6 papers
A spatio-temporal block aggregation model for latent log Gaussian outcomes: application on modelling wastewater virus concentration in Wales
Stephen Jun Villejo, Peter Diggle, Guangquan Li +6
Wastewater-based epidemiology has emerged as a valuable tool for monitoring community-level infectious disease dynamics, providing population-wide signals that complement clinical…
Spatially continuous modelling of aggregated outcome data
Stephen Jun Villejo, Peter Diggle, Finn Lindgren +5
This work develops a block aggregation approach to spatial estimation and prediction when the response is observed at a coarse spatial scale, for example as counts of events in adm…
Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model
Stephen Jun Villejo, Sara Martino, Janine Illian
Dengue is an infectious disease which poses significant socioeconomic and disease burden in many tropical and subtropical regions of the world. This work aims to provide additional…
Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration
Stephen Jun Villejo, Sara Martino, Janine Illian +2
This work tackles the problem of uncertainty propagation in two-stage Bayesian models, with a focus on spatial applications. A two-stage modeling framework has the advantage of bei…
A Data Fusion Model for Meteorological Data using the INLA-SPDE method
Stephen Jun Villejo, Sara Martino, Finn Lindgren +1
This work aims to combine two primary meteorological data sources in the Philippines: data from a sparse network of weather stations and outcomes of a numerical weather prediction…
Data Fusion in a Two-stage Spatio-Temporal Model using the INLA-SPDE Approach
Stephen Jun Villejo, Janine B Illian, Ben Swallow
This paper proposes a two-stage estimation approach for a spatial misalignment scenario that is motivated by the epidemiological problem of linking pollutant exposures and health o…