Optimising decision making in mastitis control

Abstract

Mastitis remains one of the most common diseases of dairy cows and represents a large economic loss to the industry as well as a considerable welfare issue to the cows affected. Decisions are routinely made about the treatment and control of mastitis despite evidence being sparse regarding the likely consequences in terms of clinical efficacy and return on investment. The aim of this thesis was to enhance decision making around the treatment and prevention of mastitis using probabilistic methods. In Chapter 2 and Chapter 3, decision making around the treatment of clinical mastitis was explored using probabilistic sensitivity analysis. The results from Chapter 2 identified transmission to be the most influential parameter affecting the cost of clinical mastitis at cow level and, therefore, highlighted how important the prevention of transmission was in order to minimise losses associated with clinical mastitis. The cost-effectiveness of an on-farm culture (OFC) approach to the treatment of clinical mastitis was explored in Chapter 3, and compared with the cost-effectiveness of a ‘standard’ approach commonly used in the UK. The results of this study identified that the OFC approach could be cost-effective in some circumstances but this was highly dependent on the proportion of Gram-negative infections and the reduction in bacteriological cure rate that may occur as a result of the delay before treatment. Therefore, in the UK, this approach is unlikely to be cost beneficial in the majority of dairy herds. In Chapters 4, 5 and 6, decision making around the control of mastitis was explored utilising data from UK dairy herds that had participated in a nationwide mastitis control plan. In Chapter 4, mastitis control interventions were identified that were not currently practised by a large proportion of herds, and the frequency at which they were made a priority by the plan deliverers was also reported. In Chapter 5 and Chapter 6, the cost-effectiveness of specific mastitis control interventions was explored within an integrated Bayesian cost-effectiveness framework from herds with a predominance of environmental intramammary infections. Results from the Bayesian microsimulations identified that a variety of interventions would be cost effective in different farm circumstances. The cost-effectiveness of different interventions has been incorporated in a decision support tool to assist optimal decision making by veterinary practitioners in the field