Cow-specific treatment of clinical mastitis: An economic approach
Bibliographic record
Abstract
Under Dutch circumstances, most clinical mastitis (CM) cases of cows on dairy farms are treated with a standard intramammary antimicrobial treatment. Several antimicrobial treatments are available for CM, differing in antimicrobial compound, route of application, duration, and cost. Because cow factors (e.g., parity, stage of lactation, and somatic cell count history) and the causal pathogen influence the probability of cure, cow-specific treatment of CM is often recommended. The objective of this study was to determine if cow-specific treatment of CM is economically beneficial. Using a stochastic Monte Carlo simulation model, 20,000 CM cases were simulated. These CM cases were caused by Streptococcus uberis and Streptococcus dysgalactiae (40%), Staphylococcus aureus (30%), or Escherichia coli (30%). For each simulated CM case, the consequences of using different antimicrobial treatment regimens (standard 3-d intramammary, extended 5-d intramammary, combination 3-d intramammary+systemic, combination 3-d intramammary+systemic+1-d nonsteroidal antiinflammatory drugs, and combination extended 5-d intramammary+systemic) were simulated simultaneously. Finally, total costs of the 5 antimicrobial treatment regimens were compared. Some inputs for the model were based on literature information and assumptions made by the authors were used if no information was available. Bacteriological cure for each individual cow depended on the antimicrobial treatment regimen, the causal pathogen, and the cow factors parity, stage of lactation, somatic cell count history, CM history, and whether the cow was systemically ill. Total costs for each case depended on treatment costs for the initial CM case (including costs for antibiotics, milk withdrawal, and labor), treatment costs for follow-up CM cases, costs for milk production losses, and costs for culling. Average total costs for CM using the 5 treatments were (US) $224, $247, $253, $260, and $275, respectively. Average probabilities of bacteriological cure for the 5 treatments were 0.53, 0.65, 0.65, 0.68, and 0.75, respectively. For all different simulated CM cases, the standard 3-d intramammary antimicrobial treatment had the lowest total costs. The benefits of lower costs for milk production losses and culling for cases treated with the intensive treatments did not outweigh the higher treatment costs. The stochastic model was developed using information from the literature and assumptions made by the authors. Using these information sources resulted in a difference in effectiveness of different antimicrobial treatments for CM. Based on our assumptions, cow-specific treatment of CM was not economically beneficial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".