PHC_Data_Engineering_Pipeline
# ai4phc-north-nigeria
PHC_Data_Engineering_Pipeline
# π₯ **AI4PHC β Smarter Primary Health Care for Northern Nigeria**
**Strengthening Maternal, Child, and Public Health through Data and AI**
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## π Overview
The **AI for Smarter Primary Health Care (AI4PHC)** initiative is a flagship Federal Government project designed to enhance **maternal and child health outcomes** and improve **disease outbreak preparedness** in **Northern Nigeria** through artificial intelligence and data-driven innovation.
This project integrates **data engineering**, **machine learning**, and **human-centred design** to build an intelligent PHC support system β starting with a **prototype deployment at a Primary Health Centre (PHC) in Kano Municipal**, before scaling nationwide.
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## π― Project Objectives
- Strengthen PHC service delivery using **AI-assisted analytics and dashboards**.
- Predict and mitigate **maternal, neonatal, and under-5 mortality** through data science.
- Forecast **medical and vaccine inventory levels** to prevent stockouts.
- Improve accessibility for **remote settlements** through appointment clustering and transport scheduling.
- Bridge literacy and language barriers using a **Hausa-language AI chatbot β Dr. Amina**, capable of both text and voice interaction.
- Automate appointment reminders through **SMS + voice Hausa messages**.
- Provide policymakers with **real-time insights** for evidence-based interventions.
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## π§ Key Components
### **1. Data Engineering**
- **PostgreSQL + PostGIS** database architecture.
- Automated **ETL pipelines** for patient, visit, immunization, and inventory data.
- Integration of **simulated and real PHC datasets (2022β2025)**.
- Built-in **database triggers** for stock updates and geographic distance calculations.
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### **2. Data Science & Analytics**
**Forecasting models for:**
- Disease outbreaks β *Malaria, Cholera, Meningitis*.
- Stock-out risk prediction.
- Maternal and child mortality trends.
- Predictive cl β¦