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University of Cambridge > Talks.cam > MRC Biostatistics Unit Seminars > BSU Seminar: 'Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19'
BSU Seminar: 'Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19'Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Alison Quenault. This will be an online seminar. To register to attend, please click on this link: https://us02web.zoom.us/meeting/register/tZ0ocO6qrTsiH9V3mlmvd_EOYT1sTBOKOmUZ We consider a flexible Bayesian evidence synthesis approach to model the age-specific transmission dynamics of COVID -19 based on daily age-stratified mortality counts. The temporal evolution of transmission rates in populations containing multiple types of individual is reconstructed via an appropriate dimension-reduction formulation driven by independent diffusion processes assigned to the key epidemiological parameters. A suitably tailored Susceptible-Exposed-Infected -Removed (SEIR) compartmental model is used to capture the latent counts of infections and to account for fluctuations in transmission influenced by phenomena like public health interventions and changes in human behaviour. We analyze the outbreak of COVID -19 in Greece and Austria and validate the proposed model using the estimated counts of cumulative infections from a large-scale seroprevalence survey in England. This is joint work with Nikolaos Demiris (AUEB), Konstantinos Kalogeropoulos (LSE) and Ioannis Ntzoufras (AUEB). arXiv link: https://aps.arxiv.org/abs/2211.15229 CRAN : https://cran.r-project.org/web/packages/Bernadette/index.html Github repository: https://github.com/bernadette-eu/Bernadette This talk is part of the MRC Biostatistics Unit Seminars series. This talk is included in these lists:
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