1 Mycoplasm a net Mycoplasm a net Building the m odel: Bayesian - PDF document

Overview Mycoplasm a net Bayesian netw ork - Background A case exam ple - The model - Consequences of Mycoplasma - Effect of control strategies Advanced Herd Management GRO net October 3rd 2006 Tina Birk Jensen Tina Birk Jensen 1 Tina Birk Jensen 2 Mycoplasm a net Mycoplasm a net Purpose Part of the CEPROS project on Animal Health Economics To develop a tool for evaluating the economic consequences of different control strategies against Developed by Lars Otto, FØI Mycoplasma The decisions are often based on intuition from farmers, advisors and vets Tina Birk Jensen 3 Tina Birk Jensen 4 Mycoplasm a hyopneum onia Mycoplasm a net Causes enzootic pneumonia in finishers The model supports decisions but do not take them Important in the intensive pig production Bayesian network Can exist latent in the herd The parameters in the model are based on: Outbreak: 50-70 percent of the finishers have lung lesions - Literature studies - Expert opinions A well documented disease Tina Birk Jensen 5 Tina Birk Jensen 6 1

Mycoplasm a net Mycoplasm a net Building the m odel: Bayesian net Static model for a single pig herd Biological m odel : Stochastic and probabilistic model - Based on biological knowledge Make use of Bayes formula for probalistic interference Econom ic m odel : - Economic risk due to the biological variation A B A A ( ) ( ) ( ) ( ) | ( ) P B A P A | ( ) P A B P B = i i = i i | | P A B P B A ( ) ( ) i i P B P A Tina Birk Jensen 7 Tina Birk Jensen 8 Risk factors Risk factors Control stragegy Disease level Diagnostics Disease level Productivity Productivity Economics Economics Constibution margin Constibution margin Tina Birk Jensen 9 Tina Birk Jensen 10 Mycoplasm a net Mycoplasm a net I nput I nput Risk factors: Diagnostics: -Herd size - Clinical examination -Production type - Serology examination -Purchase policy - Postmortem examination -Season -Region Determines the disease level with more precision Tina Birk Jensen 11 Tina Birk Jensen 12 2

Mycoplasm a net Mycoplasm a net I nput Output: Control strategy: Probability distribution: (Any action with the aim to change the level of disease) - Disease level Short term strategy: Medication - Production outcome Vaccination - Economical outcome Long term strategy: Change in mangement Buildings Tina Birk Jensen 13 Tina Birk Jensen 14 The states of the input variables Label Text Risk factors Herd size States: 1-1000 / 1001-3000 / 3001-5000 / 5001- All in all out States: Yes / no Seson States: Sept. / Dec. / Mar. / Jun. Diagnostics Clinical examination States: Zero / low / middle / high Serologic examination States: Zero / low / middle / high Postmortem examination States: 0-1% / 1-10% / 10-20% / 20%- Productivity outcome Change in daily weight gain States: 0g / -30g / -60g / -90g Change in feed conversion rate States: 0 / 0-0.15 / 0.15-0.30 / 0.30-0.45 Change in mortality States: 0% / ½% / 1% / 1½% Tina Birk Jensen 15 Tina Birk Jensen 16 Different scenarios High-risk herd: Large herd size Continous production Buying piglets from many other herds Low-risk herd: Small herd size Managing all in all out production Not buying piglets from other herds Tina Birk Jensen 17 Tina Birk Jensen 18 3

The econom ic part Change in productivity Calculation: Contribution margin = TR – VC TR: The income from the slaughterhouse P 0 = P pot + ∆ P 0 VC: Weaner price P 1 = P pot + ∆ P 1 Cost of feed P 1 - P 0 = (P pot + ∆ P 1 ) – (P pot + ∆ P 0 ) Dead pigs Labor cost Control strategy P 1 - P 0 = ∆ P 1 - ∆ P 0 Diagnosis Tina Birk Jensen 19 Tina Birk Jensen 20 Economic loss due to Mycoplasma: Economic loss due to Mycoplasma: Low-risk herd High-risk herd Tina Birk Jensen 21 Tina Birk Jensen 22 Effect of m edication Effect of vaccination Tina Birk Jensen 23 Tina Birk Jensen 24 4

Perspectives: Mycoplasm a net Not all needed information can be found in the literature Describes the steady state between risk factors and the severity of Mycoplasma Often it does not pays off to control just one disease It is important to consider several diseases and their interactions Tina Birk Jensen 25 Tina Birk Jensen 26 GRO net Grise, risiko og økonom i Further development of the Mycoplasma-net Considers tw o disease com plexes: • Gastro-intestinal disorders • Air-way disease Tina Birk Jensen 27 Tina Birk Jensen 28 Perspectives: GRO net Not all information to the model can be found in the literature A challenge to estimate the effect of more than one disease The model will be able to estimate long term control strategies Need to test the model in ”real” herds Tina Birk Jensen 29 Tina Birk Jensen 30 5