Provisional counts of the number of deaths and age-standardised mortality rates involving the coronavirus (COVID-19) in England and Wales. Figures are provided by age, sex, geographies down to local authority level and deprivation indices.

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.

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.

About the Data:

A year ago, when WHO declared COVID-19 outbreak a pandemic, countries in WHO South-East Asia Region were either responding to their first cases of importation or cluster of cases or keeping a strict vigil against importation of the new coronavirus.

The following months were unprecedented, and for many reasons. Scientists, experts, governments, societies, communities and even individuals responded to the new virus with urgency and measures never witnessed before.

Metadata:

ID: Unique Identifier Country: Name of Country TotalCases: Total Number of cases recorded so far TotalDeaths: Total Deaths recorded so far TotalRecovered: How many people survived ActiveCases: Number of people who currently has the virus TotalCasesPerMillion: How many cases are recorded per million individual TotalDeathsPerMillion: How many deaths recorded per million individual TotalTests: Total number of COVID19 tests conducted RTPCR + RAT + any other tests TotalTestsPerMillion: How many tests were conducted per million individual TotalPopulation: Population of the country

Acknowledgements:

This dataset was collected from: https://www.worldometers.info/coronavirus/#countries

Call For Code:

Fellow Data Scientist and ML engineers, can you identify which countries are doing relatively well and which ones need immediate attention? Your insights can save millions of lives in Asia!

In early-February, 2020, the first cases of the coronavirus (COVID-19) were reported in the United Kingdom (UK). The number of cases in the UK has since risen to 24,243,393, with 1,062 new cases reported on January 13, 2023. The highest daily figure since the beginning of the pandemic was on January 6, 2022 at 275,646 cases.

COVID deaths in the UK COVID-19 has so far been responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK has one of the highest death toll from COVID-19 in Europe. As of January 13, the incidence of deaths in the UK is 298 per 100,000 population.

Regional breakdown The South East has the highest amount of cases in the country with 3,123,050 confirmed cases as of January 11. London and the North West have 2,912,859 and 2,580,090 cases respectively.

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

We examined the construct validity of a 28-item survey that was designed to measure inner wellbeing (i.e., individuals’ thoughts and feelings about what they can do and be; White et al., 2014) among individuals in (1) the Global South nation of India (n = 205), (2) the Global North nation of the United Kingdom (n = 392), and (3) the nation of Greece, which is not readily categorized as Global South or Global North (n = 354) during COVID lockdown. Using a series of multiple-group confirmatory factor analyses via LISREL 10.20 (Joreskog & Sorbom, 2019), we tested the hypothesis that a model specifying seven factors (i.e., economic confidence, agency/participation, social connections, close relationships, physical/mental health, competence/self-worth, and values/meaning as intercorrelated domains) would provide a significantly better fit to the correlational data than would a model specifying a one factor (i.e., unidimensional inner wellbeing).

Number of excess deaths, including deaths due to coronavirus (COVID-19) and due to other causes. Including breakdowns by age, sex and geography.

Indonesia Number of Bed: Covid-19: Available: South East Sulawesi data was reported at 540.000 Unit in 09 Oct 2022. This stayed constant from the previous number of 540.000 Unit for 08 Oct 2022. Indonesia Number of Bed: Covid-19: Available: South East Sulawesi data is updated daily, averaging 610.000 Unit from Aug 2021 (Median) to 09 Oct 2022, with 370 observations. The data reached an all-time high of 913.000 Unit in 07 Aug 2021 and a record low of 514.000 Unit in 31 Jul 2022. Indonesia Number of Bed: Covid-19: Available: South East Sulawesi data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Indonesia Premium Database’s Health Sector – Table ID.HLA013: Number of Available Hospital Bed: Covid-19: by Province (Discontinued).

This study consists of transcripts of interviews conducted as part of the research project Identity, Inequality and the Media in Brexit-Covid-19-Britain. These transcripts report verbatim on in-depth interviews conducted with interviewees who live in the South West, East Midlands and North East of England. The interviews were designed to explore the ways in which participants perceived and experienced the social and political impacts of COVID-19 and Brexit. They explore the impact of both the pandemic and Brexit on individuals’ daily lives, their sense of belonging (or not) to place and nation, as well as the ways in which individuals engage with the media. Some of the interviews include a discussion of images that the participants felt captured the processes of Brexit and the pandemic. Furthermore, some of the interviews conducted in the South West focussed specifically on the project artist’s representation of the research themes.

The study authors conducted 90 interviews for this research. Of these, 80 are included in the UKDS version due to confidentiality considerations.

The interviews were conducted between October 2020 and July 2021. During this time England was experiencing national lockdowns and varying degrees of social distancing restrictions due to the COVID-19 pandemic.

This test dataset consists of one table of variables collected in PRIEST dataset. The PRIEST (Pandemic Respiratory Infection Emergency System Triage) Study for Low and Middle-Income Countries (DP – PRIEST)

To ensure hospitals in low- and middle- income countries are not overwhelmed during the COVID-19 pandemic by developing a risk assessment tool for clinicians to quickly decide whether a patient needs emergency care or can be safely sent home.

Carl Marincowitz and colleagues at the University of Sheffield in the United Kingdom and the University of Cape Town in South Africa have developed a risk assessment tool to help emergency clinicians quickly decide whether a patient with suspected COVID-19 needs emergency care or can be safely treated at home to avoid overburdening hospitals particularly in low- and middle- income countries (LMICs). They have used existing data to which they have access on 50,000 patients with suspected COVID-19 infection who sought emergency care in the United Kingdom, South Africa, and Sudan to develop prediction models for specific COVID-19 related outcomes in all income settings. These prediction models have been used to develop risk stratification tools, which enable providers to identify the right level of care and services for distinct subgroups of patients. These have been developed with input from patient and clinical stakeholders. The team have tested the performance of their risk assessment tools for identifying high-risk patients with existing triage methods.

Additional file 4. Confirmed and Deaths Data.

Summary of transmission clusters according to the type of index case.

In 2020 the world was presently burdened with the COVID-19 pandemic. World Health Organization confirms 34,874,744 cases with 1,097,497 deaths (case fatality rate (CFR) 3.1%) were reported in 216 countries. In Indonesia, the number of people who have been infected and the number who have died are approximately 287,008 and 10,740 (CFR 3.7%), respectively, with the most predominant regions being Jakarta (73,700), East Java (43,536) and Central Java (22,440). Many factors can increase the transmission of COVID-19. One of them is wind speed. This data set contains covid-19 data in DKI Jakarta from June 2020 until August 2022 and wind speed in daily power point form. This data can be analyzed to see the correlation between wind speed and the COVID-19 cases. Methods The records of COVID-19 were obtained from the special website of coronavirus for the Daerah Khusus Ibukota (DKI) Jakarta at the Provincial Health Office (https://corona.jakarta.go.id/en/data-pemantauan). The COVID-19 data (n = 4,740) covered six administrative city areas and 261 sub-districts in DKI Jakarta as research locations, namely Kepulauan Seribu, West Jakarta, Central Jakarta, South Jakarta, East Jakarta, and Nort Jakarta. The wind speed data was taken from the Meteorology, Climatology and Geophysics Agency's data website. The wind speed data collected for the period June 2020 to August 2022 (n = 790) was obtained from the POWER LaRC Data Access Viewer, Jakarta. The wind speed data in .csv format is downloaded by specifying the type of daily data unit, data period (time extent), and parameter (in this case wind/pressure). The type of data extraction is POWER Single Point, where the location of the centroid or midpoint of DKI Jakarta Province is determined at latitude -6.1805 and longitude 106.8284. The data of wind speed is in the form of .csv in the form of time series-daily data; it was extracted into a tabular form with two variables, namely wind speed data of 10m and wind speed of 50m (n = 790). The total data (n = 4,740) were grouped into 6 regions with n = 790/region. At the processing steps, the collected data was grouped into variable wind speeds of 10m, wind speeds of 50m, and variables of COVID-19 cases in six areas in DKI Jakarta Province. To find out the distribution of Wind Speed, the daily data before being processed was grouped into per month.

About Dataset: WHO COVID-19 Global Data

This dataset provides comprehensive information on the global COVID-19 pandemic as reported to the World Health Organization (WHO). The dataset is available in comma-separated values (CSV) format and includes the following fields:

Daily cases and deaths by date reported to WHO: WHO-COVID-19-global-data.csv

• Date_reported (Date): The date of reporting to WHO.
• Country_code (String): The ISO Alpha-2 country code.
• Country (String): The name of the country, territory, or area.
• WHO_region (String): The WHO regional office to which the country belongs. WHO Member States are grouped into six WHO regions, including AFRO (Regional Office for Africa), AMRO (Regional Office for the Americas), SEARO (Regional Office for South-East Asia), EURO (Regional Office for Europe), EMRO (Regional Office for the Eastern Mediterranean), and WPRO (Regional Office for the Western Pacific).
• New_cases (Integer): The number of new confirmed cases reported on a given day. This is calculated by subtracting the previous cumulative case count from the current cumulative case count.
• Cumulative_cases (Integer): The total cumulative confirmed cases reported to WHO up to the specified date.
• New_deaths (Integer): The number of new confirmed deaths reported on a given day. Similar to new cases, this is calculated by subtracting the previous cumulative death count from the current cumulative death count.- Cumulative_deaths (Integer): The total cumulative confirmed deaths reported to WHO up to the specified date.

In addition to the COVID-19 case and death data, this dataset also includes valuable information related to COVID-19 vaccinations. The vaccination data consists of the following fields:

Vaccination Data Fields: vaccination-data.csv

• COUNTRY (String): Country, territory, or area.
• ISO3 (String): ISO Alpha-3 country code.
• WHO_REGION (String): The WHO regional office to which the country belongs.
• DATA_SOURCE (String): Indicates the data source, which can be either "REPORTING" (Data reported by Member States or sourced from official reports) or "OWID" (Data sourced from Our World in Data COVID-19 Vaccinations).
• DATE_UPDATED (Date): Date of the last update.
• TOTAL_VACCINATIONS (Integer): Cumulative total vaccine doses administered.
• PERSONS_VACCINATED_1PLUS_DOSE (Decimal): Cumulative number of persons vaccinated with at least one dose.
• TOTAL_VACCINATIONS_PER100 (Integer): Cumulative total vaccine doses administered per 100 population.
• PERSONS_VACCINATED_1PLUS_DOSE_PER100 (Decimal): Cumulative persons vaccinated with at least one dose per 100 population.
• PERSONS_LAST_DOSE (Integer): Cumulative number of persons vaccinated with a complete primary series.
• PERSONS_LAST_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with a complete primary series per 100 population.
• VACCINES_USED (String): Combined short name of the vaccine in the format "Company - Product name."
• FIRST_VACCINE_DATE (Date): Date of the first vaccinations, equivalent to the start/launch date of the first vaccine administered in a country.
• NUMBER_VACCINES_TYPES_USED (Integer): Number of vaccine types used per country, territory, or area.
• PERSONS_BOOSTER_ADD_DOSE (Integer): Cumulative number of persons vaccinated with at least one booster or additional dose.
• PERSONS_BOOSTER_ADD_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with at least one booster or additional dose per 100 population.

In addition to the vaccination data, a separate dataset containing vaccination metadata is available, including information about vaccine names, product names, company names, authorization dates, start and end dates of vaccine rollout, and more.

Vaccination metadata Fields: vaccination-metadata.csv

• ISO3 (String): ISO Alpha-3 country code
• VACCINE_NAME (String): Combined short name of vaccine: "Company - Product name" (see below)
• PRODUCT_NAME (String): Name or label of vaccine product, or type of vaccine (if unnamed).
• COMPANY_NAME (String): Marketing authorization holder of vaccine product.
• FIRST_VACCINE_DATE (Date): Date of first vaccinations. Equivalent to start/launch date of the first vaccine administered in a country.
• AUTHORIZATION_DATE (Date): Date vaccine product was authorized for use in the country, territory, area.
• START_DATE (Date): Start/launch date of vaccination with vaccine type (excludes vaccinations during clinical trials).
• END_DATE (Date): End date of vaccine rollout
• COMMENT (String): Comments related to vaccine rollout
• DATA_SOURCE (String): Indicates data source - REPORTING: Data reported by Member States, or sourced from official re...

This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Uganda. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 1100 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

Additional file 2: Three training videos are available with links provided by selecting the instructional material button at the http://covid-webapp.numerusinc.com/ Home page. Direct links to these videos are: Training video 1, https://www.youtube.com/watch?v=iK4VSdiMOC4 ; Training video 2, https://www.youtube.com/watch?v=ZBdwZaknyj4&t=604s ; Traning video 3, https://www.youtube.com/watch?v=NtwcCGDog_o .

Since the start of COVID-19 pandemic the Republic of Djibouti, in the horn of Africa, has experienced two epidemic waves of the virus between April and August 2020 and between February and May 2021. By May 2021, COVID-19 had affected 1.18% of the Djiboutian population and caused 152 deaths. Djibouti hosts several foreign military bases which makes it a potential hot-spot for the introduction of different SARS-CoV-2 strains. We genotyped fifty three viruses that have spread during the two epidemic waves. Next, using spike sequencing of twenty-eight strains and whole genome sequencing of thirteen strains, we found that Nexstrain clades 20A and 20B with a typically European D614G substitution in the spike and a frequent P2633L substitution in nsp16 were the dominant viruses during the first epidemic wave, while the clade 20H South African variants spread during the second wave characterized by an increase in the number of severe forms of COVID-19.

Date_reported Date of reporting to WHO Country_code ISO Alpha-2 country code Country Country, territory, area WHO_region WHO regional offices: WHO Member States are grouped into six WHO regions -- Regional Office for Africa (AFRO), Regional Office for the Americas (AMRO), Regional Office for South-East Asia (SEARO), Regional Office for Europe (EURO), Regional Office for the Eastern Mediterranean (EMRO), and Regional Office for the Western Pacific (WPRO). New_cases New confirmed cases. Calculated by subtracting previous cumulative case count from current cumulative cases count.* Cumulative_cases Cumulative confirmed cases reported to WHO to date. New_deaths New confirmed deaths. Calculated by subtracting previous cumulative deaths from current cumulative deaths.* Cumulative_deaths Cumulative confirmed deaths reported to WHO to date. Pregnat How many people were pregnant during covid 19 Intubed How many people were intubated during covid 19