Bayesian inference and model selection for stochastic epidemics

Statistical modeling of epidemic outbreaks


The workshop will take place on 5 May 2023 at the Department of Statistics, Athens University of Economics and Business, Athens, Greece. The primary aim of this workshop is to facilitate a discussion of current research topics related to the Statistical modeling of epidemic outbreaks. It is aimed at Public Health policy makers, Epidemiologists, Statisticians and Data Scientists, as well as students working in these areas.

The workshop is open to all, but participants who wish to attend should email us at bernadette.aueb AT for catering purposes.


Marc Baguelin (Imperial College London & London School of Hygiene and Tropical Medicine)

Angelos Alexopoulos (Athens University of Economics and Business)

Theodore Kypraios (University of Nottingham)

Vana Sypsa (National and Kapodistrian University of Athens)

Lampros Bouranis (Athens University of Economics and Business)


09:30-10:15 Marc Baguelin, Models and evidence synthesis for policy making [slides]

10:15-11:00 Vana Sypsa, Modelling transmission and control of infectious diseases: From HIV and antibiotic resistant bacteria to SARS-CoV-2 [slides]

11:00-11:45 Angelos Alexopoulos, A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes [slides]

11:45-12:15 Break

12:15-13:00 Theodore Kypraios, Bayesian Non-Parametrics for Stochastic Infectious Disease Models [slides]

13:00-13:45 Lampros Bouranis, Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19 [slides]


Auditorium, Trias Building, Athens university of Economics and Business [Map]

Trias 2, Athens, 113 62

Contact Details

Email: bernadette.aueb AT

Twitter profile: BernadetteMsca

Organising/Scientific committee

Lampros Bouranis (Athens University of Economics and Business)

Nikolaos Demiris (Athens University of Economics and Business)


EU emblem

This BERNADETTE project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101027218.

For more information, please visit the European Commission’s Community Research and Development Information Service (CORDIS) webpage.