GeoVisualisation of health data

Prof Clive SabelGeography, CLES andEuropean Centre for Environment & Human Health

Spatial data mining

case-studies - Childhood Obesity in Devon

- Neurological disease in Finland

- Road Traffic Accidents in New Zealand

Childhood Obesity in Devon

US election 2004

US election 2008

‘Distorted’maps:

Cartograms

HIV Prevalance

Physicians working

Neurological disease in Finland

Cases MND

• 1000 cases• 3113 case residences• But population

naturally clusters in cities

• So search for ‘excess’ over and above the background rate

• Kernel (Density) Estimates ofAll places of residence

• Statistical Significance tested by Monte-Carlo Simulation

• Note large peak in SE Finland

Residential Clustering ofMotor Neurone Disease

Finland

Space-TimeVisualisation

• Residential Migration• Animation

• Space: Finland• Time: 1965 – 1990

• Illustrates Spatial and Temporal variation

• Note:• persistent dark areas in SE• In SW, at varying times, areas

switch from high to low rates of disease

MND Individual Migration Histories

• Same data as before, but now showing individual migration trajectories.

• The larger densities of colour identify the larger cities

Road Traffic Accidents in New Zealand

Christchurch, NZCity Centre

Also a Kernel density estimate of RTAs.

Compare model results (black polygon) with observations (red-blue image)

Note more accidents than modelled in thecity centre, and around junctions

Left:Temporal analysis of all road accidents- accidents reducing over time, due to increased safety measures introduced.

Right:Temporal analysis of just accidents

involving cyclists- accidents increasing in the circled area,

why?

Drive Safely!