Pre-existing conditions of people who died due to COVID-19, broken down by country, broad age group, and place of death occurrence, usual residents of England and Wales.

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.

The number of deaths registered in England and Wales due to and involving coronavirus (COVID-19). Breakdowns include age, sex, region, local authority, Middle-layer Super Output Area (MSOA), indices of deprivation and place of death. Includes age-specific and age-standardised mortality rates.

11th January 2020 Change to vaccination data made available by UK gov - now just cumulative number of vaccines delivered are available for both first and second doses. For the devolved nations the cumulative totals are available for the dates from when given, however for the UK as a whole the total doses given is just on the last date of the index, regardless of when those vaccines were given.

4th January 2020 VACCINATION DATA ADDED - New and Cumulative First Dose Vaccination Data added to UK_National_Total_COVID_Dataset.csv and UK_Devolved_Nations_COVID_Dataset.csv

2nd December 2020:

NEW population, land area and population density data added in file NEW_Official_Population_Data_ONS_mid-2019.csv. This data is scraped from the Office for National Statistics and covers the UK, devolved UK nations, regions and local authorities (boroughs).

20th November 2020:

With European governments struggling with a 'second-wave' of rising cases, hospitalisations and deaths resulting from the SARS-CoV-2 virus (COVID-19), I wanted to make a comparative analysis between the data coming out of major European nations since the start of the pandemic.

I started by creating a Sweden COVID-19 dataset and now I'm looking at my own country, the United Kingdom.

The data comes from https://coronavirus.data.gov.uk/ and I used the Developer's Guide to scrape the data, so it was a fairly simple process. The notebook that scapes the data is public and can be found here. Further information about data collection methodologies and definitions can be found here.

The data includes the overall numbers for the UK as a whole, the numbers for each of the devolved UK nations (Eng, Sco, Wal & NI), English Regions and Upper Tier Local Authorities (UTLA) for all of the UK (what we call Boroughs). I have also included a small table with the populations of the 4 devolved UK nations, used to calculate the death rates per 100,000 population.

As I've said for before - I am not an Epidemiologist, Sociologist or even a Data Scientist. I am actually a Mechanical Engineer! The objective here is to improve my data science skills and maybe provide some useful data to the wider community.

Any questions, comments or suggestions are most welcome! I am open to requests and collaborations! Stay Safe!

Dataset description

Daily official UK Covid data. The data is available per country (England, Scotland, Wales and Northern Ireland) and for different regions in England. The different regions are split into two different files as part of the data is directly gathered by the NHS (National Health Service). The files that contain the word 'nhsregion' in their name, include data related to hospitals only, such as number of admissions or number of people in respirators. The files containing the word 'region' in their name, include the rest of the data, such as number of cases, number of vaccinated people or number of tests performed per day. The next paragraphs describe the columns for the different file types.

Region files

Files related to regions (word 'region' included in the file name) have the following columns: - "date": date in YYYY-MM-DD format - "area type": type of area covered in the file (region or nation) - "area name": name of area covered in the file (region or nation name) - "daily cases": new cases on a given date - "cum cases": cumulative cases - "new deaths 28days": new deaths within 28 days of a positive test - "cum deaths 28days": cumulative deaths within 28 days of a positive test - "new deaths_60days": new deaths within 60 days of a positive test - "cum deaths 60days": cumulative deaths within 60 days of a positive test - "new_first_episode": new first episodes by date - "cum_first_episode": cumulative first episodes by date - "new_reinfections": new reinfections by specimen data - "cum_reinfections": cumualtive reinfections by specimen data - "new_virus_test": new virus tests by date - "cum_virus_test": cumulative virus tests by date - "new_pcr_test": new PCR tests by date - "cum_pcr_test": cumulative PCR tests by date - "new_lfd_test": new LFD tests by date - "cum_lfd_test": cumulative LFD tests by date - "test_roll_pos_pct": percentage of unique case positivity by date rolling sum - "test_roll_people": unique people tested by date rolling sum - "new first dose": new people vaccinated with a first dose - "cum first dose": cumulative people vaccinated with a first dose - "new second dose": new people vaccinated with a first dose - "cum second dose": cumulative people vaccinated with a first dose - "new third dose": new people vaccinated with a booster or third dose - "cum third dose": cumulative people vaccinated with a booster or third dose

Country files

Files related to countries (England, Northern Ireland, Scotland and Wales) have the above columns and also: - "new admissions": new admissions, - "cum admissions": cumulative admissions, - "hospital cases": patients in hospitals, - "ventilator beds": COVID occupied mechanical ventilator beds - "trans_rate_min": minimum transmission rate (R) - "trans_rate_max": maximum transmission rate (R) - "trans_growth_min": transmission rate growth min - "trans_growth_max": transmission rate growth max

NHS Region files

Files related to nhsregion (word 'nhsregion' included in the file name) have the following columns: - "new admissions": new admissions, - "cum admissions": cumulative admissions, - "hospital cases": patients in hospitals, - "ventilator beds": COVID occupied mechanical ventilator beds - "trans_rate_min": minimum transmission rate (R) - "trans_rate_max": maximum transmission rate (R) - "trans_growth_min": transmission rate growth min - "trans_growth_max": transmission rate growth max

It's worth noting that the dataset hasn't been cleaned and it needs cleaning. Also, different files have different null columns. This isn't an error in the dataset but the way different countries and regions report the data.

This mapping tool enables you to see how COVID-19 deaths in your area may relate to factors in the local population, which research has shown are associated with COVID-19 mortality. It maps COVID-19 deaths rates for small areas of London (known as MSOAs) and enables you to compare these to a number of other factors including the Index of Multiple Deprivation, the age and ethnicity of the local population, extent of pre-existing health conditions in the local population, and occupational data. Research has shown that the mortality risk from COVID-19 is higher for people of older age groups, for men, for people with pre-existing health conditions, and for people from BAME backgrounds. London boroughs had some of the highest mortality rates from COVID-19 based on data to April 17th 2020, based on data from the Office for National Statistics (ONS). Analysis from the ONS has also shown how mortality is also related to socio-economic issues such as occupations classified ‘at risk’ and area deprivation. There is much about COVID-19-related mortality that is still not fully understood, including the intersection between the different factors e.g. relationship between BAME groups and occupation. On their own, none of these individual factors correlate strongly with deaths for these small areas. This is most likely because the most relevant factors will vary from area to area. In some cases it may relate to the age of the population, in others it may relate to the prevalence of underlying health conditions, area deprivation or the proportion of the population working in ‘at risk occupations’, and in some cases a combination of these or none of them. Further descriptive analysis of the factors in this tool can be found here: https://data.london.gov.uk/dataset/covid-19--socio-economic-risk-factors-briefing

COVID-19Plots and analysis relating to the coronavirus pandemic. Includes five sets of plots and associated R code to generate them.1) HeatmapsUpdated every few days - heatmaps of COVID-19 case and death trajectories for Local Authorities (or equivalent) in England, Wales, Scotland, Ireland and Germany.2) All cause mortalityUpdated on Tuesday (for England & Wales), Wednesday (for Scotland) and Friday (for Northern Ireland) - analysis and plots of weekly all-cause deaths in 2020 compared to previous years by country, age, sex and region. Also a set of international comparisons using data from mortality.org3) ExposuresNo longer updated - mapping of potential COVID-19 mortality exposure at local levels (LSOAs) in England based on the age-sex structure of the population and levels of poor health.There is also a Shiny app which creates slightly lower resolution versions of the same plots online, which you can find here: https://victimofmaths.shinyapps.io/covidmapper/, on GitHub https://github.com/VictimOfMaths/COVIDmapper and uploaded to this record4) Index of Multiple Deprivation No longer updated - preliminary analysis of the inequality impacts of COVID-19 based on Local Authority level cases and levels of deprivation. 5) Socioeconomic inequalities. No longer updated (unless ONS release more data) - Analysis of published ONS figures of COVID-19 and other cause mortality in 2020 compared to previous years by deprivation decile.Latest versions of plots and associated analysis can be found on Twitter: https://twitter.com/victimofmathsThis work is described in more detail on the UK Data Service Impact and Innovation Lab blog: https://blog.ukdataservice.ac.uk/visualising-high-risk-areas-for-covid-19-mortality/Adapted from data from the Office for National Statistics licensed under the Open Government Licence v.1.0.http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

NHS UK - COVID-19 Daily Deaths

This section contains information on deaths of patients who have died in hospitals in England and had tested positive for COVID-19 at time of death. All deaths are recorded against the date of death rather than the date the deaths were announced. Interpretation of the figures should take into account the fact that totals by date of death, particularly for most recent days, are likely to be updated in future releases. For example as deaths are confirmed as testing positive for COVID-19, as more post-mortem tests are processed and data from them are validated. Any changes are made clear in the daily files.

These figures do not include deaths outside hospital, such as those in care homes. This approach makes it possible to compile deaths data on a daily basis using up to date figures.

Dataset Content

These figures will be updated at 2pm each day and include confirmed cases reported at 5pm the previous day. Confirmation of COVID-19 diagnosis, death notification and reporting in central figures can take up to several days and the hospitals providing the data are under significant operational pressure. This means that the totals reported at 5pm on each day may not include all deaths that occurred on that day or on recent prior days.

The original dataset is sourced directly from the NHS source site, this original dataset is then cleaned and converted to a csv format available for inclusion into a Kaggle notebook.

There are 3 files considered within the data :- 1. Fatalities_by_age_uk 2.Fatalities_by_region_uk 3.Fatalities_by_trust_uk

Data runs from March 1st up to the current day. Any discrepancies will be outlined. The first is cumulative for any previous days leading up to of relevance. The following days are not cumulative and represent the updated value for the date under consideration.

A start kernel is provided to demonstrate using the dataset.

Citations

This dataset is sourced from the NHS statistical work areas:- https://www.england.nhs.uk/statistics/statistical-work-areas/

This dataset has been sourced and provided to aid in the following competition:- https://www.kaggle.com/c/covid19-global-forecasting-week-4

Context

Complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. It is updated daily and includes data on confirmed cases, deaths, hospitalizations, testing, and vaccinations as well as other variables of potential interest.

Content

The variables represent all data related to confirmed cases, deaths, hospitalizations, and testing, as well as other variables of potential interest.
the columns are: iso_code, continent, location, date, total_cases, new_cases, new_cases_smoothed, total_deaths, new_deaths, new_deaths_smoothed, total_cases_per_million, new_cases_per_million, new_cases_smoothed_per_million, total_deaths_per_million, new_deaths_per_million, new_deaths_smoothed_per_million, reproduction_rate, icu_patients, icu_patients_per_million, hosp_patients, hosp_patients_per_million, weekly_icu_admissions, weekly_icu_admissions_per_million, weekly_hosp_admissions, weekly_hosp_admissions_per_million, total_tests, new_tests, total_tests_per_thousand, new_tests_per_thousand, new_tests_smoothed, new_tests_smoothed_per_thousand, positive_rate, tests_per_case, tests_units, total_vaccinations, people_vaccinated, people_fully_vaccinated, new_vaccinations, new_vaccinations_smoothed, total_vaccinations_per_hundred, people_vaccinated_per_hundred, people_fully_vaccinated_per_hundred, new_vaccinations_smoothed_per_million, stringency_index, population, population_density, median_age, aged_65_older, aged_70_older, gdp_per_capita, extreme_poverty, cardiovasc_death_rate, diabetes_prevalence, female_smokers, male_smokers, handwashing_facilities, hospital_beds_per_thousand, life_expectancy, human_development_index

Acknowledgements/ Data Source

https://systems.jhu.edu/research/public-health/ncov/ https://www.ecdc.europa.eu/en/publications-data/download-data-hospital-and-icu-admission-rates-and-current-occupancy-covid-19 https://coronavirus.data.gov.uk/details/healthcare https://covid19tracker.ca/ https://healthdata.gov/dataset/covid-19-reported-patient-impact-and-hospital-capacity-state-timeseries https://ourworldindata.org/coronavirus-testing#our-checklist-for-covid-19-testing-data

Context

Public Health England (PHE) coronavirus cases reported daily. This data shows case numbers as reported to PHE. Cases includes people who have recovered.

Content

DateVal : dd/mm/yyyy CMODateCount : The number of cases reported for the day CumCases: The cumulative number of cases IncreasePercent: The percentage increase in cases from the previous day DeathPercent: The percentage increase/decrease in daily deaths from the previous day CumCases7DayAvg: 7 day moving average of the cumulative number of cases CumDeaths7DayAvg: 7 day moving average of the cumulative number of deaths DailyDeath7DayAvg: 7 day moving average of the daily number of deaths

IncreasePercent and moving 7 day averages are calculated fields added to the original source.

Acknowledgements

https://www.gov.uk/government/publications/covid-19-track-coronavirus-cases https://coronavirus.data.gov.uk/

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

Multiple linear regression table with R2, coefficient and p value for input features (population density, normalized busy airport, pre-infected count, pre-death count) and observed factors (post-infected count and post-death count).

Context

A new coronavirus designated 2019-nCoV was first identified in Wuhan, the capital of China's Hubei province. People developed pneumonia without a clear cause and for which existing vaccines or treatments were not effective. The virus has shown evidence of human-to-human transmission. You can use this data for Analysis

Content

City Province Country LastUpdate keyID Confirmed Deaths

Acknowledgements

https://rapidapi.com/KishCom/api/covid-19-coronavirus-statistics

Cover Image

https://c.files.bbci.co.uk/D505/production/_115033545_gettyimages-1226314512.jpg

Inspiration

You can use this dataset for analyzing the Covid19 cases in different countries...

PIONEER: The impact of ethnicity and multi-morbidity on COVID-related outcomes; a primary care supplemented hospitalised dataset Dataset number 3.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 65million cases and more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) and death. Evidence suggests that older patients, those from some ethnic minority groups and those with multiple long-term health conditions have worse outcomes. This secondary care COVID dataset contains granular demographic and morbidity data, supplemented from primary care records, to add to the understanding of patient factors on disease outcomes.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 and 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records and clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding and following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

This publication was archived on 12 October 2023. Please see the Viral Respiratory Diseases (Including Influenza and COVID-19) in Scotland publication for the latest data. This dataset provides information on number of new daily confirmed cases, negative cases, deaths, testing by NHS Labs (Pillar 1) and UK Government (Pillar 2), new hospital admissions, new ICU admissions, hospital and ICU bed occupancy from novel coronavirus (COVID-19) in Scotland, including cumulative totals and population rates at Scotland, NHS Board and Council Area levels (where possible). Seven day positive cases and population rates are also presented by Neighbourhood Area (Intermediate Zone 2011). Information on how PHS publish small are COVID figures is available on the PHS website. Information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system is provided in this publication. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. COVID-19 was declared a pandemic by the World Health Organisation on 12 March 2020. We now have spread of COVID-19 within communities in the UK. Public Health Scotland no longer reports the number of COVID-19 deaths within 28 days of a first positive test from 2nd June 2022. Please refer to NRS death certificate data as the single source for COVID-19 deaths data in Scotland. In the process of updating the hospital admissions reporting to include reinfections, we have had to review existing methodology. In order to provide the best possible linkage of COVID-19 cases to hospital admissions, each admission record is required to have a discharge date, to allow us to better match the most appropriate COVID positive episode details to an admission. This means that in cases where the discharge date is missing (either due to the patient still being treated, delays in discharge information being submitted or data quality issues), it has to be estimated. Estimating a discharge date for historic records means that the average stay for those with missing dates is reduced, and fewer stays overlap with records of positive tests. The result of these changes has meant that approximately 1,200 historic COVID admissions have been removed due to improvements in methodology to handle missing discharge dates, while approximately 820 have been added to the cumulative total with the inclusion of reinfections. COVID-19 hospital admissions are now identified as the following: A patient's first positive PCR or LFD test of the episode of infection (including reinfections at 90 days or more) for COVID-19 up to 14 days prior to admission to hospital, on the day of their admission or during their stay in hospital. If a patient's first positive PCR or LFD test of the episode of infection is after their date of discharge from hospital, they are not included in the analysis. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. Data visualisation of Scottish COVID-19 cases is available on the Public Health Scotland - Covid 19 Scotland dashboard. Further information on coronavirus in Scotland is available on the Scottish Government - Coronavirus in Scotland page, where further breakdown of past coronavirus data has also been published.

The features in the order shown under “Feature name” are: GDP, inter-state distance based on lat-long coordinates, gender, ethnicity, quality of health care facility, number of homeless people, total infected and death, population density, airport passenger traffic, age group, days for infection and death to peak, number of people tested for COVID-19, days elapsed between first reported infection and the imposition of lockdown measures at a given state.

OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 2.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases & more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) & death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID OMOP dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date. This is a subset of data in OMOP format.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – August 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data. Further OMOP data available as an additional service.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

PIONEER: Deeply-phenotyped hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 4.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases& more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS)& death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records& clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Provisional counts of the number of deaths registered in England and Wales, including deaths involving coronavirus (COVID-19), by local authority, health board and place of death in the latest weeks for which data are available. The occurrence tabs in the 2021 edition of this dataset were updated for the last time on 25 October 2022.

Values of parameters.