J A Omumbo1, R W Snow. 1. Public Health Group, KEMRI/Wellcome Trust Collaborative Programme PO. Box 43640, 00100 GPO, Nairobi, Kenya.
Abstract
OBJECTIVES: Empirical data on malaria endemicity are rarely available for public domain use to guide effective malaria control. This paper describes the work carried in East Africa since 1997 as part of a pan-African collaboration to map the risk of malaria, Mapping Malaria Risk in Africa (MARA) aimed at redressing deficiency. DATA EXTRACTION: Studies of cross-sectional community estimates of Plasmodium falciparum prevalence among children aged 0-15 years were identified from a variety of sources including electronic searches of published material, manual review of pre-electronic peer reviewed journals and searches of libraries and archives in Kenya, Tanzania and Uganda. Each survey source, infection prevalence, date, longitude and latitude and survey characteristics were recorded. DATA SYNTHESIS: All data were subjected to a number of selection criteria including minimum sample sizes, samples randomly selected, community-based surveys, age ranges of sampled communities within 0-15 years, and surveys that were spatially unique. Of the 2,003 survey data points identified since 1907 in East Africa, only 503 were eligible for inclusion in the analysis dating from 1927 to 2003. The spatial plots of the data demonstrate the paucity of information on malaria prevalence from a number of densely populated areas and highlight the concentration of empirical data in concert with research centres in the sub-region. CONCLUSIONS: Models are required to define malaria risk in areas of East Africa where no empirical data are available so that limited resources can be better targeted to those in greatest need.
OBJECTIVES: Empirical data on malaria endemicity are rarely available for public domain use to guide effective malaria control. This paper describes the work carried in East Africa since 1997 as part of a pan-African collaboration to map the risk of malaria, Mapping Malaria Risk in Africa (MARA) aimed at redressing deficiency. DATA EXTRACTION: Studies of cross-sectional community estimates of Plasmodium falciparum prevalence among children aged 0-15 years were identified from a variety of sources including electronic searches of published material, manual review of pre-electronic peer reviewed journals and searches of libraries and archives in Kenya, Tanzania and Uganda. Each survey source, infection prevalence, date, longitude and latitude and survey characteristics were recorded. DATA SYNTHESIS: All data were subjected to a number of selection criteria including minimum sample sizes, samples randomly selected, community-based surveys, age ranges of sampled communities within 0-15 years, and surveys that were spatially unique. Of the 2,003 survey data points identified since 1907 in East Africa, only 503 were eligible for inclusion in the analysis dating from 1927 to 2003. The spatial plots of the data demonstrate the paucity of information on malaria prevalence from a number of densely populated areas and highlight the concentration of empirical data in concert with research centres in the sub-region. CONCLUSIONS: Models are required to define malaria risk in areas of East Africa where no empirical data are available so that limited resources can be better targeted to those in greatest need.
Authors: Alexander K Rowe; Samantha Y Rowe; Robert W Snow; Eline L Korenromp; Joanna Rm Armstrong Schellenberg; Claudia Stein; Bernard L Nahlen; Jennifer Bryce; Robert E Black; Richard W Steketee Journal: Int J Epidemiol Date: 2006-02-28 Impact factor: 7.196
Authors: Abdisalan M Noor; Peter W Gething; Victor A Alegana; Anand P Patil; Simon I Hay; Eric Muchiri; Elizabeth Juma; Robert W Snow Journal: BMC Infect Dis Date: 2009-11-20 Impact factor: 3.090