African Neonatal Outcomes Dashboard

This dashboard simulates a neonatal monitoring system aligned with the Minimal Neonatal Dataset (mND) structure. It showcases how key metrics and filters can support monitoring and evaluation (M&E) for neonatal care across hospitals and time.

Hosted version: [Render URL]

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Features

• Multi-select filters: Hospital, Outcome, Diagnosis, Year
• Interactive charts:
  • Outcomes by Diagnosis
  • Average Length of Stay
  • Monthly Admissions Trend
  • Birth Weight Distribution
  • Patient Outcome Proportions
• Summary cards:
  • Total Admissions
  • Number of Deaths
  • Average LOS
  • Average Birth Weight
• Sticky header and sidebar
• Dynamic chart titles based on filters

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Project Structure

├── app.py                  
├── data/
│   └── synthetic_mnd_data.csv
├── requirements.txt        
├── Procfile                
└── README.md

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Running the App Locally

1. Clone the repo

git clone https://github.com/3liud/nest-job-sample-dashboard.git
cd nest-job-sample-dashboard

2. Set up a virtual environment

For macOS/Linux:

python3 -m venv venv
source venv/bin/activate

For Windows:

python -m venv venv
venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Run the app

python app.py

Then open http://localhost:8050 in your browser.

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Deploying on Render

1. Add these two files:

• requirements.txt
• Procfile

2. Set Procfile content:

web: python app.py

3. Push your repo to GitHub, then connect it to Render and deploy as a Web Service.

Set:

• Start command: python app.py
• Python version: 3.x
• Port binding: Handled automatically via os.environ.get("PORT")

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Data

The app uses synthetic neonatal data based on the Minimal Neonatal Dataset (mND) for demonstration only. No real patient data is included.

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Author

Built by Eliud, a data analyst passionate about applying data to improve health outcomes.

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