Assessing the geographic and socioeconomic determinants of vaccine coverage in Ethiopia: A spatial and multistage analysis at the district level

Abstract

Background

Despite substantial progress over the past decades, many Ethiopian children still lack the full WHO-recommended immunization schedule. Notably, diphtheria-pertussis-tetanus-Hib-HepB and measles vaccines present large coverage disparities in Ethiopia. This study integrated routine, survey and census data from health, geographic and socioeconomic sources at the district level. We then explored associations between extracted covariates and coverage of measles (1st dose, MCV1) and diphtheria-pertussis-tetanus-Hib-HepB (3rd dose, Penta3). Lastly, we developed prediction models of immunization coverage.

Methods

We utilized multiple data sources, including district (known as woreda) immunization coverage estimates from the District Health Information Software (DHIS-2), Demographic and Health Surveys, demographic census, and public databases on electricity, administrative boundaries and health facility geolocations. We sought to develop parsimonious beta-regression models of immunization coverage using variable selection, so as to identify covariates with high predictive power. We then fitted and internally validated generalized additive models to predict MCV1 and Penta3 coverage.

Results

Our analysis identified access time to health centers, electrification levels, and woreda sizes as major factors associated with district-level immunization. Our prediction models estimated district-level MCV1 and Penta3 coverage with mean absolute errors of 11–12 %.

Conclusions

This study highlights the significant potential of geospatial models for public health policy and planning in low- and middle-income countries. By integrating diverse data sources and focusing on the district level, we provide a quantitative framework for identifying gaps in immunization coverage. The approach, using geographic and socio-economic data, can be effectively applied to a wide range of public health interventions.