Overall Course Design

The course will be structured to cover basic methods and principles on the first two days, and to consider more advanced issues on the final two days, thereby allowing those with experience to join for the latter part of the course only, if they wish. Participants may register for five days or for Mon-Wed or Wed-Fri. The course will also be structured to move progressively from consideration of health data, at the start, to exposure modelling and linkage of health, socio-economic and environmental data at the end. The third day will be reserved for invited speakers, and will be run in conference mode.

Following registration and an Introduction on day 1, the course will be run as a series of sessions, daily. Course days (i.e. other than Wednesday) will comprise a mix of lectures, practical demonstrations, small-group discussion sessions and plenary discussions as follows:

Session A. 09.00–10.30: Lectures and demonstrations (focusing on key methods)

Morning tea

Session B. 11.00–13.00 Small-group discussions (3 groups, chaired by course leaders, discussing applications and examples)

Lunch

Session C. 14.00–15.00: Panel session and plenary discussion (to discuss advantages, disadvantages and alternatives to each method)

Afternoon tea

15.30–17.00: Reflective lecture (to consider cross-cutting issues – e.g. scale, MAUP, uncertainty)

Course leaders

David Briggs, Linda Beale, Clive Sabel ( Imperial College London )

Each day will be led by a different member of the team, with contributions (including lectures, demonstrations, chairing discussions) from other members.

Indicative Programme

Monday: Mapping and visualisation – Leader L. Beale

1. Introduction: principles of epidemiology; the role of geography in epidemiology and risk analysis
2. GIS in the context of epidemiology: what are GIS? what can GIS do? spatial data types, data sources
3. Visualisation and mapping: principles of map design, visualisation techniques, good and bad practice in visualisation
4. Population and disease mapping: mapping raw health data, the small number problem, map smoothing
5. The modifiable areal unit problem and scale

Tuesday: Exploring spatial data – Leader C. Sabel

1. Getting to know your (spatial) data: why explore spatial data; approaches to data exploration
2. Exploring point data: buffering, interpolation (kriging etc), point density functions
3. Pattern, cluster and outlier detection
4. Uncertainty

Wednesday: Guest lectures

Topics to be confirmed.

Thursday: Modelling Spatial Data – Leader D. Briggs

1. Exposure and health: the source-impact chain; exposure pathways and processes; determinants of exposure
2. Spatial modelling of exposure: exposure metrics; simple proximity methods; intelligent interpolation; land use regression; focal sum methods
3. Modelling people: modelling population distribution; modelling human dynamics
4. Time-space modelling of exposure: the role of time; linking time and space

  Friday: Applying GIS in epidemiology and risk assessment – Leader D. Briggs

1. Linking environmental, socio-economic and health data – some practical examples
2. GIS in risk epidemiology and risk analysis – towards a more integrated approach; demonstration of the Rapid Inquiry Facility
3. Designing epidemiological studies – the place for geography
4. Using GIS for advocacy and awareness raising
5. Using GIS for decision-making and policy development