2024 NDHS: COVID-19 Vaccine Uptake Among Nigerian Women

The 2024 Nigeria Demographic and Health Survey (NDHS) provides a nationally representative dataset of 36,161 women aged 15–49, harmonized for machine learning analysis. It contains 43 variables on socio-demographics, health access, media exposure, and COVID-19 knowledge, with a binary outcome for vaccine uptake. The data includes sampling weights and engineered features to support predictive modeling of health behavior.

Use Cases

• Training binary classification models to predict vaccine uptake based on socio-demographic and behavioral factors.
• Analyzing the association between media exposure and health outcomes among women of reproductive age.
• Investigating regional disparities in health service access using the stratified cluster sampling design.
• Conducting feature importance analysis on engineered variables like education and family size transformations.

Strengths

• Contains 36,161 observations, providing a substantial sample size for analysis.
• Incorporates sampling weights (variable `wgt`) to ensure national representativeness across Nigeria's geopolitical regions.
• Includes 43 curated variables, with preprocessing and feature engineering (e.g., `EduHusbTrans`) specifically for machine learning.

Limitations

• Column names are not explicitly listed in the provided metadata, limiting precise feature understanding.
• The dataset is derived from a single survey year (2024), offering a cross-sectional rather than longitudinal view.
• Data preprocessing involved exclusion and imputation, which may introduce bias not fully detailed.

Provenance

Source

2024 Nigeria Demographic and Health Survey (NDHS), curated by Aklilu Habte Hailegebireal.

Collection Method

Two-stage stratified cluster sampling design, with data extraction, harmonization, and preprocessing for a specific research study.

Time Range

2024

Freshness

Last updated on 2026-03 18.

Geography

Nationally representative across Nigeria's geopolitical regions.