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Small Area Estimation of Under‑Five Mortality at 5 km Resolution – Covariate and Censoring Pipelines

Domaine:

healthcaregeospatial

Type de record:

dataset
Créateur:
Bay
Éditeur:
Zenodo
Hôte:avatar
This deposit contains two R Markdown scripts and derived covariate rasters for small area estimation of under‑five mortality in Ethiopia at 5 km resolution. The first script (censoring_adjustment.Rmd) loads 21 raw covariate rasters, selects 16 uncorrelated covariates, and adjusts DHS birth histories for informative censoring using Random Survival Forest (RSF) with external benchmark calibration (U5MR 55/1000). The second script (covariate_adjustment.Rmd) processes the 16 selected covariates for each year 2000‑2015 (log1p, z‑score, capping) and exports 5 km GeoTIFFs. A synthetic DHS dataset (synthetic_dhs.rds) is provided to test the censoring pipeline without restricted data. Example final INLA model outputs are included for 2000 and 2015. Full documentation is in the README.md file. The code is licensed under MIT.

Visit

doi.orgzenodo.org

Tags

small area estimation, under-five mortality, covariate selection, censoring adjustment, Random Survival Forest, INLA, data integration, multi-source data, climate data, environmental covariates, GBD, DHS, spatial analysis, 5 km resolution, rescaling, standardisation

Licenses

MIT Licensehttps://opensource.org/licenses/MITCopyright (c) 2026 Bayuh Asmamaw Hailuhttp://rightsstatements.org/vocab/InC/1.0/

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