Research
Spatial prediction of Plasmodium falciparum prevalence in Somalia
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* Corresponding author: Abdisalan M Noor anoor@nairobi.kemri-wellcome.org
1 Malaria Public Health & Epidemiology Group, Centre for Geographic Medicine Research-Coast, Kenya Medical Research Institute/Wellcome Trust Research Programme, P.O. Box 43640, 00100 GPO, Nairobi, Kenya
2 Centre for Tropical Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK
3 School of Population Health, University of Queensland, Brisbane, Queensland, 4006, Australia
4 Centre for Geographic Health Research, School of Geography, University of Southampton, Southampton, SO17 1BJ, UK
5 United Nations Food and Agricultural Organization, Food Security Analysis Unit-Somalia, 3rd Floor, Kalson Towers, Parklands, P.O. Box 1230, Village Market, Nairobi, Kenya
6 United Nations Children's Fund, Somalia Support Centre, P.O. Box 44145, 00100, Nairobi, Kenya
7 Spatial Ecology and Epidemiology Group, Tinbergen building, Department of Zoology, University of Oxford, South Parks Road, Oxford, UK
Malaria Journal 2008, 7:159 doi:10.1186/1475-2875-7-159
Published: 21 August 2008Additional files
Additional File 1:
A method for identifying outliers. Statistical outliers were identified using a spatial filtering algorithm that implemented the following procedure in turn for each datum p(xi) at location xi.
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Additional File 2:
The Bayesian model form developed in WinBUGS without covariates. The univariate Bayesian geostatistical models
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Additional File 3:
Maps of north and south of Somalia.
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