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Friday, April 26 2024.

Friday, May 31 2024.

PRELIMINARY PROGRAMME (subject to adjustments):

TIME: 11:45 - 17:15 (a total of 24 lecture hours)

15 min break
12:45- 13:30
lunch (13:30-15:30)
15 min break

1. Mathematical concepts and applications (8 weeks)

  • Intro deterministic and stochastic epidemiological models
  • Stability analysis, complex eigenvalues, bifurcation diagrams, state space plots
  • Basic concepts on epidemiology: reproduction number, growth rates, relative risk and vaccine efficacy
  • Data on epidemiology
  • Model validation with empirical data
  • Model projections
  • Infectious disease epidemiology
  • Multi-strain models
  • Chaotic dynamics
  • Lyapunov exponents, predictability
  • Model validation and data analysis
  • Control measures (vaccination and other)
  • Epidemic processes in complex networks

2. Case studies (4 weeks)

  • 2.a. Epidemiological concepts
  • 2.b. Dengue fever: multi-strain, within-host, vaccine
  • 2.c. COVID-19 pandemic: data analysis, epidemiological measures, projections, prediction
  • 2.d. other public health threads

PREREQUISITES: Basic knowledge of ordinary differential equations, linear algebra, and probabilities/statistics

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