37 datasets found
  1. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Updated Jul 13, 2022
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    Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Jul 13, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    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.

  2. COVID-19 cases and deaths among hardest hit countries worldwide as of Nov....

    • statista.com
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    Statista, COVID-19 cases and deaths among hardest hit countries worldwide as of Nov. 14, 2022 [Dataset]. https://www.statista.com/statistics/1105264/coronavirus-covid-19-cases-most-affected-countries-worldwide/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of November 14, 2022, the United States had recorded almost 98 million cases of COVID-19. The country had also reported a total number of over one million deaths from the disease.

    COVID-19 testing remains important The cumulative number of coronavirus cases worldwide reached almost 633 million towards the beginning of November 2022. Demand for test kits has at times exceeded production levels, but many countries continue to test citizens to more effectively control rises in cases. The U.S. has performed the most tests worldwide, followed by India and the United Kingdom.

    The silent spread of the coronavirus Widespread testing will also help to detect people who might be asymptomatic – showing few or no symptoms of the illness. These carriers are unwittingly transmitting the virus to others, and the threat of silent transmission is one reason why mass lockdowns have been imposed around the world. However, as asymptomatic carriers produce no symptoms, they may have developed some natural immunity to the illness. Viruses are not as easily spread in communities with high rates of immunity, which helps to protect more vulnerable groups of people. When an infection rate is less than one, a community has achieved herd immunity.

  3. T

    CORONAVIRUS DEATHS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
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    TRADING ECONOMICS (2020). CORONAVIRUS DEATHS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/coronavirus-deaths
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  4. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +4more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

    We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

    The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

  5. COVID19-SelectedAfricanCountries

    • kaggle.com
    zip
    Updated Jun 30, 2022
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    Ojobo Agbo (2022). COVID19-SelectedAfricanCountries [Dataset]. https://www.kaggle.com/datasets/ojoboagbo/covid19selectedafricancountries
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    zip(323895 bytes)Available download formats
    Dataset updated
    Jun 30, 2022
    Authors
    Ojobo Agbo
    Description

    Data Set

    This dataset contains the COVID19 data for some specific African countries, as sourced from one of the world's top repositories on COVID 19 (https://www.worldometers.info/coronavirus/#countries).

    The raw data contains COVID19 cases, deaths, recoveries, population etc, grouped into continents and countries.

    Motivation

    Over the last 3 years, the whole world has been ravaged by the pandemic COVID19. Over this period, some nations have come to a halt, economic activities reduced drastically in many cities. This was accompanied by hundreds of thousands of deaths across the world.

    Considering a continent as populous as Africa, we have had our own fair share of the effects of the COVID19 pandemic.

    This analysis project was motivated by my desire to seek out and compare COVID 19 prevalence in some African countries between June 15th - June 27th; and also draw out insights from this analysis.

    Data Cleaning

    Upon collection of this data from the data source, the data was cleaned using MS Excel to search for missing values, outliers, spellings, duplicate data etc.

    This cleaned data was further transformed using Power Query.

    Analysis

    I carried out this analysis in a bid to answer some pressing questions: 1. Which were the 10 best-performing countries (based on the least number of COVID cases) 2. Which were the 10 worst performing countries (based on the most number of COVID cases) 3. Carry out descriptive analysis for each of 1 and 2 above. 4. Compare the expository analysis between 1 and 2 stated above. 5. Create visualization for 3 and 4 above. 6. Perform a forecast of cases for each of the 10 best and worst-performing countries.

    Visualization

    The analysis was done by visualization and creating insights using Microsoft PowerBI Desktop.

  6. G

    Covid total deaths per million around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 31, 2023
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    Globalen LLC (2023). Covid total deaths per million around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/covid_deaths_per_million/
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    csv, xml, excelAvailable download formats
    Dataset updated
    Mar 31, 2023
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    Trends in Covid total deaths per million. The latest data for over 100 countries around the world.

  7. COVID-19 deaths worldwide as of May 2, 2023, by country and territory

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). COVID-19 deaths worldwide as of May 2, 2023, by country and territory [Dataset]. https://www.statista.com/statistics/1093256/novel-coronavirus-2019ncov-deaths-worldwide-by-country/
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    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

    As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

    Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

    What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

  8. COVID-19 Trends for Countries

    • hub.arcgis.com
    Updated Apr 8, 2020
    + more versions
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    Urban Observatory by Esri (2020). COVID-19 Trends for Countries [Dataset]. https://hub.arcgis.com/maps/UrbanObservatory::covid-19-trends-for-countries
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    Dataset updated
    Apr 8, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center. -- Esri COVID-19 Trend Report for 3-9-2022 --0 (-0) Countries are in Emergent trend41 (-3) Countries are in Spreading trend.61 (+2) Countries are in Epidemic trend.54 (+0) Countries have Controlled trend.41 (+1) Countries have End Stage trend.Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.See the full methodology for information about how COVID-19 Trends are produced.

  9. Number of coronavirus (COVID-19) cases in Europe 2024, by country

    • statista.com
    Updated Nov 24, 2024
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    Statista (2024). Number of coronavirus (COVID-19) cases in Europe 2024, by country [Dataset]. https://www.statista.com/statistics/1104837/coronavirus-cases-europe-by-country/
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    Dataset updated
    Nov 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 24, 2024
    Area covered
    Europe
    Description

    As of November 24, 2024 there were over 274 million confirmed cases of coronavirus (COVID-19) across the whole of Europe since the first confirmed cases in France in January 2020. France has been the worst affected country in Europe with 39,028,437 confirmed cases, followed by Germany with 38,437,756 cases. Italy and the UK have approximately 26.8 million and 25 million cases respectively. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

  10. Incidence of coronavirus (COVID-19) deaths in Europe 2023, by country

    • statista.com
    Updated Jan 16, 2023
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    Statista (2023). Incidence of coronavirus (COVID-19) deaths in Europe 2023, by country [Dataset]. https://www.statista.com/statistics/1111779/coronavirus-death-rate-europe-by-country/
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    Dataset updated
    Jan 16, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 13, 2023
    Area covered
    Europe
    Description

    As of January 13, 2023, Bulgaria had the highest rate of COVID-19 deaths among its population in Europe at 548.6 deaths per 100,000 population. Hungary had recorded 496.4 deaths from COVID-19 per 100,000. Furthermore, Russia had the highest number of confirmed COVID-19 deaths in Europe, at over 394 thousand.

    Number of cases in Europe During the same period, across the whole of Europe, there have been over 270 million confirmed cases of COVID-19. France has been Europe's worst affected country with around 38.3 million cases, this translates to an incidence rate of approximately 58,945 cases per 100,000 population. Germany and Italy had approximately 37.6 million and 25.3 million cases respectively.

    Current situation In March 2023, the rate of cases in Austria over the last seven days was 224 per 100,000 which was the highest in Europe. Luxembourg and Slovenia both followed with seven day rates of infections at 122 and 108 respectively.

  11. Table_2_Finding Meaning in Hell. The Role of Meaning, Religiosity and...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    María Prieto-Ursúa; Rafael Jódar (2023). Table_2_Finding Meaning in Hell. The Role of Meaning, Religiosity and Spirituality in Posttraumatic Growth During the Coronavirus Crisis in Spain.docx [Dataset]. http://doi.org/10.3389/fpsyg.2020.567836.s002
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    María Prieto-Ursúa; Rafael Jódar
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Coronavirus has blighted our world, hitting some countries harder than others. Morbidity and mortality rates make Madrid one of the worst affected places so far in the wake of the coronavirus. The aim of this study was to analyze the presence of post-traumatic growth during the coronavirus crisis and to understand the contribution of meaning, religiosity, and spirituality to such growth; 1,492 people completed the questionnaire; N = 1,091 residents in Madrid were selected for the study. We assessed the personal experience of COVID-19, the Spirituality, Religiosity, Meaning trough Purpose in Life-10 test, and Posttraumatic Growth (Community Post-Traumatic Growth Scale). Results showed significant differences for all measures of growth, with higher values in women. Sex and direct impact of COVID-19 accounted for 4.4% of the variance of growth. The different dimensions of meaning contribute differently to growth. Only religiosity was associated with total growth when meaning was included in the model. This same pattern of results is obtained in models predicting interpersonal and social growth. However, in predicting personal growth, it is spirituality that predicts this type of growth once meaning has been previously controlled for, while religiosity fails to reach a statistically significant level. Our results reflect the interest in maintaining the distinction between spirituality and religiosity, their different roles in traumatic growth and the different dimensions on which each has an effect. Finally, it confirms the importance of meaning in post-traumatic growth, especially the dimension of life goals and purposes.

  12. Coronavirus (COVID-19) cases per 100,000 in Europe 2023, by country

    • statista.com
    Updated Jan 16, 2023
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    Statista (2023). Coronavirus (COVID-19) cases per 100,000 in Europe 2023, by country [Dataset]. https://www.statista.com/statistics/1110187/coronavirus-incidence-europe-by-country/
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    Dataset updated
    Jan 16, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 13, 2023
    Area covered
    Europe
    Description

    As of January 13, 2023, there had been over 270 million confirmed cases of COVID-19 across the whole of Europe since the first confirmed case in January, 2020. Cyprus has the highest incidence of COVID-19 cases among its population in Europe at 71,853 per 100,000 people, followed by a rate of 64,449 in Austria. Slovenia has recorded the third highest rate of cases in Europe at 62,834 cases per 100,000. With almost 38.3 million confirmed cases, France has been the worst affected country in Europe, which translates into a rate of 58,945 cases per 100,000 population.

    Current infection rate in Europe San Marino had the highest rate of cases per 100,000 in the past week at 336, as of January 16, 2023. Cyprus and Slovenia had seven day rates of infections at 278 and 181 respectively.

    Coronavirus deaths in Europe There have been 2,169,191 recorded COVID-19 deaths in Europe since the beginning of the pandemic. Russia has the highest number of deaths recorded in a European country at over 394 thousand. Bulgaria has the highest death rate from the virus in Europe with approximately 549 deaths per 100,000 as of January 13, followed by Hungary with 496 deaths per 100,000. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

  13. f

    Table_1_COVID-19 and Tuberculosis Coinfection: An Overview of Case...

    • datasetcatalog.nlm.nih.gov
    • frontiersin.figshare.com
    Updated Aug 24, 2021
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    Li, Huai-chen; Zhao, Jing-yu; Zhang, Qian-yun; Song, Wan-mei; Tao, Ning-ning; An, Qi-qi; Li, Shi-jin; Zhu, Xue-han; Li, Yi-fan; Liu, Si-qi; Liu, Yao; Xu, Ting-ting; Liu, Jin-yue (2021). Table_1_COVID-19 and Tuberculosis Coinfection: An Overview of Case Reports/Case Series and Meta-Analysis.doc [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000792192
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    Dataset updated
    Aug 24, 2021
    Authors
    Li, Huai-chen; Zhao, Jing-yu; Zhang, Qian-yun; Song, Wan-mei; Tao, Ning-ning; An, Qi-qi; Li, Shi-jin; Zhu, Xue-han; Li, Yi-fan; Liu, Si-qi; Liu, Yao; Xu, Ting-ting; Liu, Jin-yue
    Description

    Background: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are two major infectious diseases posing significant public health threats, and their coinfection (aptly abbreviated COVID-TB) makes the situation worse. This study aimed to investigate the clinical features and prognosis of COVID-TB cases.Methods: The PubMed, Embase, Cochrane, CNKI, and Wanfang databases were searched for relevant studies published through December 18, 2020. An overview of COVID-TB case reports/case series was prepared that described their clinical characteristics and differences between survivors and deceased patients. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) for death or severe COVID-19 were calculated. The quality of outcomes was assessed using GRADEpro.Results: Thirty-six studies were included. Of 89 COVID-TB patients, 19 (23.46%) died, and 72 (80.90%) were male. The median age of non-survivors (53.95 ± 19.78 years) was greater than that of survivors (37.76 ± 15.54 years) (p < 0.001). Non-survivors were more likely to have hypertension (47.06 vs. 17.95%) or symptoms of dyspnea (72.73% vs. 30%) or bilateral lesions (73.68 vs. 47.14%), infiltrates (57.89 vs. 24.29%), tree in bud (10.53% vs. 0%), or a higher leucocyte count (12.9 [10.5–16.73] vs. 8.015 [4.8–8.97] × 109/L) than survivors (p < 0.05). In terms of treatment, 88.52% received anti-TB therapy, 50.82% received antibiotics, 22.95% received antiviral therapy, 26.23% received hydroxychloroquine, and 11.48% received corticosteroids. The pooled ORs of death or severe disease in the COVID-TB group and the non-TB group were 2.21 (95% CI: 1.80, 2.70) and 2.77 (95% CI: 1.33, 5.74) (P < 0.01), respectively.Conclusion: In summary, there appear to be some predictors of worse prognosis among COVID-TB cases. A moderate level of evidence suggests that COVID-TB patients are more likely to suffer severe disease or death than COVID-19 patients. Finally, routine screening for TB may be recommended among suspected or confirmed cases of COVID-19 in countries with high TB burden.

  14. COVID-19 cases worldwide as of May 2, 2023, by country or territory

    • statista.com
    • avatarcrewapp.com
    + more versions
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    Statista, COVID-19 cases worldwide as of May 2, 2023, by country or territory [Dataset]. https://www.statista.com/statistics/1043366/novel-coronavirus-2019ncov-cases-worldwide-by-country/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had been confirmed in almost every country in the world. The virus had infected over 687 million people worldwide, and the number of deaths had reached almost 6.87 million. The most severely affected countries include the U.S., India, and Brazil.

    COVID-19: background information COVID-19 is a novel coronavirus that had not previously been identified in humans. The first case was detected in the Hubei province of China at the end of December 2019. The virus is highly transmissible and coughing and sneezing are the most common forms of transmission, which is similar to the outbreak of the SARS coronavirus that began in 2002 and was thought to have spread via cough and sneeze droplets expelled into the air by infected persons.

    Naming the coronavirus disease Coronaviruses are a group of viruses that can be transmitted between animals and people, causing illnesses that may range from the common cold to more severe respiratory syndromes. In February 2020, the International Committee on Taxonomy of Viruses and the World Health Organization announced official names for both the virus and the disease it causes: SARS-CoV-2 and COVID-19, respectively. The name of the disease is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged.

  15. r

    Data for: Public preferences on policies for climate, local pollution, and...

    • researchdata.se
    Updated Feb 11, 2025
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    Richard T. Carson; Jiajun Lu; Emily A. Khossravi; Gunnar Köhlin; Erik Sterner; Thomas Sterner; Dale Whittington (2025). Data for: Public preferences on policies for climate, local pollution, and health - a survey in seven large Global South countries [Dataset]. http://doi.org/10.5878/jy7v-5k80
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    (3045), (214435), (274772)Available download formats
    Dataset updated
    Feb 11, 2025
    Dataset provided by
    University of Gothenburg
    Authors
    Richard T. Carson; Jiajun Lu; Emily A. Khossravi; Gunnar Köhlin; Erik Sterner; Thomas Sterner; Dale Whittington
    Time period covered
    Feb 2, 2022 - May 7, 2023
    Area covered
    Chile, South Africa, Tanzania, Viet Nam, Colombia, India, Kenya, Nigeria
    Description

    The current dataset is a subset of a large data collection based on a purpose-built survey conducted in seven middle-income countries in the Global South: Chile, Colombia, India, Kenya, Nigeria, Tanzania, South Africa and Vietnam. The purpose of the collected variables in the present dataset aims to understanding public preferences as a critical way to any effort to reduce greenhouse gas emissions. There are many studies of public preferences regarding climate change in the Global North. However, survey work in low and middle-income countries is limited. Survey work facilitating cross-country comparisons not using the major omnibus surveys is relatively rare.
    We designed the Environment for Development (EfD) Seven-country Global South Climate Survey (the EfD Survey) which collected information on respondents’ knowledge about climate change, the information sources that respondents rely on, and opinions on climate policy. The EfD survey contains a battery of well-known climate knowledge questions and questions concerning the attention to and degree of trust in various sources for climate information. Respondents faced several ranking tasks using a best-worst elicitation format. This approach offers greater robustness to cultural differences in how questions are answered than the Likert-scale questions commonly asked in omnibus surveys. We examine: (a) priorities for spending in thirteen policy areas including climate and COVID-19, (b) how respiratory diseases due to air pollution rank relative to six other health problems, (c) agreement with ten statements characterizing various aspects of climate policies, and (d) prioritization of uses for carbon tax revenue. The company YouGov collected data for the EfD Survey in 2023 from 8400 respondents, 1200 in each country. It supplements an earlier survey wave (administered a year earlier) that focused on COVID-19. Respondents were drawn from YouGov’s online panels. During the COVID-19 pandemic almost all surveys were conducted online. This has advantages and disadvantages. Online survey administration reduces costs and data collection times and allows for experimental designs assigning different survey stimuli. With substantial incentive payments, high response rates within the sampling frame are achievable and such incentivized respondents are hopefully motivated to carefully answer the questions posed. The main disadvantage is that the sampling frame is comprised of the internet-enabled portion of the population in each country (e.g., with computers, mobile phones, and tablets). This sample systematically underrepresents those with lower incomes and living in rural areas. This large segment of the population is, however, of considerable interest in its own right due to its exposure to online media and outsized influence on public opinion. The data includes respondents’ preferences for climate change mitigation policies and competing policy issues like health. The data also includes questions such as how respondents think revenues from carbon taxes should be used. The outcome provide important information for policymakers to understand, evaluate, and shape national climate policies. It is worth noting that the data from Tanzania is only present in Wave 1 and that the data from Chile is only present in Wave 2.

  16. #IndiaNeedsOxygen Tweets

    • kaggle.com
    zip
    Updated Nov 14, 2021
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    Kash (2021). #IndiaNeedsOxygen Tweets [Dataset]. https://www.kaggle.com/kaushiksuresh147/indianeedsoxygen-tweets
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    zip(4441094 bytes)Available download formats
    Dataset updated
    Nov 14, 2021
    Authors
    Kash
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    India marks one COVID-19 death every 5 minutes

    https://ichef.bbci.co.uk/news/976/cpsprodpb/11C98/production/_118165827_gettyimages-1232465340.jpg" alt="">

    Content

    People across India scrambled for life-saving oxygen supplies on Friday and patients lay dying outside hospitals as the capital recorded the equivalent of one death from COVID-19 every five minutes.

    For the second day running, the country’s overnight infection total was higher than ever recorded anywhere in the world since the pandemic began last year, at 332,730.

    India’s second wave has hit with such ferocity that hospitals are running out of oxygen, beds, and anti-viral drugs. Many patients have been turned away because there was no space for them, doctors in Delhi said.

    https://s.yimg.com/ny/api/res/1.2/XhVWo4SOloJoXaQLrxxUIQ--/YXBwaWQ9aGlnaGxhbmRlcjt3PTk2MA--/https://s.yimg.com/os/creatr-uploaded-images/2021-04/8aa568f0-a3e0-11eb-8ff6-6b9a188e374a" alt="">

    Mass cremations have been taking place as the crematoriums have run out of space. Ambulance sirens sounded throughout the day in the deserted streets of the capital, one of India’s worst-hit cities, where a lockdown is in place to try and stem the transmission of the virus. source

    Dataset

    The dataset consists of the tweets made with the #IndiaWantsOxygen hashtag covering the tweets from the past week. The dataset totally consists of 25,440 tweets and will be updated on a daily basis.

    The description of the features is given below | No |Columns | Descriptions | | -- | -- | -- | | 1 | user_name | The name of the user, as they’ve defined it. | | 2 | user_location | The user-defined location for this account’s profile. | | 3 | user_description | The user-defined UTF-8 string describing their account. | | 4 | user_created | Time and date, when the account was created. | | 5 | user_followers | The number of followers an account currently has. | | 6 | user_friends | The number of friends an account currently has. | | 7 | user_favourites | The number of favorites an account currently has | | 8 | user_verified | When true, indicates that the user has a verified account | | 9 | date | UTC time and date when the Tweet was created | | 10 | text | The actual UTF-8 text of the Tweet | | 11 | hashtags | All the other hashtags posted in the tweet along with #IndiaWantsOxygen | | 12 | source | Utility used to post the Tweet, Tweets from the Twitter website have a source value - web | | 13 | is_retweet | Indicates whether this Tweet has been Retweeted by the authenticating user. |

    Acknowledgements

    https://globalnews.ca/news/7785122/india-covid-19-hospitals-record/ Image courtesy: BBC and Reuters

    Inspiration

    The past few days have been really depressing after seeing these incidents. These tweets are the voice of the indians requesting help and people all over the globe asking their own countries to support India by providing oxygen tanks.

    And I strongly believe that this is not just some data, but the pure emotions of people and their call for help. And I hope we as data scientists could contribute on this front by providing valuable information and insights.

  17. f

    The five countries reporting the most Covid-19 deaths worldwide.

    • plos.figshare.com
    • figshare.com
    xls
    Updated Apr 18, 2024
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    Mireille Razafindrakoto; François Roubaud; Marta Reis Castilho; Valeria Pero; João Saboia (2024). The five countries reporting the most Covid-19 deaths worldwide. [Dataset]. http://doi.org/10.1371/journal.pone.0288894.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 18, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Mireille Razafindrakoto; François Roubaud; Marta Reis Castilho; Valeria Pero; João Saboia
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The five countries reporting the most Covid-19 deaths worldwide.

  18. Rate of U.S. COVID-19 cases as of March 10, 2023, by state

    • statista.com
    Updated Jun 15, 2020
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    Statista (2020). Rate of U.S. COVID-19 cases as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109004/coronavirus-covid19-cases-rate-us-americans-by-state/
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    Dataset updated
    Jun 15, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the state with the highest rate of COVID-19 cases was Rhode Island followed by Alaska. Around 103.9 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers of infections.

    From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time; when the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide is roughly 683 million, and it has affected almost every country in the world.

    The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. Those aged 85 years and older have accounted for around 27 percent of all COVID deaths in the United States, although this age group makes up just two percent of the total population

  19. COVID-19 cases in Latin America 2025, by country

    • statista.com
    Updated Jun 5, 2025
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    Statista (2025). COVID-19 cases in Latin America 2025, by country [Dataset]. https://www.statista.com/statistics/1101643/latin-america-caribbean-coronavirus-cases/
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    Dataset updated
    Jun 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Americas, Latin America
    Description

    Brazil is the Latin American country affected the most by the COVID-19 pandemic. As of May 2025, the country had reported around 38 million cases. It was followed by Argentina, with approximately ten million confirmed cases of COVID-19. In total, the region had registered more than 83 million diagnosed patients, as well as a growing number of fatal COVID-19 cases. The research marathon Normally, the development of vaccines takes years of research and testing until options are available to the general public. However, with an alarming and threatening situation as that of the COVID-19 pandemic, scientists quickly got on board in a vaccine marathon to develop a safe and effective way to prevent and control the spread of the virus in record time. Over two years after the first cases were reported, the world had around 1,521 drugs and vaccines targeting the COVID-19 disease. As of June 2022, a total of 39 candidates were already launched and countries all over the world had started negotiations and acquisition of the vaccine, along with immunization campaigns. COVID vaccination rates in Latin America As immunization against the spread of the disease continues to progress, regional disparities in vaccination coverage persist. While Brazil, Argentina, and Mexico were among the Latin American nations with the most COVID-19 cases, those that administered the highest number of COVID-19 doses per 100 population are Cuba, Chile, and Peru. Leading the vaccination coverage in the region is the Caribbean nation, with more than 406 COVID-19 vaccines administered per every 100 inhabitants as of January 5, 2024.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  20. f

    Table_1_Professional Quality of Life Among Physicians and Nurses Working in...

    • frontiersin.figshare.com
    pdf
    Updated May 30, 2023
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    Carla Serrão; Vera Martins; Carla Ribeiro; Paulo Maia; Rita Pinho; Andreia Teixeira; Luísa Castro; Ivone Duarte (2023). Table_1_Professional Quality of Life Among Physicians and Nurses Working in Portuguese Hospitals During the Third Wave of the COVID-19 Pandemic.pdf [Dataset]. http://doi.org/10.3389/fpsyg.2022.814109.s001
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Carla Serrão; Vera Martins; Carla Ribeiro; Paulo Maia; Rita Pinho; Andreia Teixeira; Luísa Castro; Ivone Duarte
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundIn the last 2 weeks of January 2021, Portugal was the worst country in the world in incidence of infections and deaths due to COVID-19. As a result, the pressure on the healthcare system increased exponentially, exceeding its capacities and leaving hospitals in near collapse. This scenario caused multiple constraints, particularly for hospital medical staff. Previous studies conducted at different moments during the pandemic reported that COVID-19 has had significant negative impacts on healthcare workers’ psychological health, including stress, anxiety, depression, burnout, post-traumatic stress symptoms, and sleep disturbances. However, there are many uncertainties regarding the professional quality of life of hospital nurses and physicians. To address gaps in previous research on secondary traumatic stress, we focused on healthcare workers working in hospitals affected by a major traumatic event: the third wave of COVID-19.ObjectivesThe aim of the present study was to identify the contribution of personal and work-related contextual variables (gender, age, parental status, occupation, years of experience, working with patients affected by COVID-19) on professional quality of life of healthcare workers.MethodsCross-sectional study with a web-based questionnaire given to physicians and nurses working in a hospital setting. A total of 853 healthcare professionals (276 physicians and 586 nurses; median age 37 years old) participated in the survey assessing professional quality of life compassion satisfaction, secondary traumatic stress, and burnout. Factors of professional quality of life were assessed using regression analysis.ResultsMost of the participants showed moderate (80%; n = 684) or high (18%; n = 155) levels of compassion satisfaction, whereas the majority of them experienced moderate levels of burnout (72%; n = 613) and secondary traumatic stress (69%; n = 592). The analyzed variables demonstrated no differences between professionals who were directly or not involved in the care of COVID-19 patients. Parental status was found to be a significant factor in compassion satisfaction. Female gender was significantly associated with more susceptibility to secondary traumatization. Factors that may potentially contribute to burnout include years of professional experience and the number of work hours per week.ConclusionThe COVID-19 pandemic has created a new challenge for the healthcare system. Burnout and secondary traumatic stress can lead to medical errors and impact standards of patient care, particularly compromising compassionate care. It is therefore recommended that hospitals develop psychoeducational initiatives to support professionals in dealing with barriers to compassion.

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Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

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163 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 13, 2022
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

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.

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