Optimising decision making in mastitis control

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

Optimising decision making in mastitis control

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

Factors affecting the cost-effectiveness of on-farm culture prior to the treatment of clinical mastitis in dairy cows

The objective of this study was to use probabilistic sensitivity analysis to evaluate the cost-effectiveness of using an on-farm culture (OFC) approach to the treatment of clinical mastitis in dairy cows and compare this to a ‘standard’ treatment approach. A specific aim was to identify the herd circumstances under which an OFC approach would be most likely to be cost-effective. A stochastic Monte Carlo model was developed to simulate 5000 cases of clinical mastitis at the cow level and to calculate the associated costs simultaneously when treated according to 2 different treatment protocols; i) a 'conventional' approach (3 tubes of intramammary antibiotic) and ii) an OFC programme, whereby cows are treated according to the results of OFC. Model parameters were taken from recent peer reviewed literature on the use of OFC prior to treatment of clinical mastitis. Spearman rank correlation coefficients were used to evaluate the relationships between model input values and the estimated difference in cost between the standard and OFC treatment protocols. The simulation analyses revealed that both the difference in the bacteriological cure rate due to a delay in treatment when using OFC and the proportion of Gram-positive cases that occur on a dairy unit would have a fundamental impact on whether OFC would be cost-effective. The results of this study illustrated that an OFC approach for the treatment of clinical mastitis would probably not be cost-effective in many circumstances, in particular, not those in which Gram-positive pathogens were responsible for more than 20% of all clinical cases. The results highlight an ethical dilemma surrounding reduced use of antimicrobials for clinical mastitis since it may be associated with financial losses and poorer cow welfare in many instances

A Bayesian micro-simulation to evaluate the cost-effectiveness of interventions for mastitis control during the dry period in UK dairy herds

Importance of the dry period with respect to mastitis control is now well established although the precise interventions that reduce the risk of acquiring intramammary infections during this time are not clearly understood. There are very few intervention studies that have measured the clinical efficacy of specific mastitis interventions within a cost-effectiveness framework so there remains a large degree of uncertainty about the impact of a specific intervention and its costeffectiveness. The aim of this study was to use a Bayesian framework to investigate the cost-effectiveness of mastitis controls during the dry period. Data were assimilated from 77 UK dairy farms that participated in a British national mastitis control programme during 2009–2012 in which the majority of intramammary infections were acquired during the dry period. The data consisted of clinical mastitis (CM) and somatic cell count (SCC) records, herd management practices and details of interventions that were implemented by the farmer as part of the control plan. The outcomes used to measure the effectiveness of the interventions were i) changes in the incidence rate of clinical mastitis during the first 30 days after calving and ii) the rate at which cows gained new infections during the dry period (measured by SCC changes across the dry period from 200,000 cells/ml). A Bayesian one-step microsimulation model was constructed such that posterior predictions from the model incorporated uncertainty in all parameters. The incremental net benefit was calculated across 10,000 Markov chain Monte Carlo iterations, to estimate the cost-benefit (and associated uncertainty) of each mastitis intervention. Interventions identified as being cost-effective in most circumstances included selecting dry-cow therapy at the cow level, dry-cow rations formulated by a qualified nutritionist, use of individual calving pens, first milking cows within 24 h of calving and spreading bedding evenly in dry-cow yards. The results of this study highlighted the efficacy of specific mastitis interventions in UK conditions which, when incorporated into a costeffectiveness framework, can be used to optimize decision making in mastitis control. This intervention study provides an example of how an intuitive and clinically useful Bayesian approach can be used to form the basis of an on-farm decision support tool

Increased rejection of murine allogeneic bone marrow in presensitized recipients

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Rate of transmission: a major determinant of the cost of clinical mastitis

The aim of this research was to use probabilistic sensitivity analysis to evaluate the relative importance of different components of a model designed to estimate the cost of clinical mastitis (CM). A particular focus was placed on the importance of pathogen transmission relative to other factors, such as milk price or treatment costs. A stochastic Monte Carlo model was developed to simulate a case of CM at the cow level and to calculate the associated costs for 5 defined treatment protocols. The 5 treatment protocols modeled were 3 d of antibiotic intramammary treatment, 5 d of antibiotic intramammary treatment, 3 d of intramammary and systemic antibiotic treatment, 3 d of intramammary and systemic antibiotic treatment plus 1 d of nonsteroidal antiinflammatory drug treatment, and 5 d of intramammary and systemic antibiotic treatment. Uniform distributions were used throughout the model to enable investigation of the cost of CM over a spectrum of clinically realistic scenarios without specifying which scenario was more or less likely. A risk of transmission parameter distribution, based on literature values, was included to model the effect of pathogen transmission to uninfected cows, from cows that remained subclinically infected after treatment for CM. Spearman rank correlation coefficients were used to evaluate the relationships between model input values and the estimated cost of CM. Linear regression models were used to explore the effect that changes to specific independent variables had on the cost of CM. Risk of transmission was found to have the strongest association with the cost of CM, followed by bacteriological cure rate, cost of culling, and yield loss. Other factors such as milk price, cost of labor, and cost of medicines were of minimal influence in comparison. The cost of CM was similar for all 5 treatment protocols. The results from this study suggest that, when seeking to minimize the economic impact of CM in dairy herds, great emphasis should be placed on the reduction of pathogen transmission from cows with CM to uninfected cows