As of July 30, 2020, there had been more confirmed cases of coronavirus (COVID-19) among women in England compared to men. The data shows that there are few confirmed cases among children, while there have been approximately nine thousand confirmed cases for both men and women aged 80 to 84 years.

As of July 30, there have been 302,301 confirmed coronavirus cases in the UK, and the regional breakdown of cases can be found here. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

The number of COVID vaccinations carried out and payments made for these vaccinations to individual pharmacies, listed by their ODS code and with full postal address details. Could you provide the data for the month of January 2024 in EXCEL format please. The data should be: Column1--Administration Month Column2--ODS Code Column3--Pharmacy Name Column4--Pharmacy Trading Name Column5--Pharmacy Address Column6--Pharmacy Post Code Column7--Number of Vaccinations Claimed Column8--Number of Vaccinations Paid Column9--Payment Amount GB Response A copy of the information is attached. The NHSBSA calculates payments for Covid-19 vaccinations to Pharmacies and Primary Care Network (PCN) providers in England. Covid-19 vaccination data is keyed in via Point of Care (POC) Systems and they are transferred to the NHSBSA Manage Your Service (MYS) application. Each month, vaccine providers submit claims to request payment based on the data that has been transferred into MYS. To be paid in a timely fashion, such claims must be submitted during a specified declaration submission period. Should claims be submitted outside of the submission period, they will be processed in the following period. This means that in some cases, there is a difference between the number of vaccines that have been 'claimed' and the number that have been 'paid'. Both the number of 'claimed' and 'paid' vaccinations have been reported in this request. When considering the nature of the vaccine data, there are several ways it can be reported over time: Administration Month - This is the month in which the vaccine was administered to the patient. Payment Month - This is the month in which the payment was made to the vaccine dispenser. Note that all payments for Pharmacies are paid one month later than those for PCN providers. Keying Month - This is the month in which the vaccine record first appeared on the MYS system. Submission/Claim Month - This is the month in which the claim for payment for a vaccination occurred. For example, suppose that a PCN patient is given a Covid-19 vaccination dose 1 in January (Administration Month) and then the paper record of this is misplaced for a while. The record is found and keyed into a POC system during February (Keying Month). The Provider is allowed to claim for keying during February in the first five days of March, but they're slightly late and authorise the claim on 7 March (Submission Month). As the claim is outside the submission window, it is not paid in March, it will instead be processed during April (Payment Month). Another example could be a Pharmacy patient is given a Covid-19 vaccination dose 1 in January (Administration Month), keyed in January (Keying Month), then submitted in February (Submission Month) and then payments are calculated in February, however as this is for a pharmacy, the payments are held back and not paid until March (Payment Month). For the purposes of this request, we have chosen to report by Administration Month. Data included in this request is limited to vaccinations carried out by Pharmacies only. Data included in this request is also limited to vaccinations administered in January 2024. The latest data used is a snapshot of the MYS system data that was taken on 6 February 2024. This is the snapshot of data taken after the January 2024 submission period that was used to calculate payments. Pharmacy name and address are as held at this date. This payment data does not include any adjustments made by NHSBSA Provider Assurance as part of post-payment verification exercises. These adjustments are made at account level and may relate to several months of activity. Payment data includes payments made and those scheduled for payment in the future. Payments comprise an Item of Service (IoS) fee and potentially a supplementary fee. Payments do not relate to the value of the drugs dispensed. The total used for the payment calculation may not match the totals shown in 'live' POC systems or MYS that continue to receive updates after the snapshot used to calculate payments was taken. Vaccination records are limited to those which have been associated with a declaration submission. This may include late submission declarations received after the deadline for declarations such records are not processed until the next month. Please note that some vaccinations attract a supplementary fee, so it is not possible to determine the number of vaccinations by dividing the total paid by the basic IoS fee. It is possible for new records from old administration months to be entered in the future, thus the totals here for each administration month could change when more data is processed.

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 distribution of farms in Great Britain by number of confirmed BSE (Bovine Spongiform Encephalopathy) cases (excluding dealers and survey cases) between 1988 and 2016. The dataset includes the following fields: Number of cases; Number of farms; Percent (of total farms). Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk.

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.

Findings from the Coronavirus (COVID-19) Infection Survey for England.

[The spreadsheet is organised into two parts. The first contains a broad set of annual data covering the UK national accounts and other financial and macroeconomic data stretching back in some cases to the late 17th century. The second and third sections cover the available monthly and quarterly data for the UK to facilitate higher frequency analysis on the macroeconomy and the financial system. The spreadsheet attempts to provide continuous historical time series for most variables up to the present day by making various assumptions about how to link the historical components together. But we also have provided the various chains of raw historical data and retained all our calculations in the spreadsheet so that the method of calculating the continuous times series is clear and users can construct their own composite estimates by using different linking procedures., This dataset contains a broad set of historical data covering the UK national accounts and other financial and macroeconomic data stretching back in some cases to the late 17th century.]

Number of BSE (Bovine Spongiform Encephalopathy) cases from passive and active surveillance in England in the current and previous year, by county. The dataset includes the fields: County; Passive Surveillance (suspect cases) for both 2014 and 2015; Active Surveillance (routine testing) for 2014 and 2015. Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk. Attribution statement:

This dataset lists the number of bulls in which BSE (Bovine Spongiform Encephalopathy) has been confirmed, by breed (with crosses included under main breed type). The following fields are included: Breed; Total (number of cases). Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk.

Number of cases from passive and active surveillance of BSE (Bovine Spongiform Encephalopathy) in GB by year. This dataset includes the fields: Year; Passive (number of cases detected by passive surveillance - suspects); Active (number of cases from active surveillance - routine sampling of all >48 months of age fallen stock); Total (all cases). Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk.

IntroductionFollowing the identification of Local Area Energy Planning (LAEP) use cases, this dataset lists the data sources and/or information that could help facilitate this research. View our dedicated page to find out how we derived this list: Local Area Energy Plan — UK Power Networks (opendatasoft.com)

Methodological Approach Data upload: a list of datasets and ancillary details are uploaded into a static Excel file before uploaded onto the Open Data Portal.

Quality Control Statement

Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology

Assurance Statement The Open Data Team and Local Net Zero Team worked together to ensure data accuracy and consistency.

Other Download dataset information: Metadata (JSON)

Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/

Please note that "number of records" in the top left corner is higher than the number of datasets available as many datasets are indexed against multiple use cases leading to them being counted as multiple records.

This is the second publication of adult critical care data, which forms part of Hospital Episode Statistics (HES) and is collected as part of the Critical Care Minimum Data Set (CCMDS). It covers critical care periods ending between 1 April 2009 and 31 March 2010, and draws on records submitted by providers as an attachment to the inpatient record. During the period covered by this report, not all NHS trusts with critical care capacity have completed data submissions, so data quality and coverage is variable in some cases. Publishing the HES critical care data as experimental statistics allows for discussion, analysis and promotion of the dataset, which in turn should lead to improved coverage and data quality.

The COVID-19 Health Inequalities Monitoring in England (CHIME) tool brings together data relating to the direct impacts of coronavirus (COVID-19) on factors such as mortality rates, hospital admissions, confirmed cases and vaccinations.

By presenting inequality breakdowns - including by age, sex, ethnic group, level of deprivation and region - the tool provides a single point of access to:

• show how inequalities have changed during the course of the pandemic and what the current cumulative picture is
• bring together data in one tool to enable users to access and use the intelligence more easily
• provide indicators with a consistent methodology across different data sets to facilitate understanding
• support users to identify and address inequalities within their areas, and identify priority areas for recovery

In the March 2023 update, data has been updated for deaths, hospital admissions and vaccinations. Data on inequalities in vaccination uptake within upper tier local authorities has been added to the tool for the first time. This replaces data for lower tier local authorities, published in December 2022, allowing the reporting of a wider range of inequality breakdowns within these areas.

Please send any questions or comments to PHA-OHID@dhsc.gov.uk

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

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These files comprise the publicly available data for the COG-UK hospital-onset COVID-19 infection study. The individual CSV files provided are: - HOCI_public_dataset: Anonymized version of main study dataset, with one row per HOCI case included in the final analysis - HOCI_public_varlist: Variable descriptions for main study dataset - epi_data_combined: Weekly data on total SARS-CoV-2 +ve (cov_pos_epi) and -ve (cov_neg_epi) inpatients at each study site -community_incidence_summary: Weekly local community incidence data for each study site, per 100,000 people per week, obtained from UK government testing dashboard and weighted according to outer postcodes of inpatients at each site.

Notes on anonymisation: HOCI_public_dataset is an anonymised version of the main HOCI study database. In order to fully anonymise individuals, and because the focus of the study was on infection control actions rather than patient outcomes, all individual-level patient demographic and clinical characteristics have been removed. Site and ward names have been changed to anonymized codes, and all free text fields have been removed as some of these contained unblinded details of hospitals and wards. All date fields have been removed, with study week of SARS-CoV-2 +ve test result for each HOCI case provided.

Notes on acronyms: In ‘HOCI_public_varlist’, the following acronyms are used: AGP, aerosol-generating procedure CR, contact restrictions CT, contact tracing DIPC, Director of IPC HCAI, healthcare-associated infection HCW, healthcare worker IPC, infection prevention and control SR, sequence report SRO, sequence report output QM, quality management

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.

Table showing the number of animal BSE (Bovine Spongiform Encephalopathy) cases, and the number of farms with BSE cases. The table also breaks down the type of farms where cases have been detected, and includes age of the oldest and youngest animals with detected cases. The dataset includes the following fields: Total farms (number of farms with cases); Total cases (of BSE); 'Dairy Farms, Suckler Farms, Mixed Farms, Not Recorded' (Column B gives the number of farms in each type with cases, and Column C gives the percentage of these farms in each category); 'Dairy Farms, Suckler Farms, Mixed cases, Not recorded' (Column B gives the number of farms in each type with cases, and Column C gives the percentage of these farms in each category); Purchased cases (how many cases were from animals purchased); Homebred cases (how many cases were from homebred animals), Not recorded (Column B gives the number of cases where the purchase/homebred data was not record, and Column C gives the percentage); Confirmed dairy herd incidence (as a % of total); Confirmed suckler herd incidence (as a % of the total); Confirmed total herd incidence (as a % of the total); youngest confirmed case (age in months); Oldest confirmed case (age in months).

Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk. Attribution statement: