Lead


Lay summary

This research project aims to develop novel statistical methodology for

Both retro- and prospective analysis of space-time data on infectious disease

incidence. The new techniques will be applied in the particular context

of space-time surveillance data, but important parts of the methodology can

be used in a wider context.  The first sub-project is concerned with appropriate

integration of network data in statistical models to better describe the

spatio-temporal spread of infectious diseases. Both parameter- and

observation-driven models will be suitably extended and statistical

algorithms will be developed to incorporate the impact of network data in the

analysis.The second sub-project is concerned with the prospective analysis of

space-time count data. Statistical algorithms for sequential analysis of time

series models will be extended to the space-time setting with particular focus on

multivariate outbreak detection. Validation of both retro- and prospective analyses

will be based on the assessment of out-of-sample predictions based on proper

scoring rules.