使用数字年度家庭调查数据来优先确定高风险村庄的结核病例
Hamid Abdullah1, Hemant Deepak Shewade2, Manickam Ponnaiah3
1Khushi Baby, 123 Kharol Colony, Gali No. 5, Fatehpura, Udaipur, Rajasthan 313001, India.
Transactions of the Royal Society of Tropical Medicine and Hygiene
|September 5, 2025
概括
这项研究表明,数字健康调查数据可以识别高风险村庄的结核病例. 针对拉贾斯坦邦的这些地区可以改善缺失结核病例的检测.
科学领域:
- 公共卫生
- 流行病学
- 卫生信息学
背景情况:
- 结核病 (TB) 活跃病例查找 (ACF) 对于发现遗漏病例至关重要,特别是在印度拉贾斯坦邦等高发病率地区.
- 现有的数字健康调查数据为加强ACF战略提供了潜在的资源.
- 针对高风险人口和村庄可以优化对结核病控制的资源分配.
研究的目的:
- 评估数字年度健康调查数据的实用性, 以确定拉贾斯坦邦结核病ACF的高风险村庄.
- 确定拉贾斯坦邦村庄的主要风险因素 (贫困,社会边缘化,地理位置) 的普遍性.
主要方法:
- 这项生态研究使用了拉贾斯坦邦19个地区的数字年度健康调查数据.
- 高风险村庄的定义是多维贫困指数 (MDPI) >0.21,社会边缘化人口>60%,或距离初级卫生中心>7公里.
- 分析了20803个村庄2460万个人的数据.
主要成果:
- 大约34%的村庄至少表现出一种已确定的结核病高风险因素.
- 9%的村庄报告高贫困率 (MDPI>0.21),25%的人口处于社会边缘.
- 35%的受访者属于社会边缘化群体,39%的家庭使用固体燃料.
结论:
- 数字年度健康调查数据可以有效地用于针对性结核病例的发现.
- 这项研究强调了利用现有数据基础设施确定结核病干预高风险地区的可行性.
- 建议进行进一步的研究,以评估特定村庄的ACF产量,并促进其他地区的数据驱动策略.
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