Bayesian Inference of Epidemics
Levi (Finland), 12-14 March 2023
The workshop aims at collecting recent advances in the field of Bayesian methods applied in the epidemic settings and it will include, among others, key topics such as:
- DA-MCMC for epidemics
- Sequential learning of infectious disease dynamics
- Spatial models for epidemics
- Evidence synthesis and conflicts when analysing epidemic data
- Integration of genetic information and case-data
Info
The workshop in Bayesian Inference of Epidemic is a satellite event of Bayescomp 2023. Link opens in a new window
Find below a concise schedule.
Please consult the respective pages for abstracts, useful news for participants and information about this workshop.
Contact: alice.corbella@warwick.ac.uk
Programme
Here you can find a concise programme with times, speakers and titles. For full abstracts please consult the abstract page.
Day 1: Sun 12th of March
19:30 - 21:00 : Satellite Opening - chair GO Roberts
- SEF SpencerLink opens in a new window (University of Warwick) Introduction to epidemic models and their statistical analysis
- A MiraLink opens in a new window (Università della Svizzera italiana) PERISCOPELink opens in a new window Project - Pan-European Response to the Impacts of COVID-19 and future Pandemics and Epidemics
Day 2: Mon 13th of March
9:20 - 10:10 : Tutorial - Chair SEF Spencer
- TJ McKinleyLink opens in a new window (University of Exeter) A tutorial on history matching with emulation for epidemic models
10:10 - 10:30 : Coffee Break
10:30 - 12:00 : Keynotes - chair GO Roberts
- V MininLink opens in a new window (University of California Irvine) Fitting stochastic epidemic models to noisy surveillance data: are we there yet?
- C FuchsLink opens in a new window (Universität Bielefeld) Integrative modelling of infections in a corona virus cohort study
12:00 - 13:30 : Lunch Break
13:30 - 15:00 : Invited session on Environmental Stochasticity - chair R Browning
- T KypraiosLink opens in a new window (University of Nottingham) Bayesian nonparametric inference for stochastic infectious disease models
- PJ BirrellLink opens in a new window (UKHSA) An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling
- L Guzmann-RinconLink opens in a new window (University of Warwick) Bayesian estimation of the instant growth rate of SARS-CoV-2 positive cases in England, using Gaussian processes
15:30 - 17:00 : Contributed session on Informing Policy - chair SEF Roberts
- R DeardonLink opens in a new window (University of Calgary) Identifying behavioural change mechanisms in epidemic models
- E SemonevaLink opens in a new window (University of Oxford) Spatial statistics with deep generative modelling: flexible and efficient disease mapping with MCMC and deep learning
- A BeloconiLink opens in a new window (Swiss TPH) Malaria, climate variability and the effect of interventions: modelling transmission dynamics
17:00 - 19:00 : Poster session
Day 3: Tuesday the 14th of March
9:10 - 10:10 : Invited session on Sampling from the Hidden states - chair C Jewell
- C PooleyLink opens in a new window (Biomathematics and Statistics Scotland) Fast inference and model selection on epidemiolgical models using model-based proposals
- J XuLink opens in a new window (Duke University) Efficient Branching Process Proposals and Data-Augmented MCMC for the Stochastic SIR Model
10:10 - 10:30 : Coffee Break
10:30 - 12:00 : Keynotes - chair D De Angelis
- S CauchemezLink opens in a new window (Institute Pasteur) Bayesian data augmentation methods applied to infectious disease epidemiology
- P NouvelletLink opens in a new window (University of Sussex)
12:00 - 15:00 : Lunch and Ski break
15:00 - 16:30 : Invited session on Inference of nonlinear dynamics - chair PJ Birrell
- L RimellaLink opens in a new window (University of Lancaster) Approximating optimal SMC proposal distributions in individual-based epidemic models
- M WhitehouseLink opens in a new window (University of Bristol) Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods
- J WheelerLink opens in a new window (University of Michigan) Informing policy via dynamic models: Cholera in Haiti
16:30 - 17:00 : Coffee Break
17:00 - 18:30 : Invited session on Phylogenetic inference - chair D Helekal
- P MarttinenLink opens in a new window (Aalto University) A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation
- J KoskelaLink opens in a new window (Univeristy of Warwick) Bayesian inference of recombinant ancestries
- A GillLink opens in a new window (University of Warwick) Bayesian Inference of Reproduction Number from Genomic and Epidemic Data using MCMC Methods
Contacts
Should you have any question, please do not hesitate to contact us at