Space-time visualization and analysis in the Cancer Atlas Viewer

Area of Science:

• Epidemiology
• Biostatistics
• Geographic Information Systems (GIS)

Background:

• Cancer mortality data analysis is crucial for public health.
• Spatio-temporal patterns in cancer rates require advanced visualization tools.
• Understanding cancer disparities necessitates examining demographic and geographic factors.

Purpose of the Study:

• To introduce the Cancer Atlas Viewer, a novel software for exploring US cancer mortality data.
• To demonstrate the software's utility by analyzing spatio-temporal patterns of colon cancer mortality.
• To compare the effectiveness of local Moran and local G* cluster statistics in identifying cancer hotspots.

Main Methods:

• Utilized the Cancer Atlas Viewer software for data exploration.
• Analyzed colon cancer mortality rates for African-American and white populations (females and males) in the southeastern US (1970-1995).
• Applied and compared local Moran and local G* cluster statistics to identify spatial clusters.

Main Results:

• The Cancer Atlas Viewer successfully visualized spatio-temporal cancer mortality patterns.
• Both local Moran and local G* statistics identified similar patterns, with some discrepancies highlighting unique data insights.
• Identified two persistent clusters of low colon cancer mortality in the study region.

Conclusions:

• The Cancer Atlas Viewer is an effective tool for cancer data exploration.
• Cluster statistics can reveal significant spatial patterns in cancer mortality.
• The identified low-mortality clusters warrant further investigation into underlying protective factors.