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.

中文翻译：

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流行病学地理信息系统的应用：基于OMOP通用数据模型的开源空间分析工具

背景：空间流行病学用于评估健康结果的地理差异和差异。但是，构建地理统计模型需要耗费大量人力的流程，从而限制了整体效用。我们开发了用于空间流行病学分析的开源软件，并证明了其适用性和质量。方法：基于标准化的地理编码和观察健康数据，流行病学地理信息系统（AEGIS）的应用提供了两种空间分析方法：疾病制图和检测聚类的医疗状况和结果。AEGIS评估了韩国和美国的发病率和健康结局的地理分布，特别是癌症的发病率及其死亡率，流行性疟疾地区和心脏病（仅在美国）。结果：韩国AEGIS生成的事件癌症的空间分布与以前的报道一致。Moran's I最高的女性的肝癌发生率（0.44;p <0.001）为17.4（10.3-26.9）。在韩国坡州市发现了疟疾流行群（p <0.001）。将AEGIS应用于美国的数据库后，就可以正确识别出心脏病群（p <0.001）。结论：作为一种开源的，跨国的，空间分析解决方案，AEGIS可以通过使用标准化的地理编码和观察性健康数据库来全球评估健康结果的地理分布差异。