Last Updated: 13/02/2025
Defining hotspots of malaria transmission
Objectives
Malaria transmission is patchy at a local level, with hotspots of intense transmission. This hinders control measures, but also means that targeting additional interventions on hotspots will be highly effective. At present, we do not know how best to detect these hotspots, or how to apply the interventions available. For example, we need to know how much transmission in the surrounding area results from the hotspot, and how focal the point source is.
This project will analyse 19 years of historical data on malaria from coastal Kenya, supplemented by data from the Gambia in West Africa, to determine the spatial patterns of hotspots and how they might be detected. The findings will be extended by collaborations with investigators collecting spatial data on malaria cases in Gambia, Indonesia and elsewhere in Africa.
In collaboration with Dominic Kwiatkowski in the Wellcome Trust Sanger Institute, detailed genotyping studies will be conducted to assign a bar-code to malaria parasites. This will allow to distinguish the recent origin of malaria parasites isolated in the field, in order to inform the design of targeted interventions against hotspots.
Malaria transmission is spatially heterogeneous, and groups of homesteads that form hotspots or clusters of transmission can be identified. The presence of these hotspots makes malaria control measures less effective than they might be. However, adding targeted interventions to interrupt these hotspots will be highly effective.
At present, we lack detailed epidemiological descriptions of the properties of hotspots and the ways in which they might be identified by malaria control programmes. Furthermore, in order to rationally design targeted interventions, we need to understand their transmission dynamics. For example, we need to know how much transmission in the surrounding area results from the hotspot, and how focal the point source is.
I will analyse 19 years of historical data on severe malaria, mild malaria and asymptomatic infection in Kilifi, Kenya. I will use datasets from cohorts under active surveillance in the field, and passive dispensary and hospital level surveillance, to describe the spatial and temporal limits of individual clusters of transmission, and the epidemiological markers of them. I will obtain external validation of my findings by collaborations with investigators collecting spatial data on malaria cases in Africa, including the Gambia and Indonesia.
Jan 2012 — Jun 2017
$1.86M
Related Resources
