1. Title & Overview

“In 2020, recorded offences in Victoria hit a 10-year low as lockdowns emptied the streets. But did all communities recover equally?”

• Crime in Victoria shows strong temporal and regional variation.
• COVID-19 lockdowns created an unprecedented drop in offences.
• The question: Did all communities recover equally?

2. Data & Sources

We combined 10 years of offence records across 79 LGAs with ABS SEIFA scores to see how disadvantage shaped crime recovery.

Datasets Used

• Crime Statistics Agency Victoria (2015–2025): Recorded offences by LGA.
• ABS SEIFA 2021 Index: Measures socio-economic advantage/disadvantage.
• ASGS 2025 LGA Boundaries: Provides spatial data for mapping.

Processing Steps

• Cleaned, filtered, and merged by LGA and year.
• Aggregated total offences and offence rate (per 100k population).
• Joined with SEIFA index for contextual analysis.

3.Crime Trend (2015-2025)

Notice the sudden collapse in 2020 during the first lockdown, and a partial rebound as restrictions eased. The dashed zone marks Victoria’s strictest restrictions.

• Offences plunged during COVID lockdowns (2020–2021).
• Theft, robbery, and public order incidents dropped sharply.
• Violent and family-related offences remained stable.

But did every community follow the same pattern

4.SEIFA Context

Each dot is an LGA. To the right : wealthier areas; to the left : more disadvantaged. The downward slope shows how socio-economic advantage relates to lower crime.

• A strong negative relationship: higher SEIFA → lower offence rate.
• Disadvantaged LGAs remain more vulnerable post-lockdown.
• R² value shows SEIFA explains part of the variance in crime.

“Disadvantage amplifies risk even after lockdowns.”

5.Map of Rates

“Hover to explore Victoria. Darker tones mark LGAs with higher offence rates, notice clusters across outer regional corridors.”

• Darker purple/red = higher offence rates.
• Outer regional areas show persistent hotspots.
• Metropolitan Melbourne shows partial recovery.

6.Change Over Time (2019→2021)

“While theft dropped sharply in metro Melbourne, regional LGAs like Horsham saw increases as policing resources shifted.”

• Metro LGAs like Melbourne saw major decreases.
• Some regional LGAs experienced rebounds.
• Indicates uneven recovery linked to socio-economic factors.

“COVID’s effect was uneven — some areas rebounded, others worsened.”

7. Key Findings

2020–2021 lockdowns caused a sharp statewide decline in offences.

• Lockdowns triggered a temporary crime dip.
• Recovery uneven across socio-economic groups.
• Low-SEIFA areas show persistent vulnerability.

Data doesn’t just show numbers, it shows inequality.

8. Implications

Data-driven insights can guide targeted policing and community safety programs.

• Direct community safety programs toward high-risk LGAs.
• Combine socio-economic uplift with crime prevention.
• Open data reveals inequality and guides policy action.

Every dataset hides a human story, how we act on it shapes recovery.

9. References

Crime Statistics Agency Victoria. (2025). Recorded offences by LGA (2015–2025). https://www.crimestatistics.vic.gov.au/crime-statistics/latest-victorian-crime-data

Australian Bureau of Statistics. (2023). SEIFA 2021 – Index of Advantage and Disadvantage by LGA. https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia

Australian Bureau of Statistics. (2025). Australian Statistical Geography Standard (ASGS) Edition 3 – LGA Shapefile (2025). https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3