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🔍 South African Crime Intelligence Report

Gender-Based Violence, Sexual Offences & Femicide: A Critical Data Analysis™

"Crime remains unacceptably high and continues to affect many families and communities." — Acting Police Minister Firoz Cachalia, 20 February 2026

Python Jupyter SAPS SAMRC License


🎯 Project Overview

This notebook interrogates the claim by SAPS Crime Registrar Major-General Thulare Sekhukhune that reported rape cases decreased by 3.2% in Q3 FY2025/26 — and places that claim within two decades of femicide surveillance data published by the South African Medical Research Council (SAMRC).

Produced from the perspective of a private security analytical division conducting occasional work with SAPS, this notebook applies rigorous data science methodology to one of South Africa's most critical public health and safety challenges.


❓ Research Questions

  1. Is there truly a decrease in reported rape as stated by Maj-Gen Sekhukhune?
  2. What does the SAMRC's 20-year femicide surveillance data reveal that SAPS statistics cannot?
  3. Which provinces and demographics are at highest risk?
  4. What does statistical modelling predict for FY2025/26 and FY2026/27?

📓 Notebook Structure

Phase Cells Content
Phase 1 1–2 Environment setup, CSV data pipeline
Phase 2 3–10 Exploratory data analysis — 8 visualisation panels
Phase 3 11–15 Statistical modelling — correlation, anomaly detection, regression, forecasting
Phase 4 16–19 Intelligence report, dashboard, recommendations

🔬 Methods Applied

  • Pearson & Spearman correlation analysis
  • Z-score anomaly detection (annual + provincial)
  • Isolation Forest anomaly detection
  • OLS regression — simple & multiple with full diagnostics
  • Linear extrapolation with 95% prediction intervals
  • Holt's Exponential Smoothing
  • ARIMA(1,1,0) with confidence intervals
  • 3-model ensemble forecasting

📊 Data Sources

Source Description Period
SAPS Q3 2025/26 Cachalia press briefing, 20 Feb 2026 Oct–Dec 2025
SAPS Annual Reports Historical crime statistics FY2012/13–FY2023/24
SAMRC Femicide Study Abrahams et al. (2025), Global Public Health 1999–2020/21
Africa Check Underreporting research Various
Stats SA Mid-year population estimates 2013–2025

🗂️ Repository Structure

sa-crime-intelligence/
├── SA_Crime_Intelligence_Report.ipynb   # Main notebook
├── intelligence_dashboard.png           # Exported dashboard
├── data/
│   ├── quarterly_rape.csv
│   ├── annual_sexual_offences.csv
│   ├── contact_crimes_q3.csv
│   ├── provincial_rape.csv
│   ├── femicide_samrc.csv
│   └── underreporting_estimates.csv
└── README.md

🔑 Key Findings

On the reported rape decrease: A 3.2% decline in reported rape (373 fewer cases) does NOT constitute evidence of reduced sexual violence. Three provinces recorded increases, and underreporting research estimates only 1 in 25 rapes reaches SAPS records.

On femicide (SAMRC, 2025): South Africa's intimate partner femicide rate of 5.5 per 100,000 women is five times the global average. This rate INCREASED during COVID-19 and has not structurally declined since 2009.

On the forecast: Ensemble modelling (Linear + Holt's ES + ARIMA) projects no structural decline in the rape rate for FY2025/26 or FY2026/27.


🛠️ Tech Stack

Category Tools
Data manipulation Python, Pandas, NumPy
Visualisation Matplotlib, Seaborn
Statistical analysis SciPy, Statsmodels
Machine learning Scikit-learn (Isolation Forest)
Time series Statsmodels (Holt's ES, ARIMA)
Environment Google Colab

⚠️ Important Disclaimer

All data used is sourced from publicly available official government publications and peer-reviewed research. This notebook does not contain classified or confidential SAPS operational data. Findings represent the independent analytical conclusions of the author.


👩🏾‍💻 Author

Lindiwe Songelwa™ — Data Scientist | Developer | Insight Creator


© 2026 Lindiwe Songelwa™. All rights reserved. No part of this work may be reproduced without express written permission of the author.

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South Africa crime statistics analysis — GBV, rape, femicide, SAPS Q3 2025/26 | Python | SAMRC | Statsmodels | ARIMA

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