整合DHIS2和R以加强黎巴嫩的霍乱监测:关于改善数据质量的案例研究
Abass Toufic Jouny1,2, Hawraa Sweidan1,2, Maryo Baakliny1
1Epidemiological Surveillance Program, Ministry of Public Health, Ras En Nabaa, Beirut 1107, Lebanon.
International journal of environmental research and public health
|November 27, 2025
概括
自动化的R脚本显著提高了黎巴嫩的数据质量.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 黎巴嫩在2022-2023年经历了严重的霍乱疫情.
- 通过区卫生信息系统2 (DHIS2) 收集常规监测数据,面临完整性和准确性的挑战.
研究的目的:
- 提高霍乱监测数据的质量和实用性,使用自动化的R脚本.
- 为了提高数据的完整性,病例分类,地理准确性和实验室结果的文档.
主要方法:
- 开发并实施R脚本,用于在DHIS2中自动清理,标准化和重新分类数据.
- 使用R进行空间分析生成了流行病曲线和发病率图.
- 在GitHub上共享R脚本,以便开放访问和适应.
主要成果:
- 数据完整性从高缺失率 (高达99.7%) 提高到关键变量完全完整.
- 案件分类的准确性在重新分类后得到了改善.
- 实现了更好的霍乱发病率的空间分析和快速诊断测试覆盖范围.
- 在报告案例中发现了与居住地点相比的位置差异.
结论:
- 将基于R的分析与DHIS2集成,显著提高了霍乱监测数据的质量.
- 这种方法提供了更清晰的流行病学图景,支持公共卫生决策.
- 强调将分析工具与常规健康监测系统相结合的价值.
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