6 citations · 6 across the 5 of their papers we have counts for
5 papers
Semi-Markov Models with Particle-Based Bayesian Inference for Epidemics
Patrick Aschermayr, Konstantinos Kalogeropoulos, Nikolaos Demiris
The COVID-19 pandemic has been characterised by multiple waves of transmission driven by interventions and emerging variants, challenging epidemic models that assume gradually evol…
Exchangeable Gaussian Processes with application to epidemics
Lampros Bouranis, Petros Barmpounakis, Nikolaos Demiris +1
We develop a Bayesian non-parametric framework based on multi-task Gaussian processes, appropriate for temporal shrinkage. We focus on a particular class of dynamic hierarchical mo…
Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19
Lampros Bouranis, Nikolaos Demiris, Konstantinos Kalogeropoulos +1
We consider a flexible Bayesian evidence synthesis approach to model the age-specific transmission dynamics of COVID-19 based on daily mortality counts. The temporal evolution of t…
A modelling framework for the analysis of the SARS-CoV2 transmission dynamics
Anastasia Chatzilena, Nikolaos Demiris, Konstantinos Kalogeropoulos
Despite the progress in medical data collection the actual burden of SARS-CoV-2 remains unknown due to under-ascertainment of cases. This was apparent in the acute phase of the pan…
Bayesian spatio-temporal epidemic models with applications to sheep pox
C. Malesios, N. Demiris, K. Kalogeropoulos +1
Epidemic data often possess certain characteristics, such as the presence of many zeros, the spatial nature of the disease spread mechanism or environmental noise. This paper addre…