Seminar 07/3: ‘Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19

On March 7th, the seminar series will welcome Dr. Lampros Bouranis, a Marie Skłodowska-Curie Fellow at the Department of Statistics, Athens University of Economics and Business. Dr. Bouranis presented work, completed jointly with Nikolaos Demiris (AUEB), Konstantinos Kalogeropoulos (LSE) and Ioannis Ntzoufras (AUEB), investigating the age-specific transmission dynamics of COVID-19.

Title

Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19

Abstract

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 are 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.

arXiv link: https://aps.arxiv.org/abs/2211.15229

Github repository: https://github.com/bernadette-eu/indepgbm

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