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EMULSION: an expert-friendly language for designing and exploring mechanistic epidemiological models

EMULSION: an expert-friendly language for designing and exploring mechanistic epidemiological models
Complex mechanistic epidemiological models are powerful methods to understand and predict pathogen spread at multiple scales

Complex mechanistic epidemiological models are powerful methods to understand and predict pathogen spread at multiple scales. Yet, model development is a long and difficult task, often resulting in a frozen simulation code not easily accessible to non-computer scientists, either to check that the model was properly implemented, or to modify the model itself.
To help design such models, Artificial Intelligence (AI) provides powerful methods. Within this workshop, we aim to introduce EMULSION, an innovative AI-based tool intended to foster explicit model description via an user-friendly language, to revise/explore assumptions on model structure, on parameter values, and on disease management, and to facilitate scale change (e.g. from within- to between-herd scale).
The goal of this workshop is to demonstrate how to rapidly change models in response to revised hypotheses, including back and forth between one scale and another, and transforming a compartmental model into an individual-based one, without code implementation. After a short overview of EMULSION principles, participants will be guided through a set of gradual exercises based on realistic situations encountered in animal health. An already implemented model will be used and updated.

Hands-on work will be done in small groups (2-3 people) to foster interactivity. Participants are expected to work using their own laptop, for which installation instructions will be provided prior to the workshop.
Learning outcomes:
1. To be able to use EMULSION modelling language to describe their models
2. To become familiar with the software commands to run their own simulations.

Pre-workshop competences and knowledge • Experience in mechanistic epidemiological modelling. Programming skills not required.