Geographic Information Systems GIS and Public Health

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Geographic Information Systems (GIS)and Public
Health
Dionne Gesink Law National Institute of
Environmental Health Sciences National Institutes
of Health Department of Health and Human Services
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GIS and Disease

• The spread of disease is unavoidably spatial
  EE Holmes
• Infection moves from individual to individual
  following a network of contacts within a
  population through local and global
  (long-distance) transmission

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http//www.who.int/csr/sars/en/
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GIS and Disease

• GIS can enhance emergency preparedness and
  response locally, nationally, globally
• Strengthen data collection, management and
  analysis
• Monitor changes over time, in near-real time
• Develop early warning systems
• Plan and monitor response programs
• Communicate to decision makers and the public

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Surveillance and ControlWorld Health
Organization

• Public Health Mapping Program
• Developed in 1993
• WHO and UNICEF
• Boost efforts to eradicate guinea worm disease
  through the use of GIS

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Surveillance and ControlWorld Health
Organization

• Visualize disease foci
• Monitor newly infected or reinfected villages

• Identify populations at-risk
• Target interventions
• Monitor eradication efforts

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Surveillance and ControlWorld Health
Organization

• Global initiatives
• Eradicate Poliomyelitis
• Role Back Malaria

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Surveillance and ControlWest Nile Virus in the
US

• CDC-USGS National Surveillance Plan
• Monitor geographic and temporal trends and spread
  of infection
• Provide current national and regional information
  publicly
• Define regional distribution and incidence of
  other arbovirus diseases

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West Nile Virus (April 2003)
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Syphilis in Baltimore, Maryland (1994 2001)

• Examine the spatial distribution of reported
  early syphilis cases
• before, during, and after outbreak (1995/6)
• Overall density of syphilis infection
• 5.9 cases per km2 per year

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Interpretation

• Leap frog pattern
• Land use patterns
• Migration of vulnerable populations
• Tendency to under-estimate critical fraction
  within core and overestimate critical fraction in
  non-core areas

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Simulation modeling

• Use what we have learned about a disease to
  simulate its progression under different
  containment scenarios.
• http//www.nature.com/nature/journal/v437/n7056/su
  ppinfo/nature04017.html