Last Updated: 13/02/2025
Mapping the risks of Plasmodium falciparum infections in areas of low transmission intensity
Objectives
- To model malaria risk using monthly health facility data on parasitologically confirmed malaria cases among fever patients by applying novel space-time mode-based geostatistics.
- To develop new mode-based geostatistical approaches to integrate the varying spatial and temporal properties of data on P. falciparum parasite prevalence among individuals of all ages seen during community surveys and the number of febrile patients seen at public health facilities.
- To undertake a series of nested studies to enhance the understanding of the malaria epidemiology in areas of low transmission intensity that aim to inform approaches to high-resolution malaria risk mapping.
Kenya Medical Research Institute (KEMRI)
University of Oxford, United Kingdom
Malaria risk maps are fundamental to the selection of intervention tools, estimating disease burden, targeting resources and monitoring progress on the control-to-elimination path. The prevalence of Plasmodium falciparum parasite infections from community surveys has been the main metric used to map malaria risk. At low transmission, measuring prevalence requires massive sampling effort and community-based cross-sectional surveys often have low spatial sensitivity and lack adequate temporal information on risk. In low transmission areas, different metrics and modelling approaches are required. The number of infections presenting to health facilities may be a more sensitive indicator of malaria risk under low transmission where infections are more likely to lead to clinical disease and the data can be assembled temporally. For low transmission countries, these data represent a valuable source of information. However, the data from health facilities are often incomplete in time and not all facilities report.
Jun 2011 — May 2016
Related Resources
