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Background
Leg disorders in finishers: An economical problem for farmers due to:
- Increased work load
- Cost of treatments
- Reduced productivity
- Risk of condemnations
- A negative impact on animal welfare
Bayesian network Case examples Advanced Herd Managem ent October 2 - - PDF document
Bayesian network Case examples Advanced Herd Managem ent October 2 - - PDF document
Bayesian network Case examples Advanced Herd Managem ent October 2 nd 2 0 0 7 Tina Birk Jensen Outline 1 . PigLam e m odel Background of the m odel The qualitative part of the m odel The quantitative part of the m odel
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Leg disorder Pig Info Leg disorder Herd Info
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Strategy 2 Pig Info Leg disorder Strategy 1 Herd Info Strategy 3
Purpose of the PigLame model To estimate probability distributions of different manageable causes of leg disorders in finisher herds
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PigLame model
Bayesian Netw orks
- A set of variables and directed edges betw een
variables
- Each variable has a finite set of m utually exclusive
states
- The variables and edges form a directed acyclic graph
- To each variable A w ith parents B1….Bn, there is
attached the probability table P( A| B1,….,Bn)
Bayesian network
A B ( ) ( ) ( )
) ( ) | ( ... ) ( ) | ( ) ( ) | ( | |
2 2 1 1 n n i i i
A P A B P A P A B P A P A B P A P A B P B A P + + + =
Bayes Theorem :
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Bayesian network
W hy use Bayesian Netw ork approach for the PigLam e m odel?
- Static m odel
- Express the biological variation and represent
uncertainty
- I nform ation can flow in the opposite direction of the
causality
- Evidence about som e input variables can tell us
som ething about variables that are not observable ”Hypothesis variables”
Object-oriented Bayesian network The object diagram for the PigLam e m odel
Herd class Herd size Production Purchase Pen density Floor type Straw Pig class Gender Disease Diagnostic test Lean meat percent
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Qualitative structure of the PigLame model
- Tw o classes: Herd class and pig class
- Background for the qualitative structure is
based on evidence from published literature
Qualitative structure of the PigLame model
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Pen den Floor Straw Environmental Infectious Inherited Herd size Produc- tion Weight Breed Feed strat Purchase
Herd class Pig class
ObsLame PigLame Path7 Path8 Path3 Bac1 Path4 Bac2 Path5 Bac3 Path6 Bac4 Path2 Path1 Clinic1 Clinic2 Path9 Fracture Claw wall Claw sole Myco Strep Erysi Haemo OCM OCD Arth_risk Gender LMP
Environmental Infectious Inherited
TailBite
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The quantitative part of the PigLame model The probabilities in the model are based on:
- Literature
- Expert opinions
The quantitative part of the model
Probabilities elicited from the literature How to get the probabilities into the model Example:
OCM OCD Meat Percent
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The quantitative part of the model
Probabilities elicited from the literature
I ncrease in the LMP of one percentage point OR= 1 .0 3 ( OCM) OR= 1 .0 5 ( OCD) Form ula:
Assum e:
P( OCM) = 0 .5 P( OCD) = 0 .2
OR Pno Pno OR pno Pno Pyes ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ − + ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ − = 1 1 1
The quantitative part of the model
0.537 OR5 = 1.035 = 1.16 P(OCM| 5 percent) 0.530 OR4 = 1.034 = 1.13 P(OCM| 4 percent) 0.522 OR3= 1.033 = 1.09 P(OCM| 3 percent) 0.515 OR2 = 1.032 = 1.06 P(OCM| 2 percent) 0.507 OR1 = 1.031 = 1.03 P(OCM| 1 percent) 0.5 OR0 = 1.030 = 1 P(OCM| 0 percent) Probability Odds Ratio Level 0.242 OR5 = 1.055 = 1.28 P(OCD| 5 percent) 0.234 OR4 = 1.054 = 1.22 P(OCD| 4 percent) 0.225 OR3= 1.053 = 1.16 P(OCD| 3 percent) 0.216 OR2 = 1.052 = 1.10 P(OCD| 2 percent) 0.208 OR1 = 1.051 = 1.05 P(OCD| 1 percent) 0.2 OR0 = 1.050 = 1 P(OCD| 0 percent) Probability Odds Ratio Level
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Exam ple: P( Fracture| fully slatted floors)
Consider 100 pigs examined individually at a herd visit. The herd has fully slatted floors in the pens. How often do you, during the examination expect to find a pig with a fracture?
Exam ple: P( Fracture| fully slatted floors)
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Always (almost) 15 25 50 75 85 100 Usually Often As often as not Sometimes Once in a while (Almost) never
Consider 100 pigs examined individually at a herd visit. The herd has fully slatted floors in the pens. How often do you, during the examination expect to find a pig with a fracture?
Exam ple: P( Fracture| fully slatted floors)
The quantitative part of the PigLame model From the literature
- 46 conditional probabilities
From experts
- > 150 conditional probabilities
- 6 experts
- Not randomly distributed
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The quantitative part of the model
The ”output” nodes
- I nfectious, environm ental and inherited express the
m agnitude of the cause-category at herd level
- Considered as a continuous variable
- Need to m ake a discretization of the node
- Logit m ethod
- The nodes have 1 0 states
Pig class
ObsLame PigLame Path7 Path8 Path3 Bac1 Path4 Bac2 Path5 Bac3 Path6 Bac4 Path2 Path1 Clinic1 Clinic2 Path9 Fracture Claw wall Claw sole Myco Strep Erysi Haemo OCM OCD Arth_risk Gender LMP
Environmental Infectious Inherited
TailBite
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The quantitative part of the model
Exam ple:
The ”output” nodes Inherited OCD OCM
The quantitative part of the model
The ”output” nodes
( 1 ) I nherited= Logit( P( OCM| I nherited) ) + 0 C ( 2 ) I nherited= Logit( P( OCD| I nherited) ) + C Then w e get: ( 1 ’) P( OCM| I nherited) = Logit -1( I nherited – 0 C) ( 2 ’) P( OCD| I nherited) = Logit -1( I nherited – C)
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The quantitative part of the model
The ”output” nodes
Assum e: P( OCM| I nherited) = 0 .5 P( OCD| I nherited) = 0 .2 Then: ( 1 ’) P( OCM| I nherited) = Logit -1( I nherited – 0 C ) = 0 .5 ( 2 ’) P( OCD| I nherited) = Logit -1( I nherited – C) = 0 .2 W hich gives: C= -1 .3 9 I nherited ( OCM) = 0 I nherited ( OCD) = 1 .3 9
The quantitative part of the model
The ”output” nodes
1.39 0.85 0.41
- 0.41
- 0.85
- 1.39
- 2.20
I nherited
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
P( OCM| I nherited)
2.77 2.23 1.79 1.39 0.98 0.54 0.81
I nherited
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
P( OCD| I nherited)
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Perspectives
- Probability distributions for the three cause-
categories of leg disorders can serve as inputs for future econom ic calculations
- First step in developing an econom ic m odel for
leg disorders in finisher herds
Mycoplasma net
Outline Background of the model The model Consequences of Mycoplasma
Literature: Otto, L. and Kristensen, C.S., 2 0 0 4 : A biological netw ork describing infection w ith Mycoplasm a hyopnem oniae in sw ine herds. Preventive Veterinary Medicine, 6 6 , 1 4 1 - 1 6 1 .
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Mycoplasma hyopneumonia
- Cause enzootic pneumonia in finishers
- Important in the intensive pig production
- Can exist latent in the herd
- Outbreak: 50-70 percent of the finishers have lung
lesions
- A well documented disease
Mycoplasma net
Purpose To develop a tool for evaluating the economic consequences of different control strategies against Mycoplasma The decisions are often based on intuition from farmers, advisors and vets
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Mycoplasma net
Building the m odel: Biological m odel:
- Based on biological knowledge
Econom ic m odel:
- Economic risk due to the biological variation
Risk factors Disease level Productivity Economics Constibution margin
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Risk factors Disease level Productivity Economics Constibution margin Control stragegy Diagnostics Mycoplasma net
I nput Risk factors:
- Herd size
- Production type
- Purchase policy
- Season
- Region
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Mycoplasma net
I nput Diagnostics:
- Clinical examination
- Serology examination
- Postmortem examination
Determines the disease level with more precision
Mycoplasma net
I nput Control strategy: (Any action with the aim to change the level of disease) Short term strategy: Medication Vaccination Long term strategy: Change in mangement Change in production system
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Mycoplasma net
Output: Probability distribution:
- Disease level
- Production outcome
- Economical outcome
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The states of the variables
States: 1-1000 / 1001-3000 / 3001-5000 / 5001- States: Yes / no States: Sept. / Dec. / Mar. / Jun. States: Zero / low / middle / high States: Zero / low / middle / high States: 0-1% / 1-10% / 10-20% / 20%- States: 0g / -30g / -60g / -90g States: 0 / 0-0.15 / 0.15-0.30 / 0.30-0.45 States: 0% / ½% / 1% / 1½% Risk factors Herd size All in all out Seson Diagnostics Clinical examination Serologic examination Postmortem examination Productivity outcome Change in daily weight gain Change in feed conversion rate Change in mortality
Text Label
The economic part
Contribution margin = TR – VC TR: The income from the slaughterhouse VC: Weaner price Cost of feed Dead pigs Labor cost Control strategy Diagnosis
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Different scenarios High-risk herd:
Large herd size Continuous 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 Econom ic losses due to Mycoplasm a: High-risk herd
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Econom ic loss due to Mycoplasm a: Low -risk herd
Effect of medication and vaccination
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Perspectives: Mycoplasma net
- Not all needed inform ation can be found in the
literature
- Describes the steady state betw een risk factors
and the severity of Mycoplasm a
- Often it does not pays off to control just one
disease
- I t is im portant to consider several diseases and