Recorded crime figures for CSP areas. Number of offences for the last two years, percentage change, and rates per 1,000 population for the latest year.

Context

London is the capital and most populous city of England and the United Kingdom. Standing on the River Thames in the south east of the island of Great Britain, London has been a major settlement for two millennia. Source: https://en.wikipedia.org/wiki/London

Content

This data counts the number of crimes at two different geographic levels of London (LSOA and borough) by year, according to crime type. Includes data from 2008 to present. Crime categories are included in the BigQuery table description.

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Acknowledgements

https://data.london.gov.uk/

https://bigquery.cloud.google.com/dataset/bigquery-public-data:london_crime?_ga=2.189454959.-577194880.1523455401

https://console.cloud.google.com/marketplace/details/greater-london-authority/london-crime?filter=category:public-safety

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source — http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Luca Micheli from Unplash.

Inspiration

What is the change in the number of crime incidents from 2011 to 2016?

What were the top 3 crimes per borough in 2016?

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

Deaths by local authority of usual residence, numbers and standardised mortality ratios (SMRs) by sex. SMR measures whether the population of an area has a higher or lower number of deaths than expected based on the age profile of the population (more deaths are expected in older populations). The SMR is defined as follows: SMR = (Observed no. of deaths per year)/(Expected no. of deaths per year). SMRs are calculated using the previous year's mid-year population estimates. Live birth figures are used for calculations involving deaths under 1 year. The age-standardised mortality rates in this release are directly age-standardised to the European Standard Population, which cover all ages and allows comparisons between populations with different age structures, including between males and females and over time. Note: SMR and deaths by sex data only available since 2001. Download from ONS website

Part of Release: Official Sub-Ward, Ward and Borough level crime counts. This is the most accurate data available for counting numbers of crimes in London according to official recorded crime types, by the month the offence occurred, and by either borough, ward or sub ward location. The page contains the LSOA level file (Pre-2015 data in the 'archive' file) Click here for corresponding ward level data: Recorded Crime Summary Data for London: Ward Level Click here for corresponding borough level data: Recorded Crime Summary Data for London: Borough Level ‘Sub-Ward data’ counts the number of crimes in each sub ward area of London (Census Lower Super Output Area or LSOA) per month according to crime type. Use this data if you need to analyse crime data at a sub ward level. Because not all crimes can be matched to a specific LSOA area, you should not use this data set to count crimes by ward or borough. For these purposes use one of the other datasets according to the level of geographic precision you need. The categories of crime counts within them may change from time to time. Below is a list of the crime types you can currently extract (*only at borough or ward level): Minor Category: Major Category Murder: ViolenceAgainstThePerson CommonAssault: ViolenceAgainstThePerson OffensiveWeapon: ViolenceAgainstThePerson Harassment: ViolenceAgainstThePerson Otherviolence: ViolenceAgainstThePerson AssaultWithInjury: ViolenceAgainstThePerson WoundingGBH: ViolenceAgainstThePerson PersonalProperty: Robbery BusinessProperty: Robbery BurglaryInADwelling: Burglary BurglaryInOtherBuildings: Burglary TheftOrTakingOfMotor: TheftAndHandling TheftFromMotor: TheftAndHandling MotorInterferenceAndTampering: TheftAndHandling TheftFromShops: TheftAndHandling TheftOrTakingOfPedalCycles: TheftAndHandling OtherTheftPerson: TheftAndHandling OtherTheft: TheftAndHandling HandlingStolenGoods: TheftAndHandling CriminalDamageToADwelling: CriminalDamage CriminalDamageToOtherBldg: CriminalDamage CriminalDamageToMotor: CriminalDamage OtherCriminalDamage: CriminalDamage DrugTrafficking: Drugs PossessionOfDrugs: Drugs OtherDrugOffences: Drugs GoingEquipped: OtherNotifiableOffences OtherNotifiable: OtherNotifiableOffences (NB. no Sexual Offences data is included at LSOA level for disclosure purposes) Each row of data in the data sets contains: *The number of incidents according to the Month Recorded, the specific crime type, and the Location *The Month Recorded *The broad crime type (Major HO category – eg Robbery) *The specific crime type (Minor HO category – eg Robbery: Personal Property) *The Location (Sub –Ward, Ward or borough depending on the data set selected)

Excess Winter Deaths (EWD) by age and conditions (underlying cause of death) expressed as average per year based on 7 years pooled data, 2004-2011. EWD trend expressed as average per year based on 3 years data.

The Excess Winter Mortality Index (EWM Index was calculated based on the 'ONS Method' which defines the winter period as December to March, and the non-winter period as August to November of that same year and April to July of the following year.

This winter period was selected as they are the months which over the last 50 years have displayed above average monthly mortality. However, if mortality starts to increase prior to this, for example in November, the number of deaths in the non-winter period will increase, which in turn will decrease the estimate of excess winter mortality.

The EWM Index will be partly dependent on the proportion of older people in the population as most excess winter deaths effect older people (there is no standardisation in this calculation by age or any other factor).

Excess winter mortality is calculated as winter deaths (deaths occurring in December to March) minus the average of non-winter deaths (April to July of the current year and August to November of the previous year). The Excess winter mortality index is calculated as excess winter deaths divided by the average non-winter deaths, expressed as a percentage.

Relevant link: http://www.wmpho.org.uk/excesswinterdeathsinEnglandatlas/

Note: The cumulative case count for some counties (with small population) is higher than expected due to the inclusion of non-permanent residents in COVID-19 case counts.

Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration. CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• Cases and deaths are based on date of report and not on the date of symptom onset. CDC calculates rates in this data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data were organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts were calculated as the week-to-week change in reported cumulative cases and deaths (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the week before.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues. CDC also worked with jurisdictions after the end of the public health emergency declaration to finalize county data.

• Source: The weekly archived dataset is based on county-level aggregate count data
• Confirmed/Probable Cases/Death breakdown: Cumulative cases and deaths for each county are included. Total reported cases include probable and confirmed cases.
• Time Series Frequency: The weekly archived dataset contains weekly time series data (i.e., one record per week per county)

Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the daily archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implement these case classifications. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, counts of confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions reported probable cases and deaths to CDC. Confirmed and probable case definition criteria are described here: "https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-covid-19/">Coronavirus Disease 2019 (COVID-19) 2023 Case Definition | CDC Council of State and Territorial Epidemiologists (ymaws.com).

Deaths COVID-19 deaths were reported to CDC from several sources since the beginning of the pandemic including aggregate death data and NCHS Provisional Death Counts. Historic information presented on the COVID Data Tracker pages were based on the same source (Aggregate Data) as the present dataset until the expiration of the public health emergency declaration on May 11, 2023; however, the NCHS Death Counts are based on death certificate data that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Counts from previous weeks were continually revised as more records were received and processed.

Number of Jurisdictions Reporting There were 60 public health jurisdictions that reported cases and deaths of COVID-19. This included the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. In total there were 3,222 counties for which counts were tracked within the 60 public health jurisdictions.

Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

Note: In early 2020, Alaska enacted changes to their counties/boroughs due to low populations in certain areas:

Case and death counts for Yakutat City and Borough, Alaska, are shown as 0 by default. Case and death counts for Hoonah-Angoon Census Area, Alaska, represent total cases and deaths in residents of Hoonah-Angoon Census Area, Alaska, and Yakutat City and Borough, Alaska. Case and death counts for Bristol Bay Borough, Alaska, are shown as 0 by default. Case and death counts for Lake and Peninsula Borough, Alaska, represent total cases and deaths in residents of Lake and Peninsula Borough, Alaska, and Bristol Bay Borough, Alaska.

Historical cases and deaths are not tracked separately in the county level datasets, and differences in weekly new cases and deaths could exist when county-level data are aggregated to the state-level (i.e., when compared to this dataset: https://data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36).

This data counts the number of crimes at two different geographic levels of London (LSOA and borough) by year, according to crime type. Includes data from 2008 to present. Crime categories are included in the BigQuery table description. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Data on enterprise births, deaths, active enterprises and survival rates across boroughs. Data includes: the most recent annual figures for enterprise births and deaths a time series of the number of births and deaths of entrprises together with a percentage of births and deaths to active enterprises in a given year a time series of the number of active enterprises. survival rates of enterprises for up to 5 years after birth Notes and definitions: The starting point for business demography is the concept of a population of active businesses in a reference year (t). These are defined as businesses that had either turnover or employment at any time during the reference period. A birth is identified as a business that was present in year t, but did not exist in year t-1 or t-2. Births are identified by making comparison of annual active population files and identifying those present in the latest file, but not the two previous ones. A death is defined as a business that was on the active file in year t, but was no longer present in the active file in t+1 and t+2. In order to provide an early estimate of deaths, an adjustment has been made to the 2007 and 2008 deaths to allow for reactivations. These figures are provisional and subject to revision. Data on size of firms (micro-business, SME, large) for business and employees in London by industry can be found on the ONS website. More Business Demographics data on the ONS website

This data counts the number of crimes at three different geographic levels of London (borough, ward, LSOA) per month, according to crime type. Data is available in two files for each level of geography - the most up to date data covering the last available 24 months only and one covering all historic full calendar years. In March 2019, the Metropolitan Police Service started to provide offences grouped by the updated Home Office crime classifications . This currently only covers the most recent 24 months of data, but historic data using the previous categories is available separately back to January 2008. Below is a list of the crime types covered under the new HO categories (not available at LSOA level): Major Category: Minor Category Arson and Criminal Damage - Arson / Criminal Damage Burglary: Burglary - Business and Community / Burglary - Residential Drug Offences: Drug Trafficking / Possession of Drugs Miscellaneous Crimes Against Society: Absconding from Lawful Custody / Bail Offences / Bigamy / Concealing an Infant Death Close to Birth / Dangerous Driving / Disclosure, Obstruction, False or Misleading State / Exploitation of Prostitution / Forgery or Use of Drug Prescription / Fraud or Forgery Associated with Driver Records / Going Equipped for Stealing / Handling Stolen Goods / Making, Supplying or Possessing Articles for use i / Obscene Publications / Offender Management Act / Other Forgery / Other Notifiable Offences / Perjury / Perverting Course of Justice / Possession of False Documents / Profitting From or Concealing Proceeds of Crime / Soliciting for Prostitution / Threat or Possession With Intent to Commit Crimina / Wildlife Crime Possession of Weapons: Other Firearm Offences / Possession of Firearm with Intent / Possession of Firearms Offences / Possession of Other Weapon / Possession of Article with Blade or Point

Number of deaths registered each month by area of usual residence for England and Wales, by region, county, health authorities, local and unitary authority, and London borough.

The data used in the MPS Crime Dashboard is available here MPS Crime Dashboard | Metropolitan Police, along with the related data definitions. Please note that datasets are updated monthly on the 6th of the month. Data runs until the end of the month prior.

***April 2025: The Metropolitan Police Service reviewed their recording of offences where a knife or sharp instrument has been used from April 2024 onwards.

This has shown over counting for some crime types and under counting for others. These records have been corrected which has resulted in a small overall increase in crimes that have been enabled by the use or threat of a knife or sharp instrument and a small reduction in offences resulting in an injury.

Data may therefore not match earlier publications.

Previous years’ data has not been revised therefore corrected data is not directly comparable with previous years.

The offences which are included within the Knife or sharp instrument collection are specified by the Home Office. They include robbery, homicide, assault, sexual offences and threats to kill where a knife or sharp instrument has been used to threaten or to cause injury .***

***June 2024: The MPS monthly crime data-sets are now being extracted and compiled from the new CONNECT system within the MPS; these data-sets will have prefix M1045 added to the file name.***

The Metropolitan Police Service (MPS) has introduced CONNECT, a new crime recording system that consolidates several previous systems into one integrated platform. This change aims to streamline processes and enhance efficiency across the board.

At the end of February 2024 the MPS started using CONNECT to record crime and investigation data. There is a difference in how Hate Crime and Domestic Abuse are recorded on CONNECT compared with the legacy crime recording system of CRIS and for this reason, Hate Crime and Domestic Abuse figures pre an post March are not comparable.

BCU and Borough data in CONNECT are determined by the geographic location of the incident, rather than the borough managing the case, as was the case with legacy systems. This new approach has been retroactively applied to legacy data to provide consistent and comparable analysis.

NB The datasets include breakdowns by two geography types: 'Borough' and 'Safer Neighbourhood Team (SNT)', as indicated in the 'Area Type' column. Double counting may result if you do not account for this is when using the datasets.

Total Notifiable Offence (TNO) data follows the Home Office counting rules for recorded crime (https://www.gov.uk/government/publications/counting-rules-for-recorded-crime ). NB This data-set includes “Other Accepted Crime”, which are non-notifiable crimes and must be excluded if calculating a TNO total.

The “Other Crime” offence data follows the Home Office counting rules but have been grouped by specific features (e.g. Knife Crime): please see dashboard for definitions. NB "Hate Crime" totals do NOT include records that are flagged solely as 'domestic abuse'.

Measures include Offences, Positive Outcomes, and the Positive Outcome Rate (total number of positive outcomes divided by the total number of offences in a given period).

Knife Crime Offences {date-set produced from September 2025}

From September 2025, all Knife Crime data will align with the Home Office NDQIS process for checking knife crime data quality. From that point, new ‘Knife Crime’ data sets will be refreshed and uploaded on/by the 18^th of the month.

All data is broken down by financial year for each crime type.

Abstract copyright UK Data Service and data collection copyright owner. This research aimed to provide an overview of the trends in crime and victimisation in an inner city area over the last thirty years. In this period it is widely recognised that the inner city has undergone major changes involving significant population shifts. The London Borough of Islington is taken as a point of reference because it exhibits significant changes in the composition of its population over the last thirty years as well as experiencing major changes in its leisure and consumer activities. At the same time it includes an interesting mix of gentrified areas combined with pockets of poverty and deprivation. The principal aim of the research was to examine changes in the distribution of crime and victimisation in this particular context. In 1986 a landmark study of crime and victimisation was carried out and published in the form of The Islington Crime Survey (Jones, McLean and Young, 1986). This study sought to both extend and qualify the findings of the then British Crime Survey (currently referred to as the Crime Survey for England and Wales) which collected national data. It was recognised that the form and level of crime varies significantly by area and that if victimisation surveys are going to inform policy then they have to be detailed and localised. For example, local crime surveys like The Islington Crime Survey (ICS) are able to identify specific streets and areas where people feel unsafe and can provide policy makers with the information that allows them to make such areas safer. They also allow assessments by residents of police performance and the opportunity for residents to express their priorities and concerns. Nationally, there has been a significant decrease in most forms of recorded crime over the last two decades. This research provided an investigation of this decrease in an inner city area and aimed to identify which groups, if any, have benefited from this decrease. The survey also looked at repeat victimisation since it is known that some of the most victimised groups tend to be repeatedly victimised, with the aim to see if these levels of repeat victimisation have increased or decreased over time. One of the main aims of the survey was to gain information of the experiences of victimisation amongst different ethnic groups and also to examine their relation with the police. There is also a focus on domestic violence, fear of crime, as well as forms of commercial crime. The research also drew on other data sources that provide information on crime in the borough that have been produced over the past thirty years in order to identify trends. The identification of these trends are in turn linked to an analysis of the changing economic and social context in which they are taking place. In this way the research examined changes in the distribution of victimisation in relation to the changing social composition and economic activity in the borough. This form of analysis should be able to say something significant about the changing nature of urban life and about people's concerns and experiences, which should provide some useful insights into the changing dynamics of urban culture. There is considerable debate by academic researchers about the nature and direction of urban change and in particular how these changes relate to crime. There are also debates about the degree to which various crime prevention measures have been effective in reducing crime. By identifying urban trends in conjunction with changing patterns of crime this research provides a unique opportunity to increase our understanding of some of the most significant developments that are taking place in contemporary society. The survey was undertaken using a face-to-face Computer Assisted Personal Interviewing (CAPI) methodology, with interviews being conducted in respondents’ homes. To qualify as a ‘victim’ for the purposes of the study, a respondent needed to have experienced one of the particular crime types that were in scope for the study, and to have done so in the period between the start of 2015 and the time of the interview. 2,000 interviews were targeted in total (1,500 interviews with victims and 500 interviewers with non-victims). Main Topics: Crime victimisation; urban crime; crime change; Islington. Quota sample Face-to-face interview

The data used in the MPS Business Crime dashboard is available here Business crime | Metropolitan Police, along with the related data definitions.

Please note that, this dataset is updated monthly at the beginning of the month. Data runs until the end of the month prior.

***June 2024: The business crime data-sets are now being extracted and compiled from the new CONNECT system within the MPS; these data-sets will have prefix M1046 added to the file name.***

The Metropolitan Police Service (MPS) has introduced CONNECT, a new crime recording system that consolidates several previous systems into one integrated platform. This change aims to streamline processes and enhance efficiency across the board.

With the implementation of CONNECT, there have been slight modifications in the recording of specific crime categories, such as hate crime. These adjustments may result in minor variations in crime data when compared to the pre-CONNECT era. To provide a comprehensive view of the data, the MPS has regenerated the full report to cover the entire time period.

BCU and Borough data in CONNECT are determined by the geographic location of the incident, rather than the borough managing the case, as was the case with legacy systems. This new approach has been retroactively applied to legacy data to provide consistent and comparable analysis.

Business Crime is defined by the National Business Crime Forum (NBCF), the Home Office, and the National Retail Crime Steering Group (NRCSG), chaired by the minister for crime prevention as:

“Any criminal offence that is committed against a person or property which is associated by the connection of that person or property to a business.”

The approach reflects the existing definitions for domestic abuse and hate crime. This means that the victim will determine whether or not the crime has had an impact on a business and, therefore, whether it should be identified as a business crime. This removes any ambiguity about how the crime should be recorded.

Not all business crime will be immediately identified as such by the victim or others. For example, an assault in a nightclub might not be identified as a business crime by the victim because they are more likely to perceive it as a personal attack, e.g. motivated by domestic abuse or hate related hostility.

Irrespective of the nature of the offending, if the offence took place on business premises it should additionally be recorded as a business crime. This is because criminal offending of any type on business premises may have a negative impact on the business, e.g. increased insurance premiums or, as in the case of the nightclub assault, adverse impact on whether the nightclub’s license is renewed (e.g. too many assault have taken place at that venue).

Further details can be found on the National Business Crime Centre website here:

https://nbcc.police.uk/

Number of suicides, suicide rates and median registration delays, by local authority in England and Wales.

Crime Rates of offences per thousand population, by broad crime grouping, by financial year for wards. Offences: These are confirmed reports of crimes being committed. All data relates to "notifiable offences" - which are designated categories of crimes that all police forces in England and Wales are required to report to the Home Office. Ward data should not be aggregated to give a borough or London total. This is because a small percentage (less than 5%) of crimes in this dataset have not been geocoded to a ward. Therefore total numbers and rates are indicative only, and are not an exact measure at ward level. The rate is calculated using ward GLA 2012-based (SHLAA) population projections, and population data calculated and constrained to 2012 Borough (SHLAA) projections. The London figure only includes the Met Police area, not the City of London. The London total includes all offences in the Met Police Area including those that could not be geocoded. Therefore the London total will not equal the sum of the wards. Some ward boundaries changed in 2014. From 2013/14 the data shown is for the new boundaries. This only affects Hackney, Kensington and Chelsea, and Tower Hamlets. From 2013/14, the numbers and rates for 2013 ward boundaries in Hackney, K&C and Tower Hamlets, have all been modelled based on the proportion of population living in each area at the 2011 Census. Action Fraud have taken over the recording of fraud offences on behalf of individual police forces. This process began in April 2011 and was rolled out to all police forces by March 2013. Due to this change caution should be applied when comparing data over this transitional period and with earlier years. Data by detailed crime group and month are available from the MPS website .

Data on enterprise births, deaths, active enterprises and survival rates in Barnet, as well as comparative data across Greater London boroughs.

This data is adapted from data from the Office for National Statistics and published by the GLA licensed under the Open Government Licence.

Comparative data and other information can also be found on the London Datastore.

Data includes:
1) the most recent annual figures for enterprise births and deaths. Births and deaths are identified by comparing active populations of enterprises for different years
2) time series of the number of births and deaths of entrprises together with a percentage of births and deaths to active enterprises in a given year
3) a time series of the number of active enterprises. Active enterprises are businesses that had either turnover or employment at any time during the reference period.
4) survival rates of enterprises for up to 5 years after birth

Data on size of firms (micro-business, SME, large) for business and employees in London by industry can be found on the ONS website.

More Business Demographics data on the ONS website

This project will investigate Olympic-related policing and crime in the London borough of Newham, where the Olympic village and stadium are being built. We have obtained exceptional access to all levels of the Newham police force, and have been conducting extensive preliminary fieldwork with local police, and across the borough, since April 2007. More specifically: we shall investigate how the police define, monitor, contain, investigate and solve 'Olympic related' crime we shall also explore the forms of Olympic-related crime that are prioritised by police; and how Olympic related policing connects to urban policing strategies, notably in relation to large public thoroughfares and major events we shall examine Olympic-related relationships that are established by Newham police with other police, security and emergency services we shall explore the broader impacts of the Olympics in Newham in regard to: criminal activities and opportunity; local criminal markets (eg identity-theft, business fraud, drug markets); and, the wider night-time economy we shall examine the local impact of Olympic-related policing, and explore police-community relations as these unfold before, during and after the Olympic Games. The research team were embedded with the Newham Police for the length of the project, observing regular borough police tactical, strategic and management meetings, observing a variety of Olympic policing meetings (at local borough, multi-borough and London-wide levels), working with crime analysts, interviewing stakeholders, attending council meetings and Metropolitan Police meetings across London. After gaining the relevant MPS security clearance, and via effective networking within the MPS, the research team gained access to high level and sensitive meetings, in particular in relation to Olympic intelligence and Olympic policing test events. We observed the MPS Special Operations room from which the Olympic policing operation was run. We also gained access to meetings between the police in Newham, other public sector bodies (Council, education, NHS) and commercial partners to discuss the post-Olympic policing of legacy sites including the Olympic Park and Athletes’ Village. We accompanied Newham Police officers whilst they engaged in a wide range of their duties before, during and after the Olympics, attended various local council meetings, and particularly as gangs became identified as a key local problem, leading to some crucial institutional and operational innovations, we worked with specialist police, council officers and with gang members themselves. It should be noted that we were in the field at the time of the August 2011 riots and were able to observe the impact on and response of local police. We gathered a wide range of secondary materials such as documents and reports on Olympic-related issues, including regular Olympic police intelligence updates and briefings, as well as local, national and international media reports on relevant Olympic topics.

This Fire Facts publication - first published in 2018 - provides a range of statistical data about fire deaths in London. It includes a time series of data back to 1966, data for fire deaths by London borough, where people die, what causes the fires where people die, plus ethnicity and gender data about those who die in fires.