Computational Spatial Statistics

The vision for this strand of research is to apply spatial statistical methods to research questions in ecology, epidemiology, and public health.  At the moment the methods used include point process models, namely, Area interaction point processes and Log Gaussian Cox point processes.  The projects completed include work which focused on spatiotemporal models for investigating the spread of COVID-19 in different spatial settings.  Various journal articles have been published in this theme.

Most recently, a group of us have started work on a project which involves Dengue incidence and climate change data from Brazil.

Public Health

The vision for this theme is to apply quantitative methods to inform public health policy and intervention evaluation.  Projects which I have been involved with in this theme include the evaluation of 20mph speed limits in the City of Edinburgh, the analysis of the impact of COVID-19 on Scottish care homes, and the evaluation of COVID-19 community champion schemes in various LAs in the UK.

Glenna Nightingale née Evans

Dr Glenna Nightingale 

Research themes

Computational Social Science

The vision for this theme is to apply statistical modeling approaches within a robust computational environment to address research questions within demography and health in social science.  At the moment the methods employed include Generalised additive models and Latent Mixture models. 

Under this theme is the Computational Social Science research group (CSS).  Members of this group are from various institutions including the University of Edinburgh, the University of Southampton, and Queen Margaret University.

The grouping orginally started when some of us applied for our first grant.  This funding enabled us to work on investigating trends in mental health during the COVID-19 pandemic in the UK.  We are currently working on a manuscript for publication.

A second successful grant application by a subset of this group enabled us to investigate predictors for obesity using the NCDS dataset.  We have given a talk at the Usher Institute and are currently preparing a manuscript for publication.