Strengthening health information systems and inherent statistical outputs for improved malaria control and interventions in western Kenya.

Frontiers in epidemiology Pub Date : 2025-06-19 eCollection Date: 2025-01-01 DOI:10.3389/fepid.2025.1591261
Taliyah Griffin, Felix Pabon-Rodriguez, George Ayodo, Yan Zhuang
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Abstract

Malaria control efforts in Kenya face persistent challenges due to fragmented health information systems, despite notable digital innovations. This mini review evaluates implementations in western Kenya, contrasting successes like Siaya County's Electronic Community Health Information System (eCHIS), developed through collaborations between the Ministry of Health, local agencies, and frontline health workers, which reduces reporting delays through real-time mobile data collection, with ongoing struggles including paper-based records in health facilities and unreliable rural internet. We document how analytical methods, when properly supported, can transform surveillance. Methods such as spatiotemporal models using climate and case data can improve outbreak predictions, while machine learning techniques can optimize insecticide-treated bed net distributions by pinpointing high-risk households. However, these analytical tools remain underutilized due to data fragmentation and limited technical capacity. Key implementation challenges emerged, including device charging difficulties for community health workers, inconsistent data standards between systems, and privacy concerns under Kenya's new Digital Health Act that policymakers are currently addressing through revised guidelines. Key recommendations from this review include the expansion of digital health platforms with co-design input from end-users, improved data quality through standardized reporting mechanisms enforced by county health leadership, and the incorporation of predictive modeling to identify high-risk areas and optimize intervention timing. Investing in robust health information infrastructure will not only strengthen malaria control efforts in Kenya but also serve as a model for other malaria-endemic regions. Digital tools show tremendous potential when paired with sustained training, community engagement, and realistic maintenance solutions supported by public-private partnerships.

加强卫生信息系统和固有的统计产出,以改善肯尼亚西部的疟疾控制和干预措施。
尽管有显著的数字创新,但肯尼亚的疟疾控制工作由于卫生信息系统的碎片化而面临持续挑战。这项小型审查评估了肯尼亚西部的实施情况,对比了Siaya县的电子社区卫生信息系统(eCHIS)等成功案例,该系统是通过卫生部、地方机构和一线卫生工作者之间的合作开发的,通过实时移动数据收集减少了报告延误,但目前仍在挣扎,包括卫生设施的纸质记录和不可靠的农村互联网。我们记录了分析方法在得到适当支持的情况下如何改变监视。使用气候和病例数据的时空模型等方法可以改进疫情预测,而机器学习技术可以通过精确定位高风险家庭来优化杀虫剂处理过的蚊帐分配。然而,由于数据碎片化和技术能力有限,这些分析工具仍未得到充分利用。关键的实施挑战出现了,包括社区卫生工作者的设备充电困难,系统之间不一致的数据标准,以及肯尼亚新的《数字卫生法》下的隐私问题,政策制定者目前正在通过修订的指导方针解决这些问题。本次审查提出的主要建议包括:利用最终用户的共同设计投入扩大数字卫生平台,通过县卫生领导实施的标准化报告机制提高数据质量,以及纳入预测建模以识别高风险地区并优化干预时机。投资于健全的卫生信息基础设施不仅将加强肯尼亚的疟疾控制工作,而且还将成为其他疟疾流行地区的榜样。数字工具与持续的培训、社区参与以及由公私伙伴关系支持的现实维护解决方案相结合,显示出巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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