Geographic Information Systems (GIS) for Epidemiology and Public

Geographic Information Systems (GIS) for Epidemiology and Public Health Dr. Ming-Hsiang Tsou Department of Geography, San Diego State University PPT slides: http://map.sdsu.edu/publications/GISpublichealthtsou.ppt

GIS is about geography and about thinking geographically. --Demers,

Acknowledgement Thank Dr. Brett A. Bryan for the permission of using his slides and GIS examples (from The University of Adelaide, AUSTRALIA. http://www.gisca.adelaide.edu.au/ bbryan/

What is “information”? Data vs. Information (cooking example) Example: weather information What is “information system”? Information System is a chain of operations incorporating data collection and digitization, data storage and analysis, and interpretation. Examples: financial information systems (ATM).

GIS definitions Demers, 2000: GIS are tools that allow for the processing of spatial data into information, generally information tied explicitly to, and used to make decision about, some portion of the earth. A data input subsystem A data storage and retrieval subsystem A data manipulation and analysis subsystem A reporting subsystem (data output) A data sharing mechanism

Medical Geography Control of infectious disease very important Disease control requires understanding Geography can provide intelligence Location can influence health John Snow's 1854 study – cholera mapping Spatial analysis can assist in solving medical problems

Dr. John Snow’s London Street Map (1854) http://www.ph.ucla.edu/epi/snow/Snowpart2 files/frame.htm (slide 10-15)

What GIS Can Do? Integrate many different types of data – Spatial data Non-spatial data (statistical, texts,.) With GIS we can easily: – Draw maps and visualize spatial distributions – Edit and alter existing data – Accurately measure distances and areas – Overlay maps of different areas – Internet GIS for public access.

Combine Geographic Locations with Attribute Data

What GIS can help Public Health? Research Tools and Planning – Constructing mathematical models – Service planning and optimisation – Making predictions Spatial Decision Support Systems – – – Infrastructure – roads, towns, services Census – population statistics Medical resource (hospitals, clinics, available beds) Emergency Response Systems – Medicare records, 911 services – disease registers systems

GIS Applications in Epidemiology 1. Data Visualisation and Exploration 2. Data Integration 3. Monitoring 4. Geostatistics and Modelling 5. Spatial Interaction and Diffusion 6. Data Sharing and Web Services

Data Visualisation and Exploration 2D visualisation capabilities – maps – Distibutions – Patterns – Clusters 3D visualisation capabilities - surfaces 4D visualisation capabilities – temporal – Animations – Eg. Applied to spread/retreat of disease Increases understanding of disease Enables informed planning for disease management

Example 3D Visualization 3D Extrus ion Densi ty Surfac e

Data Integration Thematic structure Map Overlay Compute new information Research – Integrated risk factor datasets to form risk model – Used buffering, map algebra – Able to predict likelihood of elevated blood lead levels, based on location of residence

Temporal Change: Malaria

Monitoring Monitoring – scrutiny over space and time – Eg. Disease surveillance Through surveillance, a picture of disease activity is developed – – Geographic distribution of disease Patterns, clustering and hot spots GIS can provide data management and visualisation WWW can disseminate this information in real time Internet GIS ! (GEOG596 Internet Mapping) Requirement – infrastructure and data update SARS example.

San Diego Wildfire 2003 Http://map.sdsu.edu (GEOG 596) Internet Mapping

Geostatistics and Modelling Explore statistical relationships in data – Build geostatistical surfaces – Detect clusters – Significant change over time and space – “Statistical Alarm Bell” – Display outlier or influential cases by location Statistical analysis also useful in finding zones of significantly higher disease prevalence

P e o p le p e r H o u se 1 . 0 0 - 4 .0 0 Investigating Dengue in Iquitos, Peru (maps from Dr. Art Getis, SDSU faculty) 4 . 0 1 - 6 .3 2 6 . 3 3 - 7 .6 7 6 . 5 4 - 6 .6 2 1 0 .0 0 People Per House by Block in the Eighth Quarter N 0 1 2 K il o m e t e r s

Geostatistics and Modelling (cont.) Advanced spatial/non-spatial models can be built Procedures such as regression, correlation, ANOVA Variables may be: – Non-spatial – Eg. smoking/non-smoking, occupation – Spatial – Eg. proximity to factories Test hypotheses about disease patterns – Eg. Does low air quality increase likelihood of flu because of weakened respiratory systems? – High density of flu cases in low air quality zones?

Modeling of Dengue Transmission Pictures from Dr. Dana A. Focks http://www.id-analysis.com/pages/

Spatial Interaction and Diffusion Used widely to help explain the spread of disease Spatial interaction models – analyse & predict flows central to disease transmission – Eg. Model spread of flu by using interstate flight data & intrastate road travel – Identify high risk pathways of disease transmission target intervention Spatial diffusion models – Model spatial & temporal dimensions of disease spread – Predict how diseases spread from source

Application Examples GIS currently underutilized generally Great potential in: – Epidemiological research – Communicable disease control – Health service planning and optimization

Software Tools ESRI ArcView (entry level use) ESRI ArcGIS (ArcMap, ARC/INFO) advanced users ESRI ArcIMS (Internet Map Server) (www.esri.com) GRASS (public domain software) Autodesk Map2000, Intergraph GeoMedia

Hospitalisations at LGA, CDs, towns

Integrating service data – hospital beds

Unit record ambulance response rates

Surface building and hot spot analysis

Address Matching Convert patients’ addresses to the geospatial location on maps.

Limitations of GIS Communication Gaps between epidemiologists & spatial professionals Require uniform data standards – Eg. Address recording 1/32 Main St. or Unit 1 32 Main St. – Unit record data access – Consistent and meaningful areal units – Enable consistency & comparison Privacy issues and spatial aggregation

Summary GIS can provides spatial dimension to epidemiological research (visualization, modeling ). GIS can be used for many public heath applications and services. (efficient allocation of health care resources, equity in accessibility to services ) Internet GIS can provide the public health information in real-time. (evaluation, decision support systems, emergency response )

GIS Sources for Public Health ESRI http://www.esri.com/industries/health/index .html Books: – GIS and Public Health by Ellen Cromley and Sara McLafferty. The Guilford Press. 2002. – Internet GIS by Zhong-Ren Peng and Ming-Hsiang Tsou. Wiley, 2003.

GIS course in Geography, SDSU GEOG 381 (Maps and Graphic Methods) GEOG 484 (Intro GIS) GEOG 584 (Intermediate GIS) GEOG 596 (Internet Mapping) – http://map.sdsu.edu/geo596 PPT slides: http://map.sdsu.edu/publications/GISpublichealthtsou.ppt