Building a Malaria Intelligence System for Real-Time Prediction and Data-Driven Intervention Planning

Unlabelled: Sub-Saharan Africa continues to face the highest malaria burden worldwide, accounting for 95% of malaria cases and deaths according to the World Health Organization. In this News and Perspectives article, JMIR Correspondent Sharon Muzaki reports on a new artificial intelligence system in sub-Saharan Africa that could help improve public health responses to the disease.

Authors

Publication Details

Journal
Journal of Medical Internet Research
Published
2026-06-30
DOI
https://doi.org/10.2196/105472
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Building a Malaria Intelligence System for Real-Time Prediction and Data-Driven Intervention Planning

Sharon Muzaki
Journal of Medical Internet Research
Malaria Research and Control
article

Building a Malaria Intelligence System for Real-Time Prediction and Data-Driven Intervention Planning

Sharon Muzaki
article en

Abstract

Unlabelled: Sub-Saharan Africa continues to face the highest malaria burden worldwide, accounting for 95% of malaria cases and deaths according to the World Health Organization. In this News and Perspectives article, JMIR Correspondent Sharon Muzaki reports on a new artificial intelligence system in sub-Saharan Africa that could help improve public health responses to the disease.

Journal of Medical Internet ResearchVol. 28
Good health and well-being
Openalex Percentile: Top 6%
Malaria Research and Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.