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GIS for Public Health

GIS for Public Health. Eddie Oldfield Director, New Brunswick Lung Association. 1918. What can we learn from SARS?. The National Advisory Committee on SARS and Public Health identified many systemic deficiencies in responding to SARS in Canada. Among these were:

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GIS for Public Health

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  1. GIS for Public Health Eddie Oldfield Director, New Brunswick Lung Association 1918

  2. What can we learn from SARS? The National Advisory Committee on SARS and Public Health identified many systemic deficiencies in responding to SARS in Canada. Among these were: • absence of protocols for sharing data, • poor coordination among health authorities at national, provincial, and local levels, • delays in identification of unknown virus, • poor understanding of disease etiology and transmission vectors.

  3. The CGDI and Public Health GIS applications have become a staple in European health policy: • health data management tools in Italy, • a national public health atlas in The Netherlands, • healthcare planning tools in Switzerland, and • modular GIS applications in the United Kingdom. The expansion of theCanadian Geospatial Data Infrastructure and other national SDIs into the public health discipline is deemed critical for addressing shortcomings in population health monitoring, developing effective intervention strategies for chronic and infectious disease, improving healthcare services, and responding to health and safety emergencies. SDI: Spatial Data Infrastructure

  4. Potential for Applications in Canada and the US • All respiratory diseases • Monitor chronic diseases • Monitor epidemic outbreaks (influenza), communicable disease clusters, and disease vectors (e.g. migratory bird routes, zoonotic vectors) • Joint health and safety emergency management (e.g. bioterrorism) • Monitor water (including well-water) and food quality • Aboriginal health status (Tuberculosis, Diabetes etc) • Ambulance vehicle routing • Public Health Resource management • Population demographics (for assessing population vulnerabilities) • Global Warming: predictive health impacts modeling • Cross-disciplinary research (linking air quality, climate change and human health)

  5. Example of a thematic map showing the different insecticide treatments and the localization of bird reports and mosquito pools, in 2003. This thematic map shows the different insecticide treatments (shaded areas) and the localization of bird reports (colored dots) and mosquito pools (colored triangles) along with their status, in 2003.

  6. Example of a thematic map showing the status of reported dead Corvidae around the Montreal Island, in 2005. This thematic map shows the status (represented by different colors) of reported dead Corvidae for different territorial subdivisions around the Montreal Island, in 2005. Reference: “The Integrated System for Public Health Monitoring of West Nile Virus (ISPHM-WNV): a real-time GIS for surveillance and decision-making.” Pierre Gosselin, Germain Lebel1, Sonia Rivest and Monique Douville-Fradet

  7. Modeling Health Impacts from a Changing Climate These health issues call for the application of ecological and systems-based approaches. The classical toxicological model applied in environmental epidemiology, where defined exposure to a specific agent causes an adverse health effect to identifiable exposed populations, is generally not adequate for assessing indirect or multi-causal impacts of climate change on human health.* • Extreme Weather Events • Heat Waves • Flooding / floodplain management • Vector & Rodent borne diseases • Water-borne diseases • Drought / water supply • Food-borne diseases / food supply • Predictive Modeling * World Health Organization – Climate Change and Adaptation Strategies for Human Health

  8. Add slide showing graph / map, air quality + health in a community

  9. Gaps in GIS for Public Health • Lack of infrastructure (protocols for distributed access) • Uneven capacity among health authorities (i.e. resource constraints) • Concerns over data privacy / poor access to data • Barriers to integration of health data within CGDI (i.e. lack of health data standards / inconsistencies) • Inconsistent ‘patchwork’ approach to development of applications (technology does not currently satisfy public health requirements)

  10. Gaps in GIS for Public Health • Lack of training among public health professionals and traditional IT support • Lack of engagement of provincial epidemiologists in GIS-based modeling of health determinants and for population health monitoring • Lack of Canadian methodologies / research • Inadequate research agenda / cross-jurisdictional • Inadequate promotion of benefits to decision-makers

  11. ? Planning for One Scenario? Not likely. Virulence, Progression, Peak, Rate of Mortality Multiple Health Responses to Escalating Threats (WHO Protocols)

  12. electron microscope image of the Avian Flu Virus Understanding Spatial Disease Epidemiology • Baseline Influenza vs Pandemic Indicators • Transmissibility / Vectors • Progression Rate / Death Rate • Vulnerable Populations • Access to Health Care • Vaccine Distribution • Capacity / Demand Surge • Affected Health Care Workers From Micro To Macro

  13. Mapping Public Health Data Community Health Maps Kilometers 0 25 50 100 Access to Health Care Asthma Admission / 10,000 Population – 2001 Admission / 10,000 Population Mapping Influenza Cases 0 0.1 - 7.1 7.1 - 9.7 9.7 - 15.7 15.7 - 110.3

  14. Kilometers 0 25 50 100 0 0.1 - 7.1 7.1 - 9.7 9.7 - 15.7 15.7 - 110.3 Mapping Public Health Data New Brunswick Lung Association American Lung Association of Maine University of New Brunswick University of Southern Maine Maine Health Authority / CDC NB Department of Health Public Health Agency of Canada Emergency Measures Organization (NB) Service New Brunswick WHO-PAHO / University of Laval Cox-Hanson O’Reilly Matheson Law Firm CARIS Ltd

  15. Chief Medical Officer Physician / Nurse Data Technician Lab / Verification of Suspected Cases Identification of disease strain / etiology Vaccine Distribution Must be easy to use Ambulatory Response Notification Public Access

  16. CARIS Spatial Fusion Enterprise Configuration Manager http://www.caris.com/products/

  17. Wireless and Remote Applications Porting an existing desktop web application Layered windows Prototype Thin Client in Action Map View Data Entry

  18. Integrating Data • Quality Checking (errors, omissions) • Vertical and Horizontal Alignment • Scale Matching / Representation • Matching Health Codes / Identifiers • Multi-Dimensional DB Design • Spatial and Temporal Stamps / Querying • Statistical Modules (average / total, normalized by population, etc)

  19. User CollaborationIncident Management and Spatial Analysis Tools • Public Participation GIS – municipal model, University of New Brunswick • Existing Incident Management / Tracking and Spatial Tools are Independent • Geo-Conferencing, TGIS • CARIS Spatial Fusion Enterprise with Incident Management Suite • OGC Standards Development, CGDI Services, WMS/WFS compliance

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