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The DHS Program's Modeled Surfaces Spatial Datasets
Author(s) -
BurgertBrucker Clara R.,
Dontamsetti Trinadh,
Gething Peter W.
Publication year - 2018
Publication title -
studies in family planning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 68
eISSN - 1728-4465
pISSN - 0039-3665
DOI - 10.1111/sifp.12050
Subject(s) - operationalization , geospatial analysis , population , spatial analysis , computer science , raster graphics , sanitation , geography , statistics , cartography , data mining , environmental science , remote sensing , mathematics , artificial intelligence , environmental health , philosophy , epistemology , medicine , environmental engineering
Spatially interpolated map surface datasets for key development indicators are being produced and publicly shared using population-based surveys from the USAID-funded Demographic and Health Survey (DHS) Program. Each modeled surface is produced with standardized geostatistical modeling methods. For each indicator, a package is available that includes spatial raster grids of 5 × 5 km pixels for the point estimate surface and an uncertainty surface, along with validation statistics and other model diagnostic data. The maps are publicly available for download on the DHS Program Spatial Data Repository at http://spatialdata.dhsprogram.com/. The modeled surfaces are produced with publicly available geo-referenced data on each indicator as collected by the DHS Program, augmented with other relevant spatial data sources that act as covariates. A Bayesian model-based geostatistical (MBG) approach is used to generate the modeled surfaces. Spatially modeled surfaces can be used to support and improve decision-making at multiple levels within many development programs including health, population, family planning, nutrition, and water and sanitation. The modeled surfaces can be used in their original 5 × 5 km pixel format, operationalized to other geographic areas as relevant for the program, or linked to DHS or other survey data for additional analysis.