Mobile Health Apps for Malaria Early Detection among Female Livestock Keepers in Western Kenya: Adoption and Efficiency Evaluation

Mobile health apps have been increasingly used in various settings to improve disease detection and management, including malaria early detection among livestock keepers. A comprehensive search strategy was employed to identify relevant studies, with data extraction and assessment using predefined criteria. Mobile health apps showed an average adoption rate of 45% among female livestock keepers, with a significant proportion (32%) reporting improved operational efficiency compared to traditional methods. The findings suggest that mobile health apps can be effective tools for early malaria detection in this population, warranting further research and implementation strategies. Healthcare providers should consider integrating these apps into their surveillance systems, with specific attention to user education and app customization for local contexts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.