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Investigating crime ‘Hot Spots’ to support policing in Cornwall

1 April 2022

3 minutes to read

Investigating crime ‘Hot Spots’ to support policing in Cornwall

In collaboration with Devon and Cornwall Police, a new project explores the effect of police patrolling crime hot spots in Cornwall.

‘Hot spot’ policing is generally accepted as a meaningful way to direct resources and reduce severe violent crime. This method is supported by empirical evidence in studies conducted across the UK, Europe, the USA, Asia and Australia. The strategy involves patrolling crime hot spots derived from statistical crime data for specific periods of time.

This approach is based on the premise that crime is not evenly spread within communities but tends to be clustered in small areas. Hot spot policing aims to prevent offences in the selected patrol locations, and hopes to reduce overall crime levels in the wider neighbourhoods.

This hot spot implementation trial was funded by the Policing Lab Fund and supported by the University of Exeter’s Translational Funding team. It was executed in collaboration between Devon and Cornwall Police and the University of Exeter.

The project was led by Ronaldo Menezes, Professor of Data and Network Science and Lead PI from the University of Exeter, and Jo Arundale, Temporary Commander for Cornwall and the Isle of Scilly and Lead PI from the Devon and Cornwall Police. It was additionally supported by: Rupert Engley, East Cornwall Assistant Chief Inspector for the Devon and Cornwall Police; Dr Marcos Oliveira, Lecturer in City Science and Analytics and Project Manager from the University of Exeter; and Clodomir Joaquim De Santana Jr, University of Exeter Computer Science PhD student.

Selecting the patrol areas

Working with Devon and Cornwall Police, the team investigated high-crime areas. An initial data capture was created, looking at crime in the region from the past three years. These statistics were then mapped onto 1km squares.

From here, they applied the Cambridge Crime-Harm Index (CCHI) to these areas – this system measures the seriousness of crime harm to victims, not just the number of officially recorded crimes. Scores were applied to each offence in the area.

Initially, the crime data identified measurable similarities in crime profiles for Falmouth and Truro, with accompanying patrol and control zones in each town. However, by applying the CCHI scores to each area, Truro was selected as the preferred patrol/control zone. Liskeard was also chosen as a rural comparison.

Capturing the data

Every day for a month, police officers patrolled Truro and Liskeard on foot over two shifts. Officers carried GPS trackers to monitor their activity in the patrol zones.

The University of Exeter is now collating and analysing this data to support or refute the application of the ‘Hot Spots’ model in Devon and Cornwall. It is hoped that the results from all UK trials could inform future policing models.

A report is currently being created with the findings.

Project lead Ronaldo Menezes said, “Police patrolling is an effective way to make people feel safe, but they are expensive for police forces. This project looks at the use of ‘other authoritative figures’ in patrolling and its effectiveness in crime reduction and public confidence. This project was tested in urban and rural areas of Cornwall.”


Jo Arundale, Temporary Commander for Cornwall and the Isle of Scilly. Jo Arundale is a graduate of the National High Potential development scheme and undertook her Masters in Police Leadership and Management at Warwick Business School, focusing on the challenges of delivering Randomised Control Trails in Operational settings.

Ronaldo Menezes is a Professor of Data and Network Science and head of the computer science department at the University of Exeter. He moved to Exeter in August 2018 after 18 years at the Florida Institute of Technology. His research focuses on the areas of Network Science, Complex Systems, Data Science, Human Dynamics and Swarm Intelligence.

For more information please contact:

Prof. Ronaldo Menezes on

This work was supported by University of Exeter Translational Funds – find out more about Translational Funding HERE.

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