Abstract
Background: Spatial epidemiology is used to evaluate geographical variations and disparities in health outcomes; however, constructing geographic statistical models requires a labor-intensive process that limits the overall utility. We developed an open-source software for spatial epidemiological analysis and demonstrated its applicability and quality. Methods: Based on standardized geocode and observational health data, the Application of Epidemiological Geographic Information System (AEGIS) provides two spatial analysis methods: disease mapping and detecting clustered medical conditions and outcomes. The AEGIS assesses the geographical distribution of incidences and health outcomes in Korea and the United States, specifically incidence of cancers and their mortality rates, endemic malarial areas, and heart diseases (only the United States). Results: The AEGIS-generated spatial distribution of incident cancer in Korea was consistent with previous reports. The incidence of liver cancer in women with the highest Moran’s I (0.44; p < 0.001) was 17.4 (10.3–26.9). The malarial endemic cluster was identified in Paju-si, Korea (p < 0.001). When the AEGIS was applied to the database of the United States, a heart disease cluster was appropriately identified (p < 0.001). Conclusions: As an open-source, cross-country, spatial analytics solution, AEGIS may globally assess the differences in geographical distribution of health outcomes through the use of standardized geocode and observational health databases.
Highlights
A comprehensive understanding of the geospatial patterns of the incidence and outcomes of medical conditions is important for establishing hypotheses to identify disease-related factors or for planning to improve public health [1,2]
Application of Epidemiological Geographic Information System (AEGIS), an interactive spatial analytical solution based on OMOP-Common Data Model (CDM) version 5 and Global Administrative Areas (GADM), allows the following functions: (1) data preprocessing to prepare epidemiological analysis, including linking medical data with geographic information system (GIS) data; (2) disease mapping function to visualize patterns of regional differences in medical events; and (3) a disease-clustering function to distinguish the geographic area where adverse outcomes occur more than expected among a group of people defined over a specific time period
The AEGIS graphical user interface is classified into four functional panels
Summary
A comprehensive understanding of the geospatial patterns of the incidence and outcomes of medical conditions is important for establishing hypotheses to identify disease-related factors or for planning to improve public health [1,2]. We developed an open-source software for spatial epidemiological analysis and demonstrated its applicability and quality. Methods: Based on standardized geocode and observational health data, the Application of Epidemiological Geographic. Information System (AEGIS) provides two spatial analysis methods: disease mapping and detecting clustered medical conditions and outcomes. The AEGIS assesses the geographical distribution of incidences and health outcomes in Korea and the United States, incidence of cancers and their mortality rates, endemic malarial areas, and heart diseases (only the United States). Results: The AEGIS-generated spatial distribution of incident cancer in Korea was consistent with previous reports. The incidence of liver cancer in women with the highest Moran’s I (0.44; p < 0.001) was 17.4
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