Research

Geospatial statistics for epidemiology, methods and applications.

Research interests

My research interests lie in the interface of statistics, epidemiology and health informatics with a particular interest in spatial statistics, public health and environmental epidemiology. I am interested in developing novel model-based geostatistical methods for tropical disease mapping.

My methodological themes include spatial and spatio-temporal statistics; joint modelling of multiple outcomes; geostatistical methods for spatial misalignment and Machine Learning.

My application themes include real-time health surveillance; tropical disease mapping; environmental epidemiology.

PhD Opportunities

I am looking for PhD students to work on the following topics:

  1. Modelling clustering geo-referenced data via mixtures.

  2. Inference for multivariate spatio-temporal models.

  3. Hybrid geostatistical and machine learning approaches for analysing spatial data.

  4. Modelling spatially misaligned data.

Current projects

  • Climate and Health — Causal Inference methods for estimating the indirect effect of climate change on health.
  • Hybrid Machine learning and Geostatistical models — Investigating how best to combine these approaches.
  • COVID-19 - Developing spatio-temporal models and mathematical models for COVID-19.

Software