Dynamic maps: a visual-analytic methodology for exploring spatio-temporal disease patterns.

Area of Science:

• Public Health
• Epidemiology
• Geographic Information Systems (GIS)

Background:

• Epidemiologic studies face challenges due to complex spatio-temporal human-environment interactions.
• Dynamic mapping offers a method to visualize simultaneous temporal and spatial information, aiding hypothesis generation.
• A conceptual framework for dynamic mapping principles and implementation was previously proposed.

Purpose of the Study:

• To depict the spatio-temporal dynamics of Salmonella infections in the U.S. elderly population.
• To utilize dynamic mapping for visualizing disease patterns in relation to environmental factors.

Main Methods:

• Employed dynamic mapping to visualize Salmonella infection spatio-temporal dynamics in U.S. elderly (2002).
• Utilized hospitalization data from the Centers for Medicare and Medicaid Services.
• Superimposed hospitalization rates onto maps of environmental factors (livestock density, temperature) and created a movie for temporal analysis.

Main Results:

• Dynamic maps identified spatio-temporal clusters of Salmonella infections, peaking in summer months, especially in the South.
• Infection peaks correlated with average temperatures exceeding 83.4°F (28.6°C).
• A strong synchronization was observed between high broiler chicken sales and dense case clusters during summer.

Conclusions:

• Dynamic mapping is a valuable visual-analytic tool for public health practitioners.
• This technique provides insights into disease origins, spread patterns (waves), seasonal outbreak timing, and cluster persistence.
• Demonstrates potential for understanding complex public health issues.