Projects per year
Mastitis, or intramammary infection (IMI), is one of the most frequent diseases in dairy cattle. In addition to being painful for the affected cow, especially in the case of a clinical mastitis, it also has various other effects on production and herd routines. Mastitis not only reduces the milk yield but also the milk quality. It disrupts the herd routine by leading to increased culling rates. Furthermore, clinical cases have to be treated. The milk loss and the costs for necessary control and intervention lead to considerable economic losses for the dairy farmer. An important element of mastitis management is antimicrobial treatment. In view of rising antimicrobial resistance, the use of antibiotics in production animals has garnered the concern of consumers and politicians. Mastitis prevention and control strategies should therefore be multifaceted and only rely on antibiotics when necessary. The overall objective of this PhD project was to identify such multifaceted and cost-effective intervention strategies. The project itself was divided into two parts. The first part of this PhD project focused on data analysis. Register data from the Danish Cattle Database were analysed by herd-wise logistic regressions for determinants for antimicrobial treatment in relation to udder health. Principal component analysis and clustering were performed on the regression coefficients to group herds according to their treatment patterns. Lactational treatments and dry cow treatments were considered separately throughout the whole data analysis. The results showed that in both cases, herds grouped according to the most prominent determinants. Treatment was determined by milk production, age, or diagnostics for dry cow treatments. For lactational treatments, the determinants were milk production, age and diagnostics, or whether or not a cow was subsequently culled. In the second part of the PhD project, a strain-, cow-, and herd-specific bio-economic simulation model of intramammary infections was developed and used to investigate and compare different mastitis intervention strategies. The model incorporates a previously existing model of a Danish dairy herd (iCull). It additionally simulates the spread of several mastitis pathogens within the herd, the effects of mastitis, and intervention measures for clinical and subclinical cases. The developed model simulates a Danish dairy herd with several mastitis pathogens, and the transmission framework is strainand cow-specific: it specifically allows simulating different strains of the same pathogen species, and it considers cow-specifics for infection and cure. However, careful calibration to specific herd conditions is paramount as the model is sensitive to changes in the transmission parameters. The modelled interventions included antibiotic treatment and cow-specific reactive culling of infected animals for both clinical and subclinical cases. Some intervention measures also partly incorporate the findings of the first part of the project. The investigated intervention strategies were divided into strategies against clinical mastitis and strategies against both clinical and subclinical mastitis. The most effective strategy against clinical intramammary infections was a “good hygiene”, represented by a low transmission rate. However, specifics about the necessary measures to achieve “good hygiene” and the costs associated with implementing such measures are unknown. Cost-effectiveness, on the other hand, could be improved by using more antibiotic treatments or by culling. More specifically, a comparison of different intervention strategies showed that cow-specific treatment or culling decisions for clinical cases was most cost-effective. For these intervention strategies, the number of antibiotic treatment days was reduced at the cost of an increased number of culled cows. When the intervention strategies against clinical mastitis were supplemented by cow-specific treatment or culling of subclinical cases, cost-efficiency could be further increased. Subclinical cases were identified by two subsequent high somatic cell counts (>200 000 cells=ml) and diagnostic testing for confirmation. Depending on the main causative pathogen and among the investigated intervention strategies, the choice of the clinical intervention measure varied. For Staphylococcus aureus, the choice of the intervention measure against clinical cases affected costeffectiveness (more cost-effective interventions before addition of measures against subclinical cases stayed more cost-effective after addition of such a measure). For Streptococcus agalactiae, which primarily causes subclinical mastitis, the intervention measure against clinical cases was less relevant. The preferred intervention strategy therefore depends on the herd. It may also vary depending on the farmer’s preferences regarding management measures such as treatment or culling. Intervention strategies against mastitis should therefore be herdspecific. The limitations of a modelling approach, as it was taken in this thesis, lie in the proper understanding of the transmission dynamics and its parameterisation. If parameter estimates are missing, for example in the case of hygienic measures, the respective aspects cannot be properly investigated. Factors that could not be included in the model, because of missing parameter values or because they were unknown, may change the outcome in a real life situation. Therefore, the model results should be seen as recommendations for possible cost-effective intervention strategies against mastitis until, ideally, they can be validated by field studies. In conclusion, the model presented in this thesis can be used as a decision support tool in scientific research: it can identify cost-effective intervention strategies against mastitis, while also taking into account other related factors (e.g., antibiotic treatment and culling). These findings may then be considered in the future when planning new mastitis management strategies.
|Place of Publication||Kgs. Lyngby|
|Number of pages||201|
|Publication status||Published - 2018|
Gussmann, M. K., Hisham Beshara Halasa, T., Toft, N., Boklund, A., Denwood, M., Rajala-Schultz, P. J. & Nielsen, S. S.
01/07/2015 → 30/09/2018