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

Provisional counts of the number of deaths registered in England and Wales, by age, sex, region and Index of Multiple Deprivation (IMD), in the latest weeks for which data are available.

United Kingdom UK: Intentional Homicides: per 100,000 People data was reported at 1.202 Ratio in 2016. This records an increase from the previous number of 0.992 Ratio for 2015. United Kingdom UK: Intentional Homicides: per 100,000 People data is updated yearly, averaging 1.399 Ratio from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 1.865 Ratio in 2002 and a record low of 0.907 Ratio in 2014. United Kingdom UK: Intentional Homicides: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Health Statistics. Intentional homicides are estimates of unlawful homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.; ; UN Office on Drugs and Crime's International Homicide Statistics database.; Weighted average;

There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

Annual data on death registrations by single year of age for the UK (1974 onwards) and England and Wales (1963 onwards).

Deaths registration data (all deaths in England and Wales) collected from The Registrar General for England and Wales.

Record-level patient data set, where a record represents one death registration.

The data are collected at source from Local Registry offices at the point of death registration.

The data are collated nationally by the Register General before being passed to the Office for National Statistics (ONS), for use in statistics and coding.

Coding includes such things cause of death coding using the International Classifications of Diseases (ICD) coding system, attributing socio-economic code classifications based on occupation.

ONS maintains its own version of the data set for its use in statistics.

In addition to the description, please add "Timescales for dissemination can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process ". Supports HDR UK Delivery Lead Time below which has a standard answer of OTHER: If the typical timeframe does not fit into the broad ranges i.e. lightweight application vs linked data application, please choose “Other” and indicate the typical timeframe within the description for the dataset

The Civil Registration of Deaths data contains 14 million unique registrations since 1993 onwards, increasing yearly. Average 500,000 - 600,000 new death registrations yearly.

Records cover all deaths registered in England & Wales. ICD coding is 9th and 10th.

https://digital.nhs.uk/services/data-access-request-service-dars

Timescales for dissemination can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process

Provisional deaths registration data for single year of age and average age of death (median and mean) of persons whose death involved coronavirus (COVID-19), England and Wales. Includes deaths due to COVID-19 and breakdowns by sex.

NISRA publish timely but provisional counts of deaths registered by the General Register Office for Northern Ireland (GRO). Weekly totals are presented alongside a 5-year weekly average number of deaths for the same week over the last five years.

United Kingdom UK: Death Rate: Crude: per 1000 People data was reported at 9.100 Ratio in 2016. This records a decrease from the previous number of 9.200 Ratio for 2015. United Kingdom UK: Death Rate: Crude: per 1000 People data is updated yearly, averaging 11.300 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 12.200 Ratio in 1963 and a record low of 8.700 Ratio in 2011. United Kingdom UK: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Annual UK and constituent country figures for births, deaths, marriages, divorces, civil partnerships and civil partnership dissolutions.

There reference tables presents provisional estimated figures of excess winter mortality (EWM) for the winter period 2013/14, and final figures for the winter period 1950 to 2011 in England and Wales. These results are broken down by region, sex, age group and local authority.

Datasets include: 5 year moving average, mean number of daily deaths each month, mean monthly temperature each month, weekly deaths per 100,000 caused by influenza-like illnesses, mortality by sex, age, region, usual country of residence and local autority and the underlying case of death from 1991 - 2014.

The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. It includes deaths which occurred in hospital and deaths which occurred outside of hospital within 30 days (inclusive) of discharge. Deaths related to COVID-19 are excluded from the SHMI. The SHMI gives an indication for each non-specialist acute NHS trust in England whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected' (SHMI banding=1), 'as expected' (SHMI banding=2) or 'lower than expected' (SHMI banding=3) when compared to the national baseline. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided. The SHMI is composed of 142 different diagnosis groups and these are aggregated to calculate the overall SHMI value for each trust. The number of finished provider spells, observed deaths and expected deaths at diagnosis group level for each trust is available in the SHMI diagnosis group breakdown files. For a subset of diagnosis groups, an indication of whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected', 'as expected' or 'lower than expected' when compared to the national baseline is also provided. Details of the 142 diagnosis groups can be found in Appendix A of the SHMI specification. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for this trust are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. There is a high percentage of invalid diagnosis codes for Chesterfield Royal Hospital NHS Foundation Trust (trust code RFS), Milton Keynes University Hospital NHS Foundation Trust (trust code RD8), and West Suffolk NHS Foundation Trust (trust code RGR). Values for these trusts should therefore be interpreted with caution. 6. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 7. East Kent Hospitals University NHS Foundation Trust (trust code RVV) has a submission issue which is causing many of their patient spells to be duplicated in the HES Admitted Patient Care data. This means that the number of spells for this trust in this dataset are overstated by approximately 60,000, and the trust’s SHMI value will be lower as a result. Values for this trust should therefore be interpreted with caution. 8. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.