peaceokeke91-create/Neonatal-Mortality-Python-Analysis

Python analysis code for neonatal mortality determinants in Nigeria using 2024 Nigeria Demographic and Health Survey (NDHS) data. Neonatal Mortality Determinants in Nigeria Analysis code for the manuscript: "Socioeconomic and Geographic Determinants of Neonatal Mortality in Nigeria: A Cross-Sectional Analysis of the 2024 Demographic and Health Survey" Peace Chinenye Okeke and Precious Ifeoma Ugwu Overview This repository contains the complete Python analysis code used to produce all results, tables, and figures in the manuscript. The analysis uses survey-weighted logistic regression and concentration index methods to identify socioeconomic and geographic determinants of neonatal mortality in Nigeria. Repository Contents File Description Neonatal Mortality 2024.ipynb Main Jupyter notebook with all analysis code Figure1_NMR_by_zone.png Bar chart: Neonatal mortality rate by geopolitical zone Figure2_concentration_curve.png Concentration curve showing wealth-related inequality requirements.txt Python package dependencies Requirements · Python 3.11.0 · Packages listed in requirements.txt Install dependencies: pip install -r requirements.txt Data Source and Access This analysis uses the 2024 Nigeria Demographic and Health Survey (NDHS) Birth Recode file. The data are not included in this repository per the DHS Program data use agreement. To reproduce this analysis: 1. Register at dhsprogram.com 2. Submit a data access request for the 2024 Nigeria DHS 3. Download the Birth Recode file (.dta format) 4. Place the file in your working directory 5. Update the data_path variable in the notebook to point to your file Data Access Authorization: AuthLetter_230883 Usage 1. Clone this repository: git clone github.com 2. Install dependencies: pip install -r requirements.txt 3. Obtain the NDHS data file from the DHS Program (see above) 4. Open the Jupyter notebook: jupyter notebook "Neonatal Mortality 2024.ipynb" ``` 5. Update the data_path variable in Cell [2] to point to your NDHS .dta file 6. Run all cell …