ReviewAnnals of medicine and surgery (2012)2025
Artificial intelligence in African malaria control programs: opportunities and risks.
Review in Annals of medicine and surgery (2012), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Artificial intelligence for precision malaria control: transforming surveillance, prediction, and intervention strategies.Frontiers in digital health · 2026Review
- Circulating Tumor DNA in Breast Cancer: A Liquid Biopsy Revolution for Non-Invasive Genomic Profiling and Clinical Decision-Making.Breast cancer : basic and clinical research · 2026Review
- Hematologic Glyco-Signatures: Emerging Blood-Based Sugar Codes Linked to Hyper-Aggressive Breast Cancer.Breast cancer (Dove Medical Press) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malaria remains a major public health challenge in Sub-Saharan Africa, contributing to significant morbidity and mortality despite decades of control efforts. Conventional interventions - including vector control, chemoprevention, and diagnostics - face limitations due to drug and insecticide resistance, climate variability, and health system constraints. Artificial intelligence (AI) offers transformative potential to strengthen malaria control programs by enhancing surveillance, predicting outbreaks, improving diagnostics, optimizing treatment, and guiding resource allocation. This narrative review synthesizes current applications of AI in African malaria programs, highlighting case studies such as Kenya's drone-assisted vector surveillance, Nigeria's mobile health platforms for real-time case reporting, and Tanzania's climate-informed forecasting models. We further discuss AI-driven bioinformatics for
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.