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ABSTRACT: Background
Surprisingly little is known about the geographical overlap between malaria and other tropical diseases, including helminth infections. This is despite the potential public health importance of co-infection and synergistic opportunities for control.Methods
Statistical models are presented that predict the large-scale distribution of hookworm in sub-Saharan Africa (SSA), based on the relationship between prevalence of infection among schoolchildren and remotely sensed environmental variables. Using a climate-based spatial model of the transmission potential for Plasmodium falciparum malaria, adjusted for urbanization, the spatial congruence of populations at coincident risk of infection is determined.Results
The model of hookworm indicates that the infection is widespread throughout Africa and that, of the 179.3 million school-aged children who live on the continent, 50.0 (95% CI: 48.9-51.1) million (27.9% of total population) are infected with hookworm and 45.1 (95% CI: 43.9-46) million are estimated to be at risk of coincident infection.Conclusion
Malaria and hookworm infection are widespread throughout SSA and over a quarter of school-aged children in sub-Saharan Africa appear to be at risk of coincident infection and thus at enhanced risk of clinical disease. The results suggest that the control of parasitic helminths and of malaria in school children could be viewed as essential co-contributors to promoting the health of schoolchildren.
SUBMITTER: Brooker S
PROVIDER: S-EPMC1635726 | biostudies-literature | 2006 Nov
REPOSITORIES: biostudies-literature
Brooker Simon S Clements Archie C A AC Hotez Peter J PJ Hay Simon I SI Tatem Andrew J AJ Bundy Donald A P DA Snow Robert W RW
Malaria journal 20061103
<h4>Background</h4>Surprisingly little is known about the geographical overlap between malaria and other tropical diseases, including helminth infections. This is despite the potential public health importance of co-infection and synergistic opportunities for control.<h4>Methods</h4>Statistical models are presented that predict the large-scale distribution of hookworm in sub-Saharan Africa (SSA), based on the relationship between prevalence of infection among schoolchildren and remotely sensed e ...[more]