1. Disease Mapping
GIS maps the location of diseases.
Helps identify areas with high disease cases.
Scholar: John Snow (1854) – Created the famous cholera map in London, considered the foundation of medical mapping.
2. Health Risk Mapping
Identifies areas with high health risks (pollution, floods, poor sanitation).
Helps governments plan preventive measures.
Scholar: Charles Picket (1990s) – Promoted GIS applications in public health planning. (Often cited in health GIS literature; ensure the spelling is "Picket/Picquet" according to your syllabus source.)
3. Hotspot Analysis
Finds places with many disease cases.
Used to identify disease outbreak areas.
Method: Getis-Ord Gi* Statistic.
Developed by: Arthur Getis & J. Keith Ord (1992).
4. Coldspot Analysis
Finds places with very few disease cases.
Helps compare healthy and unhealthy regions.
Method: Getis-Ord Gi* (1992).
5. Cluster Analysis
Groups nearby disease cases.
Detects disease clusters for epidemiological studies.
Common Method: Spatial Cluster Analysis, Local Moran's I.
Scholar: Luc Anselin (1995).
6. Containment Zones
GIS identifies and maps infected areas.
Used during COVID-19 to restrict disease spread.
Widely applied: 2020 COVID-19 pandemic.
7. Kernel Density Estimation (KDE)
Creates a smooth map showing disease concentration.
Higher density = higher disease occurrence.
Scholar: Murray Rosenblatt (1956) and Emanuel Parzen (1962) developed kernel density estimation.
8. Getis-Ord Gi* Analysis
Identifies statistically significant hotspots and coldspots.
Widely used for disease surveillance.
Scholars: Arthur Getis & J. Keith Ord (1992).
9. Emerging Hotspot Analysis
Detects new, persistent, intensifying, or diminishing hotspots over time.
Helps monitor disease spread and changing health patterns.
Popularized through: Esri ArcGIS Space-Time Pattern Mining tools (2010s).
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