MINI REVIEW article
Front. Epidemiol.
Sec. Infectious Disease Epidemiology
Volume 5 - 2025 | doi: 10.3389/fepid.2025.1591261
This article is part of the Research TopicInnovative Malaria Control Strategies: Success Stories from Diverse Global RegionsView all articles
Strengthening health information systems and inherent statistical outputs for improved malaria control and interventions in Western Kenya
Provisionally accepted- 1Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States
- 2Department of BioHealth Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Indianapolis, Indiana, United States
- 3Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya
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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.
Keywords: Malaria, statistical analysis, Health information system, sub-Saharan Africa, surveillance, Kenya
Received: 11 Mar 2025; Accepted: 03 Jun 2025.
Copyright: © 2025 Griffin, Pabón-Rodríguez, Ayodo and Zhuang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Félix Pabón-Rodríguez, Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States
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