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A high resolution spatial population database of Somalia for disease risk mapping

Abstract:

Background: Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data.

Results: Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simpled and semi-automated methods that can be implemented with free image processing software to produced an easily updatable gridded population dataset at 100 x 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach.

Conclusions: The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/1476-072X-9-45

Authors

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Institution:
"University of Oxford", "Université Libre de Bruxelles, Belgium"
Research group:
Spatial Ecology and Epidemiology Group
Department:
Biological Control and Spatial Ecology
Role:
Author
More by this author
Institution:
"Centre for Geographic Medicine, KEMRI - University of Oxford - Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds, Nairobi, Kenya"
Department:
Malaria Public Health and Epidemiology Group
Role:
Author
More by this author
Institution:
"Centre for Geographic Medicine, KEMRI - University of Oxford - Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds, Nairobi, Kenya", "University of Oxford"
Department:
Medical Sciences Division - Clinical Vaccinology and Tropical Medicine,Centre for (CCVTM)
Role:
Author
More by this author
Institution:
"Centre for Geographic Medicine, KEMRI - University of Oxford - Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds, Nairobi, Kenya", "University of Oxford"
Department:
Medical Sciences Division - Clinical Vaccinology and Tropical Medicine,Centre for (CCVTM)
Role:
Author
More by this author
Institution:
"University of Florida", "Fogarty International Center, National Institutes of Health, Bethesda, MD, USA"
Department:
Emerging Pathogens Institute
Role:
Author


Publisher:
BioMed Central
Journal:
International Journal of Health Geographics More from this journal
Volume:
9
Article number:
45
Publication date:
2010-09-01
Edition:
Publisher's version
DOI:
ISSN:
1476-072X


Language:
English
Keywords:
Subjects:
UUID:
uuid:0c59be6d-ab30-451a-9dc7-89b75997aa3e
Local pid:
ora:5694
Deposit date:
2011-09-12
ARK identifier:

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