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on GitHub https://github.com/VictimOfMaths/COVIDmapper and uploaded to this record4) Index of Multiple Deprivation No longer updated - preliminary analysis of the inequality impacts of COVID-19 based on Local Authority level cases and levels of deprivation. 5) Socioeconomic inequalities. No longer updated (unless ONS release more data) - Analysis of published ONS figures of COVID-19 and other cause mortality in 2020 compared to previous years by deprivation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/

As of January 12, 2023, COVID-19 has been responsible for 202,157 deaths in the UK overall. The North West of England has been the most affected area in terms of deaths at 28,116, followed by the South East of England with 26,221 coronavirus deaths. Furthermore, there have been 22,264 mortalities in London as a result of COVID-19.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

This dataset shows the provisional COVID-19 Death registrations and occurrences by local authority and health board in England and Wales. This dataset has been prepared by Office for National Statistics.

Context

• Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus SARS-CoV2.
• Person to person transmission occurs via several different modes, mainly when people are in close proximity to one another through respiratory droplets.
• Mitigations by various countries have been put into place to limit the spread of this virus.

Content

• ConfirmedCasesByDateReported.csv
• ConfirmedCasesBySpecimenDate.csv
• Deaths.csv
• PatientNewAdmissions.csv
• PatientsInHospital.csv
• PatientsMVBeds.csv
• PCRTesting.csv
• Vaccinations.csv
• VaccinationsDaily.csv

Acknowledgements and Collection Methodology

Data downloaded from https://coronavirus.data.gov.uk

Version

• Version 11 - 25 - Various Files Updated.
• Version 10 - Added VaccinationsDaily File, data upto and including the 20th Jan 2021.
• Version 9 - Updated Deaths file, data upto and including the 20th Jan 2021.
• Version 8 - Updated ConfirmedCasesByDateReported and ConfirmedCasesBySpecimenDate files, data upto and including the 17th to 19th Jan 2021 respectively.
• Version 7 - Updated PatientNewAdmissions, PatientsInHospital and PatientsMVBeds files, data upto and including the 12th to 15th Jan 2020 depending on file.
• Version 6 - Updated PCR Testing file, data upto and including the 14th Jan 2021.
• Version 4 - Updated Vaccinations file, data upto and including the 3rd Jan 2021.
• Version 3 - Updated to include data unto and including the 28th December 2020. Additionally added data on the progress of Vaccinations.
• Version 2 - Updated to include data unto and including the 3rd November 2020.

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.

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. The number of cases in the UK increased significantly at the end of 2021. On January 13, 2023, the number of confirmed cases in the UK amounted to 24,243,393. COVID deaths among highest in Europe There were 202,157 confirmed coronavirus deaths in the UK as of January 13, 2023. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Current infection rate in Europe The current infection rate in the UK was 50 cases per 100,000 population in the last seven days as of January 16. San Marino had the highest seven day rate of infections in Europe at 336.

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.

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!

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.

COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.

Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) 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. This dataset provides 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. 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. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

Estimates of the risk of hospital admission for coronavirus (COVID-19) and death involving COVID-19 by vaccination status, overall and by age group, using anonymised linked data from Census 2021. Experimental Statistics.

Outcome definitions

For this analysis, we define a death as involving COVID-19 if either of the ICD-10 codes U07.1 (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified) is mentioned on the death certificate. Information on cause of death coding is available in the User Guide to Mortality Statistics. We use date of occurrance rather than date of registration to give the date of the death.

We define COVID-109 hospitalisation as an inpatient episode in Hospital Episode Statistics where the primary diagnosis was COVID-19, identified by the ICD-19 codes (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified). Where an individual had experienced more than one COVID-19 hospitalisation, the earliest that occurred within the study period was used. We define the date of COVID-19 hospitalisation as the start of the hospital episode.

ICD-10 code

U07.1 :

COVID-19, virus identified

U07.2:

COVID-19, virus not identified

Vaccination status is defined by the dose and the time since the last dose received

Unvaccinated:

no vaccination to less than 21 days post first dose

First dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post first dose or less than 21 days post second dose

First dose 3+ months:

more than or equal to 91 days post first dose to less than 21 days post second dose

Second dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post second dose or less than 21 days post third dose

Second dose 3-6 months:

more than or equal to 91 days post second dose to earliest of less than 182 days post second dose or less than 21 days post third dose

Second dose 6+ months:

more than or equal to 182 days post second dose to less than 21 days post third dose

Third dose 21 days to 3 months:

more than or equal to 21 days post third dose to less than 91 days post third dose

Third dose 3+ months:

more than or equal to 91 days post third dose

Model adjustments

Three sets of model adjustments were used

Age adjusted:

age (as a natural spline)

Age, socio-demographics adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status)

Fully adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status), plus health-related characteristics (disability, self-reported health, care home residency, number of QCovid comorbidities (grouped), BMI category, frailty flag and hospitalisation within the last 21 days.

Age

Age in years is defined on the Census day 2021 (21 March 2021). Age is included in the model as a natural spline with boundary knots at the 10th and 90th centiles and internal knots at the 25th, 50th and 75th centiles. The positions of the knots are calculated separately for the overall model and for each age group for the stratified model.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

Reports of Human immunodeficiency virus (HIV) diagnoses, diseases and deaths in HIV-infected persons

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.

CVD-COVID-UK, co-ordinated by the British Heart Foundation (BHF) Data Science Centre (https://bhfdatasciencecentre.org/), is one of the NIHR-BHF Cardiovascular Partnership’s National Flagship Projects.

CVD-COVID-UK aims to understand the relationship between COVID-19 and cardiovascular diseases through analyses of de-identified, pseudonymised, linked, nationally collated health datasets across the four nations of the UK. The consortium has over 400 members across more than 50 institutions including data custodians, data scientists and clinicians, all of whom have signed up to an agreed set of principles with an inclusive, open and transparent ethos.

Approved researchers access data within secure trusted/secure research environments (TREs/SDEs) provided by NHS England (England), the National Safe Haven (Scotland), the Secure Anonymised Information Linkage (SAIL) Databank (Wales) and the Honest Broker Service (Northern Ireland). A dashboard of datasets available in each nation’s TRE can be found here: https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/

This dataset represents the linked datasets in SAIL Databank’s TRE for Wales and contains the following datasets: • Welsh Longitudinal GP Dataset - Welsh Primary Care (Daily COVID codes only) (GPCD) • Welsh Longitudinal General Practice Dataset (WLGP) - Welsh Primary Care • Critical Care Dataset (CCDS) • Emergency Department Dataset Daily (EDDD) • Emergency Department Dataset (EDDS) • Outpatient Database for Wales (OPDW) • Outpatient Referral (OPRD) • Patient Episode Dataset for Wales (PEDW) • COVID-19 Test Results (PATD) • COVID-19 Test Trace and Protect (CTTP) - Legacy • COVID-19 Shielded People List (CVSP) • SARS-CoV-2 viral sequencing data (COG-UK data)-Lineage/Variant Data-Wales (CVSD) • Covid Vaccination Dataset (CVVD) • Annual District Death Daily (ADDD) • Annual District Death Extract (ADDE) • COVID-19 Consolidated Deaths (CDDS) • Intensive Care National Audit and Research Centre (ICCD) - Legacy - COVID only • Intensive Care National Audit and Research Centre (ICNC) • Welsh Dispensing Dataset (WDDS) - Legacy • Annual District Birth Extract (ADBE) • Maternity Indicators Dataset (MIDS) • National Community Child Health Database (NCCHD) • Care Home Dataset (CARE) • Congenital Anomaly Register and Information Service (CARS) • Referral to Treatment Times (RTTD) • SAIL Dementia e-Cohort (SDEC) • Welsh Ambulance Services NHS Trust (WASD) • Welsh Demographic Service Dataset (WDSD) • Welsh Results Reports Service (WRRS) • ONS 2011 Census Wales (CENW)

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...

BackgroundThis paper asks whether Dynamic Causal modelling (DCM) can predict the long-term clinical impact of the COVID-19 epidemic. DCMs are designed to continually assimilate data and modify model parameters, such as transmissibility of the virus, changes in social distancing and vaccine coverage—to accommodate changes in population dynamics and virus behavior. But as a novel way to model epidemics do they produce valid predictions? We presented DCM predictions 12 months ago, which suggested an increase in viral transmission was accompanied by a reduction in pathogenicity. These changes provided plausible reasons why the model underestimated deaths, hospital admissions and acute-post COVID-19 syndrome by 20%. A further 12-month validation exercise could help to assess how useful such predictions are.Methodswe compared DCM predictions—made in October 2022—with actual outcomes over the 12-months to October 2023. The model was then used to identify changes in COVID-19 transmissibility and the sociobehavioral responses that may explain discrepancies between predictions and outcomes over this period. The model was then used to predict future trends in infections, long-COVID, hospital admissions and deaths over 12-months to October 2024, as a prelude to future tests of predictive validity.FindingsUnlike the previous predictions—which were an underestimate—the predictions made in October 2022 overestimated incidence, death and admission rates. This overestimation appears to have been caused by reduced infectivity of new variants, less movement of people and a higher persistence of immunity following natural infection and vaccination.Interpretationdespite an expressive (generative) model, with time-dependent epidemiological and sociobehavioral parameters, the model overestimated morbidity and mortality. Effectively, the model failed to accommodate the “law of declining virulence” over a timescale of years. This speaks to a fundamental issue in long-term forecasting: how to model decreases in virulence over a timescale of years? A potential answer may be available in a year when the predictions for 2024—under a model with slowly accumulating T-cell like immunity—can be assessed against actual outcomes.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.