Spatial small area estimates of undernutrition for under five children in Ethiopia via combining survey and census data

ElsevierVolume 42, August 2022, 100509Spatial and Spatio-temporal EpidemiologyHighlights•

The coefficient of variation and root mean square errors of the spatial small area estimates are smaller than the coefficients of variation and root mean square errors of the direct survey estimates and the common small area estimates.

Spatial small area estimations are the most precise and reliable estimates compared to the direct survey estimates and the common small area estimates.

Spatial small area estimation using the Fay-Herriot model improved the direct survey estimates much further.

The inclusion of simultaneous autoregressive (SAR) spatial components to frequently used small area models is critical for enhancing direct survey estimates.

Abstract

A survey is typically designed to produce reliable estimates of target variables of the population at national and regional levels. For unplanned zones with small sample sizes, reliable estimates are needed in many ways. Because of the small sample sizes, direct survey estimates for unplanned zones are unreliable. This paper aims to improve the precision of estimates of undernutrition at zonal levels using small area estimation under the spatial Fay-Herriot (FH) model. Diagnostic measures are used to determine the reliability of spatial FH model assumptions and model-based spatial estimates. According to the results, model-based small area estimates under spatial association had higher precision than direct estimates and FH models that ignored spatial information. The spatial small area estimates of undernutrition were unevenly distributed across Ethiopian zones. Undernutrition estimates for children under five at the zonal level can be helpful for resource allocation, policymakers, and planners.

Keywords

Spatial FH model

Census

Survey

Zones

Simultaneous autoregressive

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