Spatial Analysis
The analysis of spatial patterns of health and disease has been greatly enhanced by recent advances in geographic information systems (GIS), remote sensing (RS), global positioning systems (GPS) and spatial statistics. The Department has an active research programme that uses GIS and spatial analysis in epidemiological research. Departmental staff also coordinate the Schools GIS facilities and have worked with many other groups to examine how spatial methods can be used in public health research.
Projects that utilize spatial methods
Environment & Health
- Air pollution & infant mortality
- Air pollution & implanted cardiac defibrillators
- Environmental determinants of physical exercise
- The ASHRAM study of Arsenic and cancer risk
- Warm Front evaluation
- Weather & respiratory infections
Surveillance
- European surveillance of congenital anomalies
- Cryptosporidiosis in England
- Cutaneous Leishmaniasis surveillance in Tunisia EMPHIS
- Chagas disease in Columbia & Venezuela
Geographical Variations
- Evaluation of the teenage pregnancy reduction strategy
- Geographical variation in congenital malformations
- London: our transport, our science, our health
- Mapping access to healthy food in Sandwell
- WHO Global atlas on traditional and complimentary medicine
Course and Training
The Department is also responsible for running training courses in GIS, which are open to external applicants. For full details contact Chris Grundy (chris.grundy@lshtm.ac.uk).
2 day introduction to geographical information systems and the software ArcView
This is an introduction to the basic principles of GIS The majority of the two days is spent using the software ArcView. The course is aimed at health professionals with no previous GIS experience and covers the main topics required to start using GIS in public health.
The course runs in February, July and August.
Longer term training in the use of spatial analysis in public health
There are several options available for longer term training through research collaboration, visiting attachments or research degrees.
Associated Staff
| Ben Armstrong | Professor, Statistics |
| Zaid Chalabi | Senior Lecturer, Mathematical modelling |
| Chris Grundy | Lecturer, GIS |
| Shakoor Hajat | Senior Lecturer, Statistics |
| Sari Kovats | Senior Lecturer, Epidemiology |
| Giovanni Leonardi | Consultant in Public Health |
| Sam Pattenden | Lecturer, Statistics |
| Carolyn Stephens | Reader, Environmental health policy |
| Paul Wilkinson | Reader, Epidemiology |
