness and death in poultry and humans, but also by its capacity to disrupt poultry trade and to threaten food security in resource-poor countries. To deal with infectious disease outbreaks in domestic livestock populations quickly and efficiently it is essential that animal health authorities have access to appropriate information to guide decisionmaking. Animal health information includes (but should not be restricted to) details of the population at risk and details of incident cases of disease conditions of interest. This information allows the distribution of disease to be described in terms of the established epidemiological triad of individual, place and time. Individual animal-level analyses include estimates of the number of cases per head of population and for various subsections of the population (e.g. animals of a given age, sex, breed or type). Spatial analyses provide insight into geographical factors influencing the distribution of disease (e.g. proximity to pollutants, farming practices characteristic of a given area). Temporal analyses provide insight into short and long term variations in disease frequency. All three categories of analysis are useful in that firstly they provide an objectively measured point of comparison once control measures have been implemented and secondly, they provide information that can be used for hypothesis generation about factors associated with, or causing disease. Collection of additional information about the environment in which animals are located and events they 16