ESEA Data Collective: 2020-21

2020-21: Percentage Change in Reported Hate Crimes/ Incidents against ESEA people, by Police Jurisdiction

Dorset Police: 400.00%
Gwent Police: 250.00%
Cleveland Police: 200.00%
Gloucestershire Constabulary: 180.00%
Warwickshire Police: 133.33%
Humberside Police: 120.00%
Leicestershire Police: 75.00%
Derbyshire Constabulary: 66.67%
Hertfordshire Constabulary: 57.69%
City of London Police: 40.00%
Nottinghamshire Police: 37.50%
Avon & Somerset Constabulary: 32.61%
Cambridgeshire Constabulary: 29.41%
Durham Constabulary: 26.92%
Norfolk Constabulary: 22.22%
Kent Police: 14.29%
Lancashire Constabulary: 14.29%
Sussex Police: 7.14%
Cheshire Constabulary: 6.25%
Wiltshire Police: 0.00%
Essex Police: 0.00%
Surrey Police: 0.00%
Greater Manchester Police: -3.45%
Northumbria Police: -4.17%
South Yorkshire Police: -8.33%
Bedfordshire Police: -9.09%
British Transport Police: -11.43%
West Yorkshire Police: -13.64%
Police Service of Northern Ireland: -14.29%
Thames Valley Police: -16.67%
Metropolitan Police Service: -19.90%
Staffordshire Police: -20.00%
Suffolk Constabulary: -21.43%
Police Scotland: -23.08%
North Yorkshire Police: -25.00%
South Wales Police: -29.17%
Lincolnshire Police: -33.33%
North Wales Police: -33.33%
Devon & Cornwall Police: -37.50%
West Midlands Police: -47.95%
Merseyside Police: -51.02%
Northamptonshire Police: -57.14%
Dyfed-Powys Police: -57.14%
West Mercia Police: -62.50%
Cumbria Constabulary: -71.43%
Hampshire Constabulary: No data
Civil Nuclear Constabulary: No data
Ministry of Defence Police: No data

The ESEA Data Collective is driven by VoiceESEA, End the Virus of Racism and The Public Data Lab (KCL) . The collective uses data to understand the scale of anti-ESEA discrimination in the UK.

To determine the rates of police-reported hate crimes against ESEAs between 2019-2021, data was collated from 48 police jurisdictions, using Freedom of Information Act 2000 requests.

Our raw data is accessible here (subject to terms and conditions of use). Please see this source data for actual figures, noting that relative change, compared to actual change can make values appear more significant than they are.