Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project

Carlos A Guerra¹^,2 , Simon I Hay¹^,2 , Lorena S Lucioparedes¹ , Priscilla W Gikandi² , Andrew J Tatem¹^,2 , Abdisalan M Noor² and Robert W Snow²^,3

¹Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, Oxford, OX1 3PS, UK

²Malaria Public Health & Epidemiology Group, Centre for Geographic Medicine, KEMRI-Wellcome Trust-Collaborative Programme, Kenyatta National Hospital Grounds, P.O. Box 43640-00100 Nairobi, Kenya

³Centre for Tropical Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DS, UK

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Malaria Journal 2007, 6:17doi:10.1186/1475-2875-6-17


Published:	16 February 2007

Abstract

Background

Open access to databases of information generated by the research community can synergize individual efforts and are epitomized by the genome mapping projects. Open source models for outputs of scientific research funded by tax-payers and charities are becoming the norm. This has yet to be extended to malaria epidemiology and control.

Methods

The exhaustive searches and assembly process for a global database of malaria parasite prevalence as part of the Malaria Atlas Project (MAP) are described. The different data sources visited and how productive these were in terms of availability of parasite rate (PR) data are presented, followed by a description of the methods used to assemble a relational database and an associated geographic information system. The challenges facing spatial data assembly from varied sources are described in an effort to help inform similar future applications.

Results

At the time of writing, the MAP database held 3,351 spatially independent PR estimates from community surveys conducted since 1985. These include 3,036 Plasmodium falciparum and 1,347 Plasmodium vivax estimates in 74 countries derived from 671 primary sources. More than half of these data represent malaria prevalence after the year 2000.

Conclusion

This database will help refine maps of the global spatial limits of malaria and be the foundation for the development of global malaria endemicity models as part of MAP. A widespread application of these maps is envisaged. The data compiled and the products generated by MAP are planned to be released in June 2009 to facilitate a more informed approach to global malaria control.