DHIS2 Analytics Pipeline

Overview

The DHIS2 Analytics Pipeline automates the extraction, transformation, and analysis of health data from a DHIS2 instance. This project focuses on retrieving facility-level weekly data, enriching it with organisational unit details, and exporting the processed data in a structured format for further reporting and visualisation.

Features

• Automated Data Extraction: Queries DHIS2 API to fetch datasets, data elements, and organisational units.
• Facility-Level Aggregation: Aggregates health data weekly, categorised by facilities, districts, and provinces.
• Enrichment with Organizational Details: Merges facility data with district and province information for comprehensive insights.
• CSV Export: Outputs processed data to CSV files for easy access and analysis.

Installation

1. Clone the repository:

   git clone https://github.com/malambomutila/DHIS2-Pipeline.git

2. Navigate to the project directory:

   cd DHIS2-Pipeline

3. Install required dependencies:

   pip install -r requirements.txt

4. Configure DHIS2 credentials in the 00_Local/01_Configs/credentials.txt file:

   DHIS2_URL=your_dhis2_instance_url
   USERNAME=your_username
   PASSWORD=your_password
   

Usage

1. Run the Jupyter Notebook to fetch and process data:

   querydata.ipynb

2. Processed data will be saved in the 00_Local/02_Data/ directory as CSV files.

Output Files

The following CSV files are generated by the pipeline:

• datasets.csv: List of available datasets from DHIS2.
• data_elements.csv: Metadata for available data elements.
• organisation_units.csv: Details of all organization units.
• districts.csv: District-level organization units.
• provinces.csv: Province-level organization units.
• facility_january_2024_with_org_details.csv: Processed health data by facility.

Contributions

Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to improve the project.