Literature DB >> 29484673

The DHS Program's Modeled Surfaces Spatial Datasets.

Clara R Burgert-Brucker, Trinadh Dontamsetti, Peter W Gething.   

Abstract

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.
© 2018 The Population Council, Inc.

Mesh:

Year:  2018        PMID: 29484673     DOI: 10.1111/sifp.12050

Source DB:  PubMed          Journal:  Stud Fam Plann        ISSN: 0039-3665


  4 in total

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Review 2.  Analyses of inequalities in RMNCH: rising to the challenge of the SDGs.

Authors:  Cesar Victora; Ties Boerma; Jennifer Requejo; Marilia Arndt Mesenburg; Gary Joseph; Janaína Calu Costa; Luis Paulo Vidaletti; Leonardo Zanini Ferreira; Ahmad Reza Hosseinpoor; Aluisio J D Barros
Journal:  BMJ Glob Health       Date:  2019-06-24

3.  Subnational estimates of factors associated with under-five mortality in Kenya: a spatio-temporal analysis, 1993-2014.

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Journal:  BMJ Glob Health       Date:  2021-04

4.  A vulnerability index for COVID-19: spatial analysis at the subnational level in Kenya.

Authors:  Peter M Macharia; Noel K Joseph; Emelda A Okiro
Journal:  BMJ Glob Health       Date:  2020-08
  4 in total

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