100+ datasets found
  1. Total number of COVID-19 cases APAC April 2024, by country

    • statista.com
    • ai-chatbox.pro
    Updated Sep 18, 2024
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    Statista (2024). Total number of COVID-19 cases APAC April 2024, by country [Dataset]. https://www.statista.com/statistics/1104263/apac-covid-19-cases-by-country/
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    Dataset updated
    Sep 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Asia–Pacific
    Description

    The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

  2. China CN: COVID-19: Confirmed Case: New Increase

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: COVID-19: Confirmed Case: New Increase [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-patient/cn-covid19-confirmed-case-new-increase
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Apr 29, 2020 - May 10, 2020
    Area covered
    China
    Description

    China COVID-19: Confirmed Case: New Increase data was reported at 17.000 Person in 10 May 2020. This records an increase from the previous number of 14.000 Person for 09 May 2020. China COVID-19: Confirmed Case: New Increase data is updated daily, averaging 51.000 Person from Jan 2020 (Median) to 10 May 2020, with 112 observations. The data reached an all-time high of 15,152.000 Person in 12 Feb 2020 and a record low of 1.000 Person in 08 May 2020. China COVID-19: Confirmed Case: New Increase data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient.

  3. T

    China Coronavirus COVID-19 Cases

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). China Coronavirus COVID-19 Cases [Dataset]. https://tradingeconomics.com/china/coronavirus-cases
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    excel, csv, 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
    Jan 4, 2020 - May 17, 2023
    Area covered
    China
    Description

    China recorded 99256991 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 5226 Coronavirus Deaths. This dataset includes a chart with historical data for China Coronavirus Cases.

  4. Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by...

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by region [Dataset]. https://www.statista.com/statistics/1090007/china-confirmed-and-suspected-wuhan-coronavirus-cases-region/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    The new SARS-like coronavirus has spread around China since its outbreak in Wuhan - the capital of central China’s Hubei province. As of June 7, 2022, there were 2,785,848 active cases with symptoms in Greater China. The pandemic has caused a significant impact in the country's economy.

    Fast-moving epidemic

    In Wuhan, over 3.8 thousand deaths were registered in the heart of the outbreak. The total infection number surged on February 12, 2020 in Hubei province. After a change in official methodology for diagnosing and counting cases, thousands of new cases were added to the total figure. There is little knowledge about how the virus that originated from animals transferred to humans. While human-to-human transmission has been confirmed, other transmission routes through aerosol and fecal-oral are also possible. The deaths from the current virus COVID-19 (formally known as 2019-nCoV) has surpassed the toll from the SARS epidemic of 2002 and 2003.

    Key moments in the Chinese coronavirus timeline

    The doctor in Wuhan, Dr. Li Wenliang, who first warned about the new strain of coronavirus was silenced by the police. It was announced on February 7, 2020 that he died from the effects of the coronavirus infection. His death triggered a national backlash over freedom of speech on Chinese social media. On March 18, 2020, the Chinese government reported no new domestically transmissions for the first time after a series of quarantine and social distancing measures had been implemented. On March 31, 2020, the National Health Commission (NHC) in China started reporting the infection number of symptom-free individuals who tested positive for coronavirus. Before that, asymptomatic cases had not been included in the Chinese official count. China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country. On April 17, 2020, health authorities in Wuhan revised its death toll, adding some 1,290 fatalities in its total count.

  5. COVID-19 confirmed and death case development in China 2020-2022

    • statista.com
    Updated May 22, 2024
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    Statista (2024). COVID-19 confirmed and death case development in China 2020-2022 [Dataset]. https://www.statista.com/statistics/1092918/china-wuhan-coronavirus-2019ncov-confirmed-and-deceased-number/
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Jun 6, 2022
    Area covered
    China
    Description

    As of June 6, 2022, the novel coronavirus SARS-CoV-2 that originated in Wuhan, the capital of Hubei province in China, had infected over 2.1 million people and killed 14,612 in the country. Hong Kong is currently the region with the highest active cases in China.

    From Wuhan to the rest of China

    In late December 2019, health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan Seafood Market. With Chinese New Year approaching, millions of Chinese migrant workers travelled back to their hometowns for the celebration. Before the start of the travel ban on January 23, around five million people had left Wuhan. By the end of January, the number of infections had surged to over ten thousand. The death toll from the virus exceeded that of the SARS outbreak a few days later. On February 12, thousands more cases were confirmed in Wuhan after an improvement to the diagnosis method, resulting in another sudden surge of confirmed cases. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. On April 17, 2020, health authorities in Wuhan revised its death toll, adding 50 percent more fatalities. After quarantine measures were implemented, the country reported no new local coronavirus COVID-19 transmissions for the first time on March 18, 2020.

    The overloaded healthcare system

    In Wuhan, 28 hospitals were designated to treat coronavirus patients, but the outbreak continued to test China’s disease control system and most of the hospitals were soon fully occupied. To combat the virus, the government announced plans to build a new hospital swiftly. On February 3, 2020, Huoshenshan Hospital was opened to provide an additional 1,300 beds. Due to an extreme shortage of health-care professionals in Wuhan, thousands of medical staff from all over China came voluntarily to the epicenter to offer their support. After no new deaths reported for first time, China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

  6. a

    Coronavirus COVID-19 Cases V2

    • hub.arcgis.com
    • prep-response-portal-napsg.hub.arcgis.com
    • +1more
    Updated Mar 26, 2020
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    CSSE_covid19 (2020). Coronavirus COVID-19 Cases V2 [Dataset]. https://hub.arcgis.com/maps/1cb306b5331945548745a5ccd290188e
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    Dataset updated
    Mar 26, 2020
    Dataset authored and provided by
    CSSE_covid19
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

  7. Key figures of coronavirus COVID-19 in Greater China 2022

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Key figures of coronavirus COVID-19 in Greater China 2022 [Dataset]. https://www.statista.com/statistics/1092967/china-wuhan-coronavirus-key-figures/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    The novel coronavirus that originated in the Chinese city Wuhan - the capital of Hubei province - had killed 17,826 people in Greater China. As of June 7, 2022, there were 2,785,848 active cases with symptoms in the region.

    How did it spread?

    In late December 2019, the health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan seafood market. The virus then spread spread rapidly to other provinces when millions of Chinese migrant workers headed home for Chinese New Year celebrations. About five billion people left Wuhan before the start of the travel ban on January 23. Right before Chinese New Year, the central government decided to put Wuhan and other cities in Hubei province on lockdown. With further travel restrictions and cancellations of public celebration events, the number of infections surpassed 80 thousand by the end of February. On March 18, 2020, China reported no new local coronavirus COVID-19 transmissions for the first time after quarantine measures had been implemented. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. After no new deaths reported for first time, the Chinese government lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

    What is COVID-19?

    Coronaviruses originate in animals like camels, civets and bats and are usually not transmissible to humans. But when a coronavirus mutates, it can be passed from animals to humans. The new strain of coronavirus COVID-19 is one of the seven known coronaviruses that can infect humans causing fever and respiratory infections. China's National Health Commission has confirmed the virus can be transmitted between humans through direct contact, airborne droplets. Faecal-oral transmission could also be possible. Although the death toll of COVID-19 has surpassed that of SARS, its fatality rate is relatively low compared to other deadly coronavirus, such as SARS and MERS.

  8. Latest Coronavirus COVID-19 figures for China

    • covid19-today.pages.dev
    json
    Updated Oct 27, 2023
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    Worldometers (2023). Latest Coronavirus COVID-19 figures for China [Dataset]. https://covid19-today.pages.dev/countries/china/
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Oct 27, 2023
    Dataset provided by
    Worldometershttps://dadax.com/
    CSSE at JHU
    License

    https://github.com/disease-sh/API/blob/master/LICENSEhttps://github.com/disease-sh/API/blob/master/LICENSE

    Area covered
    China
    Description

    In past 24 hours, China, Asia had N/A new cases, N/A deaths and N/A recoveries.

  9. Coronavirus COVID-19 Global Cases

    • redivis.com
    application/jsonl +7
    Updated Jul 13, 2020
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    Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
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    sas, csv, application/jsonl, spss, stata, parquet, arrow, avroAvailable download formats
    Dataset updated
    Jul 13, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    Abstract

    JHU Coronavirus COVID-19 Global Cases, by country

    Documentation

    PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

    This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

    Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    Section 2

    Included Data Sources are:

    %3C!-- --%3E

    Section 3

    **Terms of Use: **

    This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

    Section 4

    **U.S. county-level characteristics relevant to COVID-19 **

    Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

    https://github.com/mkiang/county_preparedness/

  10. COVID-19 Trends in Each Country

    • data.amerigeoss.org
    esri rest, html
    Updated Jul 29, 2020
    + more versions
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    ESRI (2020). COVID-19 Trends in Each Country [Dataset]. https://data.amerigeoss.org/dataset/covid-19-trends-in-each-country
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    html, esri restAvailable download formats
    Dataset updated
    Jul 29, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    COVID-19 Trends Methodology
    Our goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.


    6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.
    6/22/2020 - Added Executive Summary and Subsequent Outbreaks sections
    Revisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.
    Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.
    Correction on 6/1/2020
    Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020.
    Revisions added on 4/30/2020 are highlighted.
    Revisions added on 4/23/2020 are highlighted.

    Executive Summary
    COVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties.
    The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.

    We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.

    Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.

    Reasons for undertaking this work in March of 2020:
    1. The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.
    2. The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.
    3. The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:
    • U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online.
    • Initial older guidance was also obtained online.
    Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws.
    Thus, the formula used to compute an estimate of active cases is:

    Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths.
    <br

  11. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    • ai-chatbox.pro
    Updated Nov 25, 2024
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    Statista (2024). 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
    Nov 25, 2024
    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.

  12. H

    World COVID-19 Daily Cases with Basemap

    • dataverse.harvard.edu
    • dataone.org
    Updated Feb 20, 2024
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    Spatial Data Lab (2024). World COVID-19 Daily Cases with Basemap [Dataset]. http://doi.org/10.7910/DVN/L20LOT
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 20, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Spatial Data Lab
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    World
    Dataset funded by
    NSF
    Description

    Updated to May 13, 2021. World COVID-19 daily cases with basemap, starting from January 22, 2020.

  13. g

    CSSE_covid19 - Coronavirus COVID-19 (2019-nCoV) | gimi9.com

    • gimi9.com
    Updated Mar 10, 2023
    + more versions
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    (2023). CSSE_covid19 - Coronavirus COVID-19 (2019-nCoV) | gimi9.com [Dataset]. https://gimi9.com/dataset/au_bda7594740fd40299423467b48e9ecf6/
    Explore at:
    Dataset updated
    Mar 10, 2023
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This dashboard created by Operations Dashboard contains the most up-to-date coronavirus COVID-19 cases and latest trend plot. It covers China, the US, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals). Data sources are WHO, US CDC, China NHC, ECDC, and DXY. The China data is automatically updating at least once per hour, and non China data is updating manually. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This service is supported by Esri Living Atlas team and JHU Data Services.

  14. COVID-19 case death rate trend in China 2020-2023

    • statista.com
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    Statista, COVID-19 case death rate trend in China 2020-2023 [Dataset]. https://www.statista.com/statistics/1108866/china-novel-coronavirus-covid19-case-fatality-rate-development/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 19, 2020 - Jan 1, 2023
    Area covered
    China
    Description

    As of January 1, 2023, the case fatality rate (CFR) of coronavirus COVID-19 ranged at 0.27 percent in China, lower than the global level of 1.01 percent. Health authorities in Wuhan, the Chinese epicenter, revised its death toll on April 17, adding some 1,290 fatalities to its total count. The 50 percent increase of death cases in the city raised the overall CFR in China from 4.06 percent to 5.6 percent. The Chinese Center for Disease Control and Prevention reported that mortality increased with age among infected patients.

  15. Age distribution of COVID-19 patients in China 2020

    • statista.com
    Updated Aug 28, 2024
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    Statista (2024). Age distribution of COVID-19 patients in China 2020 [Dataset]. https://www.statista.com/statistics/1095024/china-age-distribution-of-wuhan-coronavirus-covid-19-patients/
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    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    According to a medical analysis based on 44,672 confirmed cases of the novel coronavirus COVID-19 in China published in February 2020, most patients aged between 30 and 69 years. Approximately ten percent of the surveyed patients were 29 years old or younger. The same report revealed that mortality increased with age among Chinese COVID-19 cases. The most common symptoms were fever and dry cough.

  16. f

    COVID-19 Case Reports in China

    • figshare.com
    txt
    Updated Jan 29, 2022
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    Xiao Fan Liu; Xiao-Ke Xu; Ye Wu (2022). COVID-19 Case Reports in China [Dataset]. http://doi.org/10.6084/m9.figshare.12656165.v35
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    txtAvailable download formats
    Dataset updated
    Jan 29, 2022
    Dataset provided by
    figshare
    Authors
    Xiao Fan Liu; Xiao-Ke Xu; Ye Wu
    License

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

    Area covered
    China
    Description

    Chinese prefectural level governments started to report daily confirmed COVID-19 cases online, starting from January 2020. The disclosures may contain the mobility, potential exposure scenario, epidemiological characteristics, and other useful information of individual cases. We organized a group of content coders since early March 2020, kept monitoring the information updates, manually extracted useful information from the public disclosures, and compiled these datasets.We welcome any form of collaborations with us and non-commercial reuse of our dataset. We highly encourage interested parties to examine the data, report errors in our coding, and help us to keep the data updated.The detailed data description can be found on SSRN preprint server https://dx.doi.org/10.2139/ssrn.3705815.

  17. M

    Coronavirus (COVID-19) Statistics in China: Number of infection and...

    • catalog.midasnetwork.us
    csv
    Updated Jul 6, 2023
    + more versions
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    MIDAS Coordination Center (2023). Coronavirus (COVID-19) Statistics in China: Number of infection and recovered cases for COVID-19 in China at the provincial and administrative division level [Dataset]. https://catalog.midasnetwork.us/collection/25
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    csvAvailable download formats
    Dataset updated
    Jul 6, 2023
    Dataset authored and provided by
    MIDAS Coordination Center
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Time period covered
    Jan 20, 2020 - Feb 29, 2020
    Area covered
    China
    Variables measured
    disease, COVID-19, pathogen, case counts, Homo sapiens, host organism, mortality data, infectious disease, Severe acute respiratory syndrome coronavirus 2
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    A data set on COVID-19 pandemic in China, which covers daily statistics of confirmed cases (new and cumulative), recoveries (new and cumulative) and deaths (new and cumulative) at city/province level. All data are extracted from Chinese government reports and are available in a CSV format.

  18. f

    Table_1_Estimation of Local Novel Coronavirus (COVID-19) Cases in Wuhan,...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    Zian Zhuang; Peihua Cao; Shi Zhao; Yijun Lou; Shu Yang; Weiming Wang; Lin Yang; Daihai He (2023). Table_1_Estimation of Local Novel Coronavirus (COVID-19) Cases in Wuhan, China from Off-Site Reported Cases and Population Flow Data from Different Sources.docx [Dataset]. http://doi.org/10.3389/fphy.2020.00336.s001
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Zian Zhuang; Peihua Cao; Shi Zhao; Yijun Lou; Shu Yang; Weiming Wang; Lin Yang; Daihai He
    License

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

    Area covered
    Wuhan, China
    Description

    In December 2019, novel coronavirus disease (COVID-19) hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate the total number of COVID-19 cases in Wuhan, by 23 January 2020, given the cases reported in other cities/regions and population flow data between Wuhan and these cities/regions. We built a model to estimate the total number of COVID-19 cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that cases exported from Wuhan were less likely underreported in other cities/regions. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases in Wuhan was determined by the maximum log likelihood estimation and Akaike Information Criterion (AIC) weight. We estimated 8 679 (95% CI: 7 701, 9 732) as total COVID-19 cases in Wuhan by 23 January 2020, based on combined source of data from Tencent and Baidu. Sources of population flow data impact the estimates of the total number of COVID-19 cases in Wuhan before city lockdown. We should make a comprehensive analysis based on different sources of data to overcome the bias from different sources.

  19. f

    Data_Sheet_1_Extended SIR Prediction of the Epidemics Trend of COVID-19 in...

    • frontiersin.figshare.com
    docx
    Updated Jun 4, 2023
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    Jia Wangping; Han Ke; Song Yang; Cao Wenzhe; Wang Shengshu; Yang Shanshan; Wang Jianwei; Kou Fuyin; Tai Penggang; Li Jing; Liu Miao; He Yao (2023). Data_Sheet_1_Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China.docx [Dataset]. http://doi.org/10.3389/fmed.2020.00169.s001
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    docxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Frontiers
    Authors
    Jia Wangping; Han Ke; Song Yang; Cao Wenzhe; Wang Shengshu; Yang Shanshan; Wang Jianwei; Kou Fuyin; Tai Penggang; Li Jing; Liu Miao; He Yao
    License

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

    Area covered
    Hunan, Italy, China
    Description

    Background: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies.Methods: We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item.Results: In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04–6.00) in Italy and 3.16 (95% CI, 1.73–5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114–274 378) under the current country blockade and the endpoint would be Aug 05 in Italy.Conclusion: Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.

  20. Cases

    • data.amerigeoss.org
    csv, esri rest +4
    Updated Aug 11, 2020
    + more versions
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    ESRI (2020). Cases [Dataset]. https://data.amerigeoss.org/mk/dataset/cases2
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    html, kml, esri rest, geojson, zip, csvAvailable download formats
    Dataset updated
    Aug 11, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description
    This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.
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Statista (2024). Total number of COVID-19 cases APAC April 2024, by country [Dataset]. https://www.statista.com/statistics/1104263/apac-covid-19-cases-by-country/
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Total number of COVID-19 cases APAC April 2024, by country

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 18, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Asia–Pacific
Description

The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

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