Mapping malaria transmission intensity using geographical information systems (GIS): an example from Kenya

Area of Science:

• Epidemiology
• Geographic Information Systems (GIS)
• Malariology

Background:

• Limited use of epidemiological maps in malaria control due to data and understanding gaps.
• Clinical outcomes of Plasmodium falciparum infection correlate with parasite exposure intensity.
• Geographical Information Systems (GIS) offer advanced methods for spatial epidemiological data representation.

Purpose of the Study:

• To spatially define and estimate Plasmodium falciparum infection risks among Kenyan children.
• To utilize parasitological, geographical, demographic, and climatic data within a GIS platform.
• To provide a rational basis for future malaria control strategies in Kenya.

Main Methods:

• Abstraction and spatial definition of parasitological data from 682 cross-sectional surveys in Kenya.
• Integration of parasitological, geographical, demographic, and climatic data into a GIS platform.
• Estimation of malaria transmission intensity (low, moderate, high) for defined populations.

Main Results:

• Malaria infection risks were estimated for millions of Kenyan children: low for 2.9 million, stable low for 1.3 million, moderate for 3.0 million, and high for 0.8 million.
• Parasitological markers of malaria endemicity showed relative stability across diverse data sources and timeframes.
• The study successfully mapped malaria transmission intensity across broad categories.

Conclusions:

• Spatially defined epidemiological data, when integrated with GIS, can effectively map malaria transmission intensity.
• Understanding the relationship between parasite exposure, ecological factors, and disease outcomes is crucial for effective malaria control.
• This approach provides a foundation for more rational and targeted malaria control interventions in Kenya.