MATHEMATICAL MODELLING OF INFECTION DYNAMICS

Osvaldo Anacleto

Course outline

Day 1: General introduction to mathematical modelling & to key concepts for infectious diseases in livestock

Lectures:

• Introduction to key modelling concepts and modelling tools (1.5h-2h)
• Infectious disease fundamentals (1.5h)
Tutorials:
• Group project: Developing conceptual models to investigate the impact of diverse control strategies on infection dynamics (1.5h)
• Introduction to R (Optional) (2h)

Day 2: Modelling epidemics

Lectures:

• Introduction to epidemiological models (deterministic / stochastic, different types of compartmental models)
• Epidemiological models for genetically heterogeneous populations

Tutorials:

• Simulating epidemics
• Simulating impact of selection on disease transmission

Day 3: Mathematical models of within host infection dynamics

Lectures:

• Statistical model of viremia profiles, example PRRS (1/2h)
• Process based models, example PRRS (1h)

Tutorials:

• Exploring viremia profiles (1/2h)
• Exploring process based models of within host infection dynamics; example PRRS (1h)

Day 4: Statistical inference

Lectures:

• Introduction to statistical inference (1h)
• Bayesian methods and MCMC (1h)
• Applications to infectious disease data (1h)

Tutorials:

• Statistical inference of epidemiological parameters (1.5h)
• Bayesian non-linear hierarchical modelling of within-host infection profiles (1.5h)

Day 5: Current research in Bayesian methods for infectious disease modelling

Última modificação em Terça, 20 Dezembro 2016 17:41