Spatial prediction of Plasmodium falciparum prevalence in Somalia

Noor, Abdisalan M., Clements, Archie C. A., Gething, Peter W., Moloney, Grainne, Borle, Mohammed, Shewchuk, Tanya, Hay, Simon I. and Snow, Robert W. (2008) Spatial prediction of Plasmodium falciparum prevalence in Somalia. Malaria Journal, 7 Article Number: 159. doi:10.1186/1475-2875-7-159

Author Noor, Abdisalan M.
Clements, Archie C. A.
Gething, Peter W.
Moloney, Grainne
Borle, Mohammed
Shewchuk, Tanya
Hay, Simon I.
Snow, Robert W.
Title Spatial prediction of Plasmodium falciparum prevalence in Somalia
Journal name Malaria Journal   Check publisher's open access policy
ISSN 1475-2875
Publication date 2008-08-21
Year available 2008
Sub-type Article (original research)
DOI 10.1186/1475-2875-7-159
Open Access Status DOI
Volume 7
Start page Article Number: 159
Total pages 13
Editor Marcel Hommel
Place of publication London, England
Publisher BioMed Central Ltd.
Language eng
Subject C1
920109 Infectious Diseases
110803 Medical Parasitology
Formatted abstract
Background: Maps of malaria distribution are vital for optimal allocation of resources for anti-malarial activities. There is a lack of reliable contemporary malaria maps in endemic countries in sub-Saharan Africa. This problem is particularly acute in low malaria transmission countries such as those located in the horn of Africa.

Methods: Data from a national malaria cluster sample survey in 2005 and routine cluster surveys in 2007 were assembled for Somalia. Rapid diagnostic tests were used to examine the presence of Plasmodium falciparum parasites in finger-prick blood samples obtained from individuals across all age-groups. Bayesian geostatistical models, with environmental and survey covariates, were used to predict continuous maps of malaria prevalence across Somalia and to define the uncertainty associated with the predictions.

Results: For analyses the country was divided into north and south. In the north, the month of survey, distance to water, precipitation and temperature had no significant association with P. falciparum prevalence when spatial correlation was taken into account. In contrast, all the covariates, except distance to water, were significantly associated with parasite prevalence in the south. The inclusion of covariates improved model fit for the south but not for the north. Model precision was highest in the south. The majority of the country had a predicted prevalence of < 5%; areas with >= 5% prevalence were predominantly in the south.

: The maps showed that malaria transmission in Somalia varied from hypo- to meso-endemic. However, even after including the selected covariates in the model, there still remained a considerable amount of unexplained spatial variation in parasite prevalence, indicating effects of other factors not captured in the study. Nonetheless the maps presented here provide the best contemporary information on malaria prevalence in Somalia.
Q-Index Code C1
Q-Index Status Confirmed Code
Additional Notes © 2008 Noor et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Faculty of Health and Behavioural Sciences -- Publications
2009 Higher Education Research Data Collection
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Citation counts: TR Web of Science Citation Count  Cited 49 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 01 Apr 2009, 00:51:58 EST by Geraldine Fitzgerald on behalf of School of Public Health