Forecasting, warning, and detection of malaria epidemics: a case study
The Lancet·
- DOI
- 10.1016/s0140-6736(03)13366-1
- PMID
- 12767739
- PMCID
- PMC3164796
- OpenAlex
- W1999919705
- Study type
- Journal article
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The authors describe malaria preparedness in the highlands as potentially improved through planning for expected annual resurgent outbreaks together with a simple nationwide early-warning approach.
Structured evidence summary
Research question
The article assessed whether seasonal climate forecasts, meteorological monitoring, and early case detection might have supported prevention of the 2002 malaria emergency in Kenya's western highlands.
Study design
This was a malaria epidemic case study using seasonal climate information, rainfall monitoring, and outpatient surveillance to evaluate warning and detection performance.
Population and setting
The setting was the highlands of western Kenya, including Kisii Central, Gucha, Nandi, and Kericho, in the context of the 2002 malaria emergency.
Main findings
The seasonal forecasts did not predict the unusually heavy rainfall. Rainfall measurements provided timely and reliable warnings, whereas monthly outpatient malaria surveillance did not provide an effective early alarm. The abstract associates normal rainfall with recurrent outbreaks in Kisii Central and Gucha and exceptional rainfall with malaria epidemics in Nandi and Kericho.
Public-health relevance
The authors describe malaria preparedness in the highlands as potentially improved through planning for expected annual resurgent outbreaks together with a simple nationwide early-warning approach.
Important limitations
The supplied abstract does not provide detailed methods, population counts, analytic procedures, or quantitative estimates, so the findings cannot be fully assessed for decision-grade interpretation. This summary is limited to the supplied single-article abstract and metadata and requires the original paper for fuller appraisal.
GIDS interpretation
The article is discoverable in the supplied metadata as a Kenya-focused malaria study concerning climate and environmental factors, outbreak investigation, and surveillance. It provides historical context about warning and detection approaches but does not establish or confirm any current surveillance signal.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 7 auditable classifier relationships to diseases, places, topics, and study design.