GEOGRAPHICAL INFORMATION IN RELATION TO HEALTH

2. CONTENTS
• Introduction
• History
• Components
• Data structure
• Procedure
• Application of GIS
• Remote sensing
• GPS
• SWOT analysis of GIS

3. GEOGRAPHICAL INFORMATION
SYSTEM
• Computer database management and mapping programme that
organizes, stores and displays large amount of multipurpose
information
• Geographic – location – geocoding
• Information – data in GIS – yield useful knowledge
• System – several interrelated and linked components
• Database system
• Analysis system

4. • HISTORY
• Hippocrates – location
can influence the
health
• John Snow 1854 –
cholera outbreak -spot
map

5. GEOGRAPHIC INFORMATION
• Information refers to the location of earth’s surface
• What, where, why?
• What is attribute? Where is location? Why is analytical?

6. Components
• Hardware – central servers to desktop
• Software – for mapping, DBMS, analysis
• Data – spatial and non-spatial
• People
• Methods and procedures

7. SOFTWARES AVAILABLE
GIS Image Processing
 ARC INFO
 ArcView
 MapInfo
 MGE
 Geomedia
 Geoconcept
 WINGIS
 Microstation
 AutoCAD
 ERDAS
 ER Mapper
 ILWIS
 ENVI
 PCI
 ArcView image analysis
 TNTMIPS
 Ecognition

8. Data structure
DATA
GRAPHIC(SPATIAL)
VECTOR
CO-ORDINATE
SYSTEM
ALPHA-NUMERIC
(NON-SPATIAL)
RASTER
IMAGE
ARERAL POTO
REMOTE SENSED
SCANNED IMAGES

9. GRAPHIC – SPATIAL DATA
• Maps and map elements
• Maps – graphic representation of area perception
• Provide 2 types of information
• Locational
• Spatial relationship

10. Maps
• Features and surfaces
• Features
• Point features – single geographic coordinate
• Line features – series of coordinates join to form line
• Area features – series of coordinates join to form boundaries
• Surfaces
• Topography , temperature , air pressure

11. Point Features
• Spatially distributed entities, activities or events
• Points have a single geographic coordinate such as:
• Tree
• Lamp post

12. Line Features
• Lines (Arcs) are a series of geographic coordinates
joined to form a line such as:
• Road
• Stream
• Railway

13. Area Features
• Areas (Polygons) are a series of geographic
coordinates joined together to form a boundary
such as:
• Lake
• Soil types

14. DATA
1. SPATIAL DATA
ATTRIBUTE DATA
2.

15. SPATIAL DATA
Raster
Vector
Data Model And Structure
RASTER MODEL VECTOR MODEL

17. Attribute Data
• Attributes can be numeric or alfanumeric data
that is assigned to a point, line or area spatial
features
• Example
• Name/number of the building, Road name etc

18. Procedure
1. spatial data acquisition with computers
2. spatial data processing – image to vectorized data
3. query and analysis
Spatial analysis
Proximity
Overlay
Network analysis
4. data display
5. data output
6. decision and policy making

21. Querying GIS data
• Attribute query
• Select features using attribute data
• Results can be mapped or presented in conventional database form
• Can be used to produce maps of subsets of the data
• Spatial query
• Clicking on features on the map to find out their attribute values
• Used in combination these are a powerful way of exploring spatial
patterns in your data

22. Attribute query: Lung disease in the 1860s
Spatial data: Registration
Districts, 1/1/1870
Attribute data: Mortality
rate per 1,000 from lung
disease among men aged
45-64
Source: Registrar
General’s Decennial
Supplement, 1871
Query: Select areas
where mortality rate >
58.0

23. Spatial query: Lung disease in the 1860s
District: Alston with
Garrigill
County: Cumberland
M_rate: 68.4

24. Mapping through attribute query

25. ANALYSIS – OVERLAY METHOD
Joins two layers to create a new layer
The output layer will contain both the spatial
AND attribute data from both of the input layers

26. BUFFER/PROXIMITY ANALYSIS

27. NETWORK ANALYSIS

28. APPLICATION OF GIS
• Construction disease maps
• Analyzing trends over space and time
• Mapping populations at risk

30. Spatial Analysis
• Mapping spatial patterns of risk
• Assessing disease clustering
• Obtain new insight into possible methods of exposure

34. Public Health Practice
• Find out geographical distribution and variation of diseases
• Analyze spatial and temporal trends
• Identify gaps in immunization
• Map populations at risk and stratify risk factors
• Document health care needs of a community and assess resource allocations
• Forecast epidemics

35. • Plan and target interventions
• Monitor diseases and interventions over time
• Manage patient care environments, materials, supplies and human resources
• Monitor the utilisation of health centres
• Route health workers, equipments and supplies to service locations
• Publish health information using maps on the Internet
• Locate the nearest health facility.

37. REMOTE SENSING
• Real information of geography at real times through Satellites.
• Started in 1970’s with the prime objective of obtaining Information
about Natural Resources.
• LANDSAT – 1….6 was the first Satellite series launched in the
World by Europian Countries.
• Indian Space Programme (Dept. of Space) was set up in 1972.

38. IMPORTANT TERMS
• Pixel to Ground Resolution
• Multi-Spectral Image
• Multi-Temporal Image
• Pseudo Colour Image
• True & False Colour Composite

39. Spatial Resolutions
Sensor:WiFS
Resolution:180m
Sensor: LISS-III
Resolution: 24m
Sensor: LISS-IV
Resolution:5m

40. RED
BLUE
GREEN
FCC
Multi Spectral Data

41. Multi Temporal Images (1998-1999)
Wheat
Mustard

42. False and True Color Composites
False Colour Composite True Colour Composite
NIR Red Green Red Green Blue

43. MSI in health
• Retinal Health Assessment is a multispectral imaging
• (MSI) device that is useful for the early detection of optic nerve and
retinal disease

45. GPS
• space-based satellite navigation
system
• provides location and time
information in all weather
conditions, anywhere on or near
the Earth
• where there is an unobstructed line
of sight to four or more GPS
satellites

47. SWOT ANALYSIS
• STRENGTH
• Fast and efficient
• Better insight in spatial patterns and of spatial needs
• GIS allows for multilevel modeling
• Useful in exploratory research
• Possibility to do predictions
• Visualization of time series
• Saves time

48. WEAKNESS
• The complexity of the software
• Costs of the software
• limitations associated with data sources and data validity
• The clarity of certain maps can be misleading
• overlook important humanitarian aspects

49. OPPORTUNITIES
• Spread information derived from the data to a broad public
• Costs of data are likely to go down
• The costs and the availability of software will go down
THREAT
• Epidemiologists are often not educated and not aware
• Data, facilities and skilled staff are needed
• Confidentiality cannot be guaranteed

50. THANK YOU