Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Tinbergen Building, South Parks Road, Oxford, OX1 3PS, UK.
Int J Health Geogr. 2010 Sep 14;9:45. doi: 10.1186/1476-072X-9-45.
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 In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly.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.
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 simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 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.
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.
由于索马里政局不稳定，数以百万计的索马里人无法获得基本的医疗服务。目前正在努力重建卫生部门，特别是要评估传染病负担的程度。然而，任何需要使用模型疾病率的方法都需要关于人口分布的合理信息。在像索马里这样的低收入国家，人口数据缺乏、质量差或迅速过时。因此，需要建模方法来生成当代和空间详细的人口数据。
这里使用卫星图像和现有定居点数据集得出的土地覆盖信息来对普查单位内的人口进行空间重新分配。我们使用了简单和半自动的方法，可以使用免费的图像处理软件来生成易于更新的 100×100 米空间分辨率的网格化人口数据集。2010 年的人口数据集与联合国预测的行政人口总数相匹配。新数据集与现有人口数据集之间的比较测试显示，人口规模分布和疟疾风险人口估计存在重要差异。这些差异在人口更密集的地区尤为重要，并且强烈依赖于建模方法中使用的定居点数据。
结果表明，使用现有数据制作索马里详细、当代且易于更新的定居点和人口分布数据集是可行的。我们制作的 2010 年人口数据集是 AfriPop 项目的一个产品，可以从以下网址免费下载：http://www.afripop.org。
