Spatio-temporal Analysis for New York State SPARCS Data.

Area of Science:

• Public Health
• Geospatial Analysis
• Health Informatics

Background:

• Accessible health data, like New York State's SPARCS data, offers opportunities to study disease patterns.
• SPARCS data includes patient demographics, diagnoses, services, charges, and home addresses for hospitalizations and visits.

Purpose of the Study:

• To perform spatial, temporal, and spatial-temporal analysis of disease patterns in New York State using SPARCS data.
• To analyze disease distribution at the ZIP code level and temporal trends over 12 years.
• To compare spatial variations of diseases with varying clustering tendencies and study their evolution.

Main Methods:

• Spatial analysis of disease distribution at the ZIP code level.
• Temporal analysis of common diseases using 12 years of historical data.
• Comparison of spatial variations for diseases with different clustering tendencies and analysis of pattern evolution.

Main Results:

• Identified spatial distribution patterns for typical diseases at the ZIP code level.
• Conducted temporal analysis of common diseases over a 12-year period.
• Demonstrated consistency of discovered spatial asthma clusters with prior studies through case studies.

Conclusions:

• Preliminary analysis reveals significant spatial and temporal disease patterns in New York State.
• Geospatial analysis of health data, like SPARCS, is valuable for public health surveillance.
• Visualizations, including animations, effectively communicate complex spatial-temporal disease patterns.