The importance of understanding end user acceptability of new technology to support animal health management

This pilot study investigates the acceptability of a mobile application (app) developed to assist livestock producers make better animal health decisions with the support of a local veterinarian. With the increase in new technologies available for producers, acceptability evaluation is important to ensure that technology is designed considering end users' needs. An acceptability qualitative study, using semi-structured interviews, was designed including a purposive selection of sheep producers and livestock veterinarians. Eleven producers and six veterinarians participated in the study. Results suggest that producers would use such a tool to contact private veterinarians in non-emergency situations to obtain animal health advice. From veterinarians' perspective, while features of the app, such as messaging and notifications, were considered useful, concerns were raised about its capacity to enhance business opportunities and potential privacy implications. This study highlights the importance of engaging with end users in the early stages of the design and the introduction of new technology to maximise potential for adoption.

Assessing the delay to detection and the size of the outbreak at the time of detection of incursions of foot and mouth disease in Australia

The time delay to detection of an outbreak of an emergency animal disease directly affects the size of the outbreak at detection and the likelihood that the disease can be eradicated. This time delay is a direct function of the efficacy of the surveillance system in the country involved. Australia has recently completed a comprehensive review of its general surveillance system examining regional variation in both the behaviour of modelled outbreaks of foot and mouth disease and the likelihood that each outbreak will be detected and reported to government veterinary services. The size of the outbreak and the time delay from introduction to the point where 95% confidence of detection was reached showed significant (p < 0.05) regional variation with the more remote northern areas experiencing smaller outbreaks that are less likely to spread and less likely to be reported to government services than outbreaks in the more developed southern areas of Australia. Outbreaks in the more densely populated areas may take up to 43 days until a 95% confidence of detection is achieved and at that time, the outbreak may involve up to 53 farms.