Infectious disease modelling to inform policy.

Area of Science:

• Veterinary epidemiology
• Mathematical modeling
• Decision science

Background:

• Modeling is increasingly vital for animal disease management and policy decisions.
• Ensuring the optimization of the modeling process maximizes benefits for decision-makers.
• A structured approach is needed to improve the utility and impact of animal disease models.

Purpose of the Study:

• To present a ten-step framework for optimizing the animal disease modeling process.
• To enhance the relevance and understanding of modeling outputs for decision-makers.
• To improve the overall effectiveness of animal disease modeling in informing policy.

Main Methods:

• Development of a ten-step protocol for animal disease modeling.
• Categorization of steps into initialisation, modeling/quality assurance, and reporting phases.
• Emphasis on defining the question, answer, and timescale upfront.

Main Results:

• A structured ten-step process is proposed to improve animal disease modeling.
• Four steps focus on initialisation (defining scope and objectives).
• Two steps cover the modeling process and quality assurance, followed by four reporting steps.

Conclusions:

• A greater emphasis on the initialisation and reporting stages of modeling projects is recommended.
• This structured approach is expected to increase the relevance of modeling work.
• Improved understanding of results will contribute to better-informed animal disease decision-making.