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One health as a tool to strengthen
interactions between risk modelling and
veterinary and human public health
Sophie O. Vanwambeke, UCLouvain
Katrien Tersago, Uantwerp
Luigi Sedda, UOxford
Needs for public health

• Accurate info in summarized form, eg: early warning,
risk vs. non risk,… accounting for changing human
behaviour
• Rapid and excellent interconnections between all
actors: practitioners, PH agencies, modellers
Modelling today

AUC? ROC?
GLM? GWR?
AIC? BIC?

• Modellers absorbed by modelling
• Entry points into modelling often diverse
• Modelling methods and data sets, while more
broadly accessible, are also getting more complex.
• Diversity of outcomes (eg maximise info vs.
Minimise error)
An example: hantavirus

Minimize error strategy: prediction
Sedda and Tersago, in progress

Maximise information: explore environmental
determinants
Zeimes et al, 2012
EDENext steering committee meeting, Budapest, 31 March 2011

5
How can one health help
• Support interpretation of factors and complex
processes represented in models for zoonotic
diseases
• Facilitate communication across disciplines
• Optimise use of resources for surveillance and
control
• EDENext!
Lessons learned
• Modellers should
communicate better, from
the onset, on PH
knowledge of the system,
and on information content
of modelling results.
• Modellers should highlight
better the PH relevant
information of model
outputs

Questions asked
• How do modellers need to
change their modelling
practice?
• What does risk -as a
modelling output- mean?
How to come up with
model outputs relevant to
risk assessment?

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One Health As A Tool to Strengthen Interactions Between Risk Modelling And Veterinary And Human Public Health

  • 1. One health as a tool to strengthen interactions between risk modelling and veterinary and human public health Sophie O. Vanwambeke, UCLouvain Katrien Tersago, Uantwerp Luigi Sedda, UOxford
  • 2.
  • 3. Needs for public health • Accurate info in summarized form, eg: early warning, risk vs. non risk,… accounting for changing human behaviour • Rapid and excellent interconnections between all actors: practitioners, PH agencies, modellers
  • 4. Modelling today AUC? ROC? GLM? GWR? AIC? BIC? • Modellers absorbed by modelling • Entry points into modelling often diverse • Modelling methods and data sets, while more broadly accessible, are also getting more complex. • Diversity of outcomes (eg maximise info vs. Minimise error)
  • 5. An example: hantavirus Minimize error strategy: prediction Sedda and Tersago, in progress Maximise information: explore environmental determinants Zeimes et al, 2012 EDENext steering committee meeting, Budapest, 31 March 2011 5
  • 6. How can one health help • Support interpretation of factors and complex processes represented in models for zoonotic diseases • Facilitate communication across disciplines • Optimise use of resources for surveillance and control • EDENext!
  • 7. Lessons learned • Modellers should communicate better, from the onset, on PH knowledge of the system, and on information content of modelling results. • Modellers should highlight better the PH relevant information of model outputs Questions asked • How do modellers need to change their modelling practice? • What does risk -as a modelling output- mean? How to come up with model outputs relevant to risk assessment?