Spatial filtering using a raster geographic information system: methods for scaling health and environmental data

Area of Science:

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

Background:

• Geographic Information Systems (GIS) are underutilized in public health practice despite their academic use.
• Methodological complexities in analyzing health-environment relationships, disease spatial variation, and healthcare access hinder GIS adoption in public health.
• There is a need for accessible GIS methods for public health officials.

Purpose of the Study:

• To demonstrate simple spatial filtering techniques for analyzing health and environmental data using raster GIS.
• To illustrate how spatial analysis can improve the understanding of health and environmental issues.
• To address the gap in practical GIS application for public health decision-making.

Main Methods:

• Utilized raster GIS for spatial analysis of health and environmental data.
• Applied spatial moving average rates to smooth individual variations and create continuous phenomenon surfaces.
• Computed exposure status surfaces incorporating neighbor influences weighted by distance decay.

Main Results:

• Spatial filtering methods effectively scale health and environmental data for better problem analysis.
• Demonstrated the practical application of spatial moving averages and exposure status surfaces.
• Successfully applied these methods to health and population surveillance data in Matlab, Bangladesh.

Conclusions:

• Simple spatial filtering methods in GIS can enhance the analysis of health and environmental data for public health.
• These techniques offer practical solutions to overcome methodological barriers in applying GIS to public health.
• The demonstrated methods provide a scalable approach for addressing health problems using spatial data.