Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds.

Assessing the economic importance of traits is crucial for delivering appropriate breeding goals in dairy cattle breeding. The aim of the present study was to calculate economic values (EV) and assign the importance of health traits for three dairy cattle breeds: Lithuanian Black-and-White open population (LBW), Lithuanian Red open population (LR) and Lithuanian Red old genotype (LROG). The EV estimation was carried out using a stochastic bio-economic model SimHerd, which allows the simulation of the expected monetary gain of dairy herds. The simulation model was calibrated for LBW, LR and LROG breeds, taking into account breed-specific phenotypic and economic data. For each trait, two scenarios were simulated with a respective trait at different phenotypic levels. To obtain the EVs, the scenarios were compared with each other in terms of their economic outcomes. In order to avoid the double counting of the effects, the output results were corrected using a multiple regression analysis with mediator variables. The EVs were derived for the traits related to production ECM (energy-corrected milk), fertility, calving traits, calf survival, cow survival and direct health. To demonstrate the importance of health traits in herd management, we provided reliable EVs estimates for functional traits related to herd health. The highest EV for direct health traits, caused by an increase in of 1 percentage point, were those found for mastitis (EUR 1.73 to EUR 1.82 per cow-year) and lameness (EUR 1.07 to EUR 1.27 per cow-year). The total costs per case of ketosis, milk fever and metritis ranged from EUR 1.01 to EUR 1.30, EUR 1.14 to EUR 1.26 and EUR 0.95 to EUR 1.0, respectively. The highest economic values of dystocia were estimated for LROG (EUR -1.32), slightly lower for LBW (EUR -1.31) and LR (EUR -1.23). The results of this study show the importance of health traits to the economic features of cattle herd selection of new breeding goal and this would improve the herd health. The economic evaluation of the functional traits analyzed in this study indicated the significant economic importance of the functional traits in Lithuanian dairy cattle breeds.

Economic value of information from an alert system on physiological imbalance in fresh cows.

Physiological imbalance is an abnormal physiological condition that cannot be directly observed but is assumed to precede subclinical and clinical diseases in the beginning of lactation. Alert systems to detect the physiological imbalance in a cow using Fourier transform mid-infrared spectroscopy in milk have been developed. The objective of this study was to estimate the value of information provided from such system with different indicator accuracies, herd prevalence and prices. A decision tree was created to model the probabilities of detection and associated costs of test outcome, intervention and occurrence of disease. We assumed that the negative effect of physiological imbalance was the development of subclinical ketosis and that this negative effect was prevented by drenching the cows with propylene glycol for 5 days. We simulated the economic impact of subclinical ketosis mediated through physiological imbalance to be $194 per case. The results showed that if the alert system was highly accurate (Se = 0.99/Sp = 0.99), and the prevalence of physiological imbalance was 30 %, the value of information provided from the system is $19 per cow-year. In case the prevalence is 5 % or 50 %, the value of information is $3 and $13, respectively. These estimates for the value do not cover the capital costs and operational costs of the alert system. This study furthermore clearly demonstrated that in order to estimate the value of information correctly, it is important to consider that drenching all cows and not drenching any of the cows are the two relevant alternative options in the absence of the alert system. In conclusion, the decision tree and sensitivity analysis developed in this study show that final economic results are highly variable to the prevalence of physiological imbalance and highest at an intermediate prevalence. Other relevant factors are the costs associated with drenching and the cost associated with treating false positives and not treating false negatives. In addition, this study highlights the benefits of simulation to pinpoint where additional information is needed to further quantify the economic value and required accuracy of an indication-based intervention system.

Economic figures in herd health programmes as motivation factors for farmers.

Veterinarians often express frustrations when farmers do not implement their advice, and farmers sometimes shake their heads when they receive veterinary advice which is practically unfeasible. This is the background for the development of a focused 3 page economic report created in cooperation between veterinarians, farmers, advisers and researchers. Based on herd specific key-figures for management, the report presents the short- and long-term economic effects of changes in 15 management areas. Simulations are performed by the dairy herd simulation model "SimHerd". The aim is to assist the veterinarian in identifying the economically most favorable and feasible management improvements and thereby provide more relevant and prioritised advice to the farmer. In the developing process, a prototype of the advisory tool was tested by 15 veterinarians on 55 farms. After the test period, a selection of farmers were asked to take part in a qualitative evaluation questioning them whether they had implemented the action plans suggested on basis of the advisory tool and making them explain what made them agree or disagree on the results from this new advisory tool. The aim of this process was to evaluate the farmers' receptiveness to advice based on these economic analyses. We found that the analysed advisory tool (the report) can be seen as a valuable help and support for some farmers when deciding whether to implement the action plans. However, certain reservations were recognised. The trustworthiness of the tool depends on whether the veterinarians are able to suggest to the farmer which specific management changes are needed to obtain the estimated effects and what the related expenses might be (costs). Without transparency of expenses, time-limits, work hours and so on, farmers may not be convinced by the tool.

Estimation of probability for the presence of claw and digital skin diseases by combining cow- and herd-level information using a Bayesian network.

Cross sectional data on the prevalence of claw and (inter) digital skin diseases on 4854 Holstein Friesian cows in 50 Danish dairy herds was used in a Bayesian network to create herd specific probability distributions for the presence of lameness causing diseases. Parity and lactation stage are identified as risk factors on cow level, for the prevalence of the three lameness causing diseases digital dermatitits, other infectious diseases and claw horn diseases. Four herd level risk factors have been identified; herd size, the use of footbaths, a grazing strategy and total mixed ration. Besides, the data has been used to estimate the random effect of herd on disease prevalence and to find conditional probabilities of cows being lame, given the presence of the three diseases. By considering the 50 herds representative for the Danish population, the estimates for risk factors, conditional probabilities and random herd effects are used to formulate cow-level probability distributions of disease presence in a specific Danish dairy herd. By step-wise inclusion of information on cow- and herd-level risk factors, lameness prevalence and clinical diagnosis of diseases on cows in the herd, the Bayesian network systematically adjusts the probability distributions for disease presence in the specific herd. Information on population-, herd- and cow-level is combined and the uncertainty in inference on disease probability is quantified.

The association of hoof lesions at claw trimming with test-day milk yield in Danish Holsteins.

In a cross-sectional study, performed between October 2002 and April 2003 on 55 Danish dairy herds with 6161 predominantly Holstein Friesian cows the prevalence of 9 hoof lesions was determined. All test-day yields (TDY) of kg energy corrected milk (ECM) in the lactation of diagnosis were recorded. For the purpose of including hoof lesions in a decision support model an attempt was made to aggregate the lesions into digital dermatitis (DD), other interdigital diseases (OID, infectious diseases other than DD) and hoof horn diseases (HHD, related to metabolic disorders and trauma). A division was made based on the stage of lactation in which the lesions were diagnosed; during the first 100 days in milk, between days 101 and 200 and between days 201 and 305. Associations between the presence of hoof lesions at trimming and milk production were analyzed by linear mixed modeling at the cow level, clustered within herd. The data of primiparous cows was analyzed separately from the multiparous cows. Based on the associations between TDY and the individual lesions aggregated into HHD, this aggregation as initially planned could not be justified and was therefore not maintained. For OID the value of early diagnosis was apparent; an early diagnosis and early treatment (<101 DIM) was associated with either a positive value or a value less negative compared to a diagnosis and treatment in late lactation (201-305 DIM). This pattern was not as clearly present for the other lesions.