CB_2649 - LAC II 2024/2025

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Table of Contents

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• Overview
• Project Structure
• Data Sources
• Workflow Diagram
• Reproduction Steps - Environment Setup - Running the Analysis
  • Demographic Analysis
  • LSOA-Level Analysis
  • Comprehensive Assessment
• Key Modules
• License

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Overview

This project analyzes three social care interventions in Bradford:

• Child Protection Plans (CPP)
• Looked After Children (LAC)
• Children in Need Plans (CINP)

The analysis examines both demographic patterns and geographical distribution at Lower Super Output Area (LSOA) level.

Project Structure

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├── code/               # Reusable modules for analysis
├── data/               # Input datasets
├── docs/               # Documentation
├── figs/               # Generated visualizations
├── notebooks/          # Analysis notebooks     
└── requirements.txt    # Dependencies

Data Sources

• Bradford boundary data (LSOA level) - LINK
• English Index of Multiple Deprivation (IMD) 2019 - LINK
• Bradford children population data (0-17, 2021) - LINK
• Children's social care data (CPP, LAC, CINP) - Connected Bradford

Workflow Diagram

This diagram provides an overview of the analysis workflow:

Reproduction Steps

Environment Setup

1. Clone this repository and navigate to the project folder:

git clone https://github.com/ConnectedBradford/CB_2649
cd CB_2649

2. Create and activate a virtual environment:

# For Windows
python -m venv venv
venve\Scripts\activate

# For Mac/Linux
python -m venv venv
source venv/bin/activate

3. Install dependencies:

pip install -r requirements.txt

Running the Analysis

Demographic Analysis

The demographic analysis workflow:

1. Run the initial CPP analysis:

   jupyter notebook notebooks/cpp_demographic_analysis.ipynb

2. The LAC and CINP demographic analyses reuse modules from the CPP analysis:

   jupyter notebook notebooks/lac_demographic_analysis.ipynb
   jupyter notebook notebooks/cinp_demographic_analysis.ipynb

LSOA-Level Analysis

The LSOA analysis workflow:

1. Run the initial LAC analysis:

   jupyter notebook notebooks/lac_lsoa_analysis.ipynb

2. The CPP and CINP LSOA analyses reuse modules from the LAC analysis:

   jupyter notebook notebooks/cpp_lsoa_analysis.ipynb
   jupyter notebook notebooks/cinp_lsoa_analysis.ipynb

Comprehensive Assessment

For a combined analysis of assessment across interventions:

jupyter notebook notebooks/assessment_analysis.ipynb

Key Modules

• data_cleaning.py: Data preparation and standardization
• analysis_helpers.py: Analysis functions for demographic analysis
• lsoa_analysis_helper.py: Geospatial analysis functions for LSOA-level analysis

7. License

See the LICENSE file for details.