ReviewFrontiers in epidemiology2025
Strengthening health information systems and inherent statistical outputs for improved malaria control and interventions in western Kenya.
Review in Frontiers in epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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