3 papers
cs.LG2026
Spatio-temporal stochastic graph-based learning for infectious disease forecasting
Luz Stefani Sotomayor Valenzuela, Susanna Cramb, Darren Wraith
Spatio-temporal graph-based models have typically been used to forecast new cases of infectious diseases such as COVID-19 and chickenpox outbreaks. However, the use of stochastic m…
stat.AP2024
Creating area level indices of behaviours impacting cancer in Australia with a Bayesian generalised shared component model
James Hogg, Susanna Cramb, Jessica Cameron +2
This study develops a model-based index creation approach called the Generalized Shared Component Model (GSCM) by drawing on the large field of factor models. The proposed fully Ba…
stat.AP2023
Mapping the prevalence of cancer risk factors at the small area level in Australia
James Hogg, Jessica Cameron, Susanna Cramb +2
Cancer is a significant health issue globally and it is well known that cancer risk varies geographically. However in many countries there are no small area level data on cancer ri…