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Balancing antibiotic treatment with regard to mastitis

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These are the sildes of a presentation I gave at the NMC Annual Meeting, held in Fort Worth Texas on January 27, 2014. I was asked to tell something on the economics of mastitis treatment. I broadened …

These are the sildes of a presentation I gave at the NMC Annual Meeting, held in Fort Worth Texas on January 27, 2014. I was asked to tell something on the economics of mastitis treatment. I broadened that to balancing. Economics is about optimization, but nowadays in antibiotic treatment in animals factors such as animal welfare and a reduction in the use of antibiotics play also a role. The farmer and the veterinary advisor have to balance this. The presentation aims at setting up spreadsheet to support decision making

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  • 1. Treating mastitis: Balancing cure, money, welfare and resistance Henk Hogeveen With input from Wilma Steeneveld and Claudia Kamphuis
  • 2. My paper gives latest results from literature But ...session on analytics: The modern dairy farm has at its fingertips an endless array of data. When managed properly, these data can be used to create a competitive advantage. This session will explore the potential of analytical approaches to managing mastitis through the use of on-farm records, decision support for mastitis treatment, and statistical processing of information. My presentation will have an emphasis on analytics, not on results
  • 3. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 4. Important in treatment decisions  Cure  Much knowledge available  Keywords “Cure rate” and “mastitis”  11 scientific papers in 2013
  • 5. There is more than cure rates: Welfare  Clinical mastitis gives pain (e.g., Kemp et al. 2008 VetRec)  Behaviour is also affected (Medrano-Galarza et al., 2012 JDairySci)  So: Better cure is better welfare
  • 6. Antibiotic resistance  Heavily in discussion  Resistance of mastitis pathogens ● Self-interest ● No increase seen (Hogan, IDF-factsheet)  Antibiotic resistance in humans ● Externality ● Dairy cattle has very minor contribution ● In the Netherlands (self) regulations (Oliver et al., 2011)
  • 7. Economics  A farm is a business  Self interest  Costs of antibiotics vs benefits of higher cure rates or better prevention
  • 8. Difficult task of herd manager  There is: ● Cure rate (welfare) ● Money ● Antibiotic resistance  Should be balanced
  • 9. Not much knowledge on balancing  11 scientific papers in 2013  One with economics (related to transmission); Down et al., JDairySci
  • 10. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 11. Lactational treatment  Much knowledge available on cure, e.g., reviews ● Barkema et al. 2006 JDairySci ● Roberson, 2012 VetClinFoodAnim ● Roy and Keefe, 2012 VetClinFoodAnim ● Suojala et al. 2013 JVetPharmTherap  Some papers on economics ● Steeneveld et al., 2011 JDairySci ● Halasa et al., 2012 JDairySci ● Down et al., 2013 JDairySci  These are averages  Make your own calculations
  • 12. Straightforward spreadsheet Two scenarios
  • 13. Straightforward spreadsheet Cure rates (input)
  • 14. Straightforward spreadsheet Calculation of proportion of cured cows
  • 15. Straightforward spreadsheet What if animals do not cure? We have not really thought that out very well Farm specific Role of advisor
  • 16. Let’s add economics Proportion of proportion
  • 17. Let’s add economics But we are missing input
  • 18. Let’s add economics That depends on cure and lactation stage
  • 19. Let’s add economics Formula for the average nr of days We are missing some price levels
  • 20. Let’s add economics Let’s make final calculations
  • 21. Let’s add economics
  • 22. And finally, what are the costs?
  • 23. What’s the point  Specific situation -> no papers available  Creation of a tool is not too difficult  Input needed ● Price levels – farmers know these ● Specific situation of the cow – farmers know these ● Cure rates – this is a problem  Cure rates might be available from farm records ● Large farms ● Available data  Evaluate previous assumptions
  • 24. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 25. Treatment of clinical mastitis  Causal pathogen ● Streptococci (40%), S. aureus (30%), E. coli (30%)  Parity  Day in milk  Calving interval  Most recent SCC-value  Repeated CM case yes/no  Systematically ill yes/no  305-day milk production All stochastic ● Wood curve to determine daily milk production at moment CM and remaining milk production during lactation Steeneveld et al., 2011, JDairySci
  • 26. Defined treatments  3-day intramammary antibiotic treatment (IMM3)  5-day intramammary antibiotic treatment (IMM5)  3-day intramammary antibiotic treatment + systemic antibiotic treatment (IMM3_S)  5-day intramammary antibiotic treatment + systemic antibiotic treatment (IMM5_S)  Immediately culling
  • 27. Simulating follow-up of treatment Treatment CM1 No bact. cure, clin. cure Bact. + clin. cure End lactation No bact. cure, no clin. cure Culling No bact. cure, clin. cure Culling End lactation Treatment CM2 Extended treatment Bact. + clin. cure End lactation Culling No bact. cure, no clin. cure Dying End lactation etc. Dry-off quarter Culling
  • 28. Cow-specific cure  Probability of bacteriological cure (%) defined ● for heifers, SCC<200, <60 DIM, no CM before, not systematically ill IMM3 Streptococci S. aureus E. coli IMM5 IMM3_S IMM5_S 70 40 80 80 60 85 80 60 85 90 70 95 Defined effects of cow factors • Older cow: 10% • SCC 200-500: 10% • SCC >500: 20% • >60 DIM: • Repeated case: • Systematically ill: 10% 20% 20%
  • 29. Average costs ($US) IMM3 IMM5 IMM3_S IMM5_S Culling Overall 245 270 275 295 766 Daily milk production (kg) <20 20-25 25-30 30-35 35-40 >40 158 189 200 216 253 307 174 206 223 238 279 326 192 216 230 244 284 332 207 230 255 266 301 351 478 578 569 577 732 1,026 Causal pathogen Streptococci S. aureus E. coli 216 283 253 238 296 284 238 296 284 266 318 310 758 749 789 Original calculations in €; € 1 = $US 1.37
  • 30. Least cost frontiers High cure cow E. coli cow Average cow S. aureus cow Low cure cow 100 IMM3 IMM5 IMM3_S IMM3_N_S IMM5_S 90 Probability of cure (%) 80 70 60 50 40 30 20 130 150 170 190 210 Total costs (€) 230 250 270 290
  • 31. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 32. The ongoing debate on dry-cow therapy  Dry-cow therapy has two uses ● Curative ● Preventive  “We” do not want preventive use of antibiotics (anymore)  Which cows to dry-off with antibiotics?  Let’s create another spreadsheet ● Basically the same as the previous one
  • 33. Probabilities depend on risk group Very basic input Costs with and without DCT Probabilities from: Scherpenzeel et al., 2014, in preparation
  • 34. Average costs drying-off per cow Costs per cow
  • 35. We’re also interested in amount of AB Daily doses Totals
  • 36. Let’s optimize (linear programming)
  • 37. Minimize total costs of mastitis By the numbers of treated cows Under constraints: - Nr of cows equal - Less AB than threshold
  • 38. The constraint
  • 39. What’s the point  Literature never fits the individual farmer’s situation  Probabilities can be based on farmers on data  Quite straightforward economic modelling  Evaluate previous assumptions
  • 40. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 41. Automatic milking  On-line mastitis monitoring (Electrical conductivity, colour, SCC)  Great possibilities for therapy evaluation  But ….. Sensitivity & specificity of mastitis detection  Farmer’s confirmation is needed ● Time consuming ● Mostly negative ● Not the nicest of work  3.5 % of alerts are checked
  • 42. Study on farmer’s handing of alerts  7 farmers, student checked all alerts ● 60 % of alerts false positive ● 3.5 % of alerts is checked by farmers ● checked alerts are often clinical cases ● 74 % of clinical cases is missed  How bad is this?
  • 43. Options 1. Maintain the “old” paradigm of treating clinical mastitis cases hold in automatic milking ….. and educate our farmers better to check ….. or have better sensors (less false positives) 2. Use the daily sensor measurements differently -> detect acute severe mastitis, for mild mastitis look at chronicity, use on-farm culturing before treatment  Lot’s of questions, no answers (yet)
  • 44. My presentation  Balancing treatments  Analytics of lactational treatment  Example of published results  Analytics of dry-cow therapy (optimization)  New possibilities with automatic milking  Concluding remarks
  • 45. I did not present all knowledge  There is more knowledge out there  Mostly economics  Welfare ≈ cure rate  On-farm culture systems ● Lago et al., 2011, JDairySci ● Cameron et al., 2013, PrevVetMed ● Pinzón-Sánchez et al., 2011 JDairySci (Economics)  Use of antibiotics only through dry cow therapy
  • 46. On-farm analyses  Use straightforward calculation tools  Use farm-specific input ● Price levels ● Incidences ● Cure rates  Use those farm data!!!  Operational use should be automated  There is a future for tailor-made treatment decisions  PS Example models and ppt are available
  • 47. Thank you for your attention @henkhogeveen animal-health-management.blogspot.com On-line courses on Veterinary Economics on: www.elevatehealth.eu