On January 12, 2021, over 4.5 thousand individuals in the UK were admitted to hospital with coronavirus (COVID-19), the highest single amount since the start of the pandemic. The daily hospital cases started to rise significantly at the end of 2020 and into January 2021, however since then the number of hospitalizations fell dramatically as the UK managed to vaccinate millions against COVID-19. Overall, since the pandemic started around 994 thousand people in the UK have been hospitalized with the virus.

The total number of cases in the UK can be found here. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

As of August 11, 2022, over 23.4 million people in the United Kingdom had tested positive for COVID-19 with 3,948 cases reported on that day. During the large wave of cases in the winter 2020/21, the number of daily hospitalizations also peaked with both graphs taking similar shapes. Although hospitalizations did increase, rising case numbers at the end of 2021 did not fully corresponded into a similarly large surge as the previous winter, as experts pointed to the effectiveness of being vaccinated against COVID-19.

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

As of October 6, 2022, 11,641 confirmed COVID-19 patients were in hospital in the United Kingdom. The number of COVID patients in hospitals first peaked at over 21.6 thousand on April 12, 2020 and dropped as low as 772 on September 11, 2020. However, the number of patients reached a new peak in the winter of 2020/21 with over 39.2 thousand patients in hospital on January 18, 2021.

The total number of cases in the UK can be found here. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

View daily updates and historical trends for UK Coronavirus Cases Currently Hospitalized. from United Kingdom. Source: Our World in Data. Track economic d…

BackgroundMandatory COVID-19 certification, showing proof of vaccination, negative test, or recent infection to access to public venues, was introduced at different times in the four countries of the UK. We aim to study its effects on the incidence of cases and hospital admissions.MethodsWe performed Negative binomial segmented regression and ARIMA analyses for four countries (England, Northern Ireland, Scotland and Wales), and fitted Difference-in-Differences models to compare the latter three to England, as a negative control group, since it was the last country where COVID-19 certification was introduced. The main outcome was the weekly averaged incidence of COVID-19 cases and hospital admissions.ResultsCOVID-19 certification led to a decrease in the incidence of cases and hospital admissions in Northern Ireland, as well as in Wales during the second half of November. The same was seen for hospital admissions in Wales and Scotland during October. In Wales the incidence rate of cases in October already had a decreasing tendency, as well as in England, hence a particular impact of COVID-19 certification was less obvious. Method assumptions for the Difference-in-Differences analysis did not hold for Scotland. Additional NBSR and ARIMA models suggest similar results, while also accounting for correlation in the latter. The assessment of the effect in England itself leads one to believe that this intervention might not be strong enough for the Omicron variant, which was prevalent at the time of introduction of COVID-19 certification in the country.ConclusionsMandatory COVID-19 certification reduced COVID-19 transmission and hospitalizations when Delta predominated in the UK, but lost efficacy when Omicron became the most common variant.

All data relating to “Coronavirus (COVID-19) hospital admissions by vaccination and pregnancy status, England”.

The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

Data forming the COVID-19 SARI-Watch data set relate to demographic, risk factor, treatment, and outcome information for patients admitted to hospital with a confirmed COVID-19 diagnosis, as recorded in the PHE COVID-19 SARI-Watch Surveillance System.

SARI-Watch data are to be collected for the purposes of direct care, service monitoring, planning and research in response to the spread of COVID-19, including for the following purposes identified in the COVID-19 Directions (see below): •understanding information about patient access to health services and adult social care services as a direct or indirect result of COVID-19 and the availability and capacity of those services •monitoring and managing the response to COVID-19 by health and social care bodies and the Government, including providing information to the public about COVID-19 and its effectiveness, and information about capacity, medicines, equipment, supplies, services and the workforce within the health services and adult social care services •research and planning in relation to COVID-19, such as providing COVID-19 diagnosis.

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 Standard wording

NHS Digital will only disseminate SARI-Watch data collected from PHE where the information is linked to other information controlled by NHS Digital.

Context

COVID-19 is a Pandemic which was spread worldwide in the early months of 2020, Which has had a major impact on the United Kingdom. As the UK has recently carried out wide spread vaccination and ended Lockdown I am providing the recent COVID-19 figures.

Content

Several Datasets are provided, focusing on Deaths, Cases, Hospitalisation and Vaccination. Files often protray the same information but from a different reference point. For example for Deaths there is one displaying figures from people who died using there positive date as a reference point, whereas the other is using the date of death.

Acknowledgements

These datasets was scrapped off the UK Gov website in regards to COVID-19. For those looking to build a more complex project using a constant data flow, they do provide an API which may assist.

Inspiration

Possible area to explore are: What was the Impact of Vaccines on the COVID-19 Pandemic? What was the Impact of a Lockdown on the COVID-19 Pandemic? Which Nation managed the spread of COVID-19 the best?

Licence

Open Government Licence V3.0

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.

Notes:

Covid 19 related hospital admissions to University Hospitals Leicester (UHL) for Leicester residents. Age band rates per 100,000 population are based on ONS 2019 population estimates.Data is updated weekly.Note: This dataset will soon be archived and not subject to updates. A replacement dataset is currently under development.

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

Number of weekly Covid-19 related hospital admissions to University Hospitals Leicester (UHL) for Leicester residents. Data where the count is less than 3 admissions have been suppressed to "..". Data is updated weekly and previous week data is subject to change when data is refreshed.Note: This dataset will soon be archived and not subject to updates. A replacement dataset is currently under development.

Population, population density and confirmed COVID-19 hospitalisation rates/100,000 population at six time points during the first wave of the pandemic.

Notes:

These indicators are designed to accompany the SHMI publication. COVID-19 activity is included in the SHMI if the discharge date is on or after 1 September 2021. Contextual indicators on the number of provider spells which are related to COVID-19 and on the number of provider spells as a percentage of pre-pandemic activity (January 2019 – December 2019) are produced to support the interpretation of the SHMI. These indicators are being published as official statistics in development. Official statistics in development are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. Notes: 1. There is a shortfall in the number of records for East Lancashire Hospitals NHS Trust (trust code RXR) and Harrogate and District NHS Foundation Trust (trust code RCD). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. 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. 3. Royal Surrey County Hospital NHS Foundation Trust (trust code RA2) has a high percentage of records with no data for secondary diagnoses. This is having a large impact on this trust’s data and values for this trust should therefore be interpreted with caution. 4. There is a high percentage of invalid diagnosis codes for Chesterfield Royal Hospital NHS Foundation Trust (trust code RFS), East Lancashire Hospitals NHS Trust (trust code RXR), Portsmouth Hospitals University NHS Trust (trust code RHU), and University Hospitals Plymouth NHS Trust (trust code RK9). Values for these trusts should therefore be interpreted with caution. 5. 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 SHMI background quality report. 6. 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.