69 datasets found
  1. 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/
    Explore at:
    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.

  2. COVID-19 confirmed, recovered and deceased cumulative cases in India...

    • statista.com
    Updated Dec 4, 2024
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    Statista (2024). COVID-19 confirmed, recovered and deceased cumulative cases in India 2020-2023 [Dataset]. https://www.statista.com/statistics/1104054/india-coronavirus-covid-19-daily-confirmed-recovered-death-cases/
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 29, 2020 - Oct 20, 2023
    Area covered
    India
    Description

    India reported almost 45 million cases of the coronavirus (COVID-19) as of October 20, 2023, with more than 44 million recoveries and about 532 thousand fatalities. The number of cases in the country had a decreasing trend in the past months.

    Burden on the healthcare system

    With the world's second largest population in addition to an even worse second wave of the coronavirus pandemic seems to be crushing an already inadequate healthcare system. Despite vast numbers being vaccinated, a new variant seemed to be affecting younger age groups this time around. The lack of ICU beds, black market sales of oxygen cylinders and drugs needed to treat COVID-19, as well as overworked crematoriums resorting to mass burials added to the woes of the country. Foreign aid was promised from various countries including the United States, France, Germany and the United Kingdom. Additionally, funding from the central government was expected to boost vaccine production.

    Situation overview
    Even though days in April 2021 saw record-breaking numbers compared to any other country worldwide, a nation-wide lockdown has not been implemented. The largest religious gathering - the Kumbh Mela, sacred to the Hindus, along with election rallies in certain states continue to be held. Some states and union territories including Maharashtra, Delhi, and Karnataka had issued curfews and lockdowns to try to curb the spread of infections.

  3. T

    CORONAVIRUS DEATHS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). CORONAVIRUS DEATHS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/coronavirus-deaths
    Explore at:
    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. Number of COVID-19 deaths per million India 2020 by state

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Number of COVID-19 deaths per million India 2020 by state [Dataset]. https://www.statista.com/statistics/1173403/india-number-of-covid-19-deaths-per-million-by-state/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 16, 2020
    Area covered
    India
    Description

    In October 2020, Tripura recorded the highest COVID-19 deaths per million people compared to to other states and Union territories with ** deaths. Uttarakhand followed with over ** deaths per million people.

    Indicators such as case fatality and doubling time are used to measure the spread of the disease. The total deaths per million is considered to be a good indicator, to better measure and understand, the efficacy of the measures undertaken to control the spread of the virus. A slacked increase along with a fall in the number of new deaths per day is suggestive of a good control indicator.

  5. T

    India Coronavirus COVID-19 Recovered

    • tradingeconomics.com
    csv, excel, json, xml
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    TRADING ECONOMICS, India Coronavirus COVID-19 Recovered [Dataset]. https://tradingeconomics.com/india/coronavirus-recovered
    Explore at:
    excel, csv, json, xmlAvailable download formats
    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
    Mar 11, 2020 - Dec 15, 2021
    Area covered
    India
    Description

    India recorded 29427330 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, India reported 476135 Coronavirus Deaths. This dataset includes a chart with historical data for India Coronavirus Recovered.

  6. n

    Data from: Estimation of non-health Gross Domestic Product (NHGDP) loss due...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Oct 2, 2023
    + more versions
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    Paramita Bhattacharya; Denny John; Nirmalya Mukherjee; M. S. Narassima; Jaideep Menon; Amitava Banerjee (2023). Estimation of non-health Gross Domestic Product (NHGDP) loss due to COVID-19 deaths in West Bengal, India [Dataset]. http://doi.org/10.5061/dryad.573n5tbc4
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 2, 2023
    Dataset provided by
    Manbhum Ananda Ashram Nityananda Trust
    Amrita Institute of Medical Sciences and Research Centre
    Great Lakes Institute of Management
    Manbhum Ananda Asharan Nityananda Trust
    University College London
    Authors
    Paramita Bhattacharya; Denny John; Nirmalya Mukherjee; M. S. Narassima; Jaideep Menon; Amitava Banerjee
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    West Bengal, India
    Description

    This study estimates the economic losses (GDP), particularly the impact of COVID-19 deaths on non-health components of GDP in West Bengal state. The NHGDP losses were evaluated using cost-of-illness approach. Future NHGDP losses were discounted at 3%. Excess death estimates by the World Health Organisation (WHO) and Global Burden of Disease (GBD) were used. Sensitivity analysis was carried out by varying discount rates and Average Age of Death (AAD). 21,532 deaths in West Bengal since 17th March 2020 till 31st December 2022 decreased the future NHGDP by $0.92 billion. Nearly 90% of loss was due to deaths occurring in above 30 years age-group. The majority of the loss was borne among the 46–60 years age-group. The NHGDP loss/death was $42,646, however, the average loss/death declined with a rise in age. The loss increased to $9.38 billion and $9.42 billion respectively based on GBD and WHO excess death estimates. The loss increased to $1.3 billion by considering the lower age of the interval as AAD. At 5% and 10% discount rates, the losses reduced to $0.769 billion and $0.549 billion respectively. Results from the study suggest that COVID-19 contributed to major economic loss in West Bengal. The mortality and morbidity caused by COVID-19, the substantial economic costs at individual and population levels in West Bengal, and probably across India and other countries, is another argument for better infection control strategies across the globe to end the impact of this epidemic. Methods Various open domains were used to gather data on COVID-19 deaths in West Bengal and the aforementioned estimates. Economic losses in terms of Non-Health Gross Domestic Product (NHGDP)among six age-group brackets viz. 0–15, 16–30, 31–45, 46–60, 61–75 and 75 and above were estimated to facilitate comparisons and to initiate advocacy for an increase in health investments against COVID-19. This study used midpoint age as the age of death for all the age brackets. The legal minimum age for working i.e., 15 years. A sensitivity analysis was conducted to determine the effect of age on the overall total NHGDP loss estimate. The model was re-estimated assuming an average age at death to be the starting age of each age-group bracket. Based on existing literature discounted rate of interest to measure the value of life is taken as 2.9%. As a sensitivity analysis, NHGDP loss has also been computed using 5% and 10% of discounted rates of interest.

  7. I

    India COVID-19: As on Date: Number of Death: Karnataka

    • ceicdata.com
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    CEICdata.com, India COVID-19: As on Date: Number of Death: Karnataka [Dataset]. https://www.ceicdata.com/en/india/disease-outbreaks-coronavirus-2019-mohfw/covid19-as-on-date-number-of-death-karnataka
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 23, 2024 - Mar 24, 2025
    Area covered
    India
    Description

    COVID-19: As on Date: Number of Death: Karnataka data was reported at 40,411.000 Case in 05 May 2025. This stayed constant from the previous number of 40,411.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Death: Karnataka data is updated daily, averaging 40,105.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 40,411.000 Case in 05 May 2025 and a record low of 1.000 Case in 25 Mar 2020. COVID-19: As on Date: Number of Death: Karnataka data remains active status in CEIC and is reported by Ministry of Health and Family Welfare. The data is categorized under High Frequency Database’s Disease Outbreaks – Table IN.HLF006: Disease Outbreaks: Coronavirus 2019: MOHFW.

  8. COVID 19 Dataset - INDIA

    • kaggle.com
    Updated May 2, 2020
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    Ambili (2020). COVID 19 Dataset - INDIA [Dataset]. https://www.kaggle.com/ambilidn/covid19-dataset-india/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 2, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ambili
    Area covered
    India
    Description

    Context

    This is a Covid 19 data set for India. The data set is updated frequently and is analysed using tableau. Click on the link to visit the tableau story. Click each of the caption in the story to unveil its content.

    https://public.tableau.com/profile/ambili.nair#!/vizhome/COVID19Indiastory/Indiastory?publish=yes

    The first Covid 19 case in India was reported on 30th January 2020 in South Indian state of Kerala on a medical student who was pursuing the studies at Wuhan University, China. Two more students were found to be infected in Kerala in the consecutive days. The Kerala government was successful in containing the disease with its proactive measures back then. The second outbreak of Covid 19 in India started in the first week of March from various parts of India in various people who visited the foreign countries and in some of the tourists from different countries.

    The tableau story consists of the following data analysis : 1. State-wise number of infected and number of death count in India map. Hover the mouse on each state in the India map to know the count. 2. Click on the next caption to know the state-wise number of confirmed, active, recovered and deceased cases in the form of bar chart. 3. The next caption takes you to the bar chart which shows the number of cases getting confirmed in India each day starting from January 30, 2020. 4. Next caption takes us to an analysis of the Mortality rate and the Recovery rate (in percentage) of each of the Indian state. We get an idea how hard each of the state is hit by the pandemic. 5. Next caption gives a detailed analysis of the state Kerala which has the mortality rate of 0.806% and the recovery rate of 74.4% as of now. Hover the mouse to know the count in each district. Don't forget to have a look at the line graph of 'number of active cases' in Kerala. It looks almost flattened ! As everyday we hear the increasing number of cases and deaths across the country, this graph may make you feel better...! 6. Finally the caption takes you to the statistics from the topmost district of Kerala - Kasaragod. The total number of cases reported is 179 at Kasaragod. The active number of cases is just 12 as of now... !!! Have a look at the statistics from Kasaragod and the story of 'Kasaragod model' as some of the national media in India call it !!!

    Content

    This data set consists of the following data: 1. state-wise statistics - Confirmed, Active, Recovered, Deceased cases 2. day-wise count of infected and deceased from various states 3. Statistics from Kerala - day-wise count of confirmed, Active, Recovered, Deceased cases 4. Statistics from Kasaragod district, Kerala - day-wise count of confirmed, Active, Recovered, Deceased cases 5. Count of confirmed cases from various districts of India

    Acknowledgements

    Ministry of Health and Family Welfare - India covid19india.org Wikipedia page - Covid 19 Pandemic India Govt. of Kerala dashboard - official Kerala Covid 19 statistics

    Inspiration

    Inspiration

    Your data will be in front of the world's largest data science community. What questions do you want to see answered?

  9. #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
    Explore at:
    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.

  10. I

    India COVID-19: As on Date: Number of Death: Maharashtra

    • ceicdata.com
    Updated Nov 15, 2019
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    CEICdata.com (2019). India COVID-19: As on Date: Number of Death: Maharashtra [Dataset]. https://www.ceicdata.com/en/india/disease-outbreaks-coronavirus-2019-mohfw/covid19-as-on-date-number-of-death-maharashtra
    Explore at:
    Dataset updated
    Nov 15, 2019
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 23, 2024 - Mar 24, 2025
    Area covered
    India
    Description

    COVID-19: As on Date: Number of Death: Maharashtra data was reported at 148,602.000 Case in 05 May 2025. This stayed constant from the previous number of 148,602.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Death: Maharashtra data is updated daily, averaging 147,855.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 148,602.000 Case in 05 May 2025 and a record low of 0.000 Case in 16 Mar 2020. COVID-19: As on Date: Number of Death: Maharashtra data remains active status in CEIC and is reported by Ministry of Health and Family Welfare. The data is categorized under High Frequency Database’s Disease Outbreaks – Table IN.HLF006: Disease Outbreaks: Coronavirus 2019: MOHFW.

  11. Covid-19 in Indian States and UT with Time Series

    • kaggle.com
    Updated Jun 20, 2020
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    Saurabh Bade (2020). Covid-19 in Indian States and UT with Time Series [Dataset]. https://www.kaggle.com/saurabhbade/covid-19-timeseries-india/tasks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 20, 2020
    Dataset provided by
    Kaggle
    Authors
    Saurabh Bade
    License

    https://www.worldbank.org/en/about/legal/terms-of-use-for-datasetshttps://www.worldbank.org/en/about/legal/terms-of-use-for-datasets

    Area covered
    India
    Description

    Context

    Time series data of Indian State and UT for Covid19.

    Content

    Time Series Data for number of cases, deaths and cured cases in Indian States and UT.

    3 files COVID19_Cured_Indian_States_UT COVID19_Deaths_Indian_States_UT COVID19_TotalCases_Indian_States_UT

    Can be used for prediction.

    Acknowledgements

    Govt of India: https://www.mohfw.gov.in https://www.covid19india.org/

    Inspiration

    Data can be used to see the pattern and prediction so that we can stop the spread of COVID19.

  12. India COVID-19: As on Date: Number of Death: Andhra Pradesh

    • ceicdata.com
    Updated Dec 15, 2019
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    CEICdata.com (2019). India COVID-19: As on Date: Number of Death: Andhra Pradesh [Dataset]. https://www.ceicdata.com/en/india/disease-outbreaks-coronavirus-2019-mohfw/covid19-as-on-date-number-of-death-andhra-pradesh
    Explore at:
    Dataset updated
    Dec 15, 2019
    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
    Dec 23, 2024 - Mar 24, 2025
    Area covered
    India
    Description

    COVID-19: As on Date: Number of Death: Andhra Pradesh data was reported at 14,733.000 Case in 05 May 2025. This stayed constant from the previous number of 14,733.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Death: Andhra Pradesh data is updated daily, averaging 14,730.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 14,733.000 Case in 05 May 2025 and a record low of 0.000 Case in 01 Apr 2020. COVID-19: As on Date: Number of Death: Andhra Pradesh data remains active status in CEIC and is reported by Ministry of Health and Family Welfare. The data is categorized under High Frequency Database’s Disease Outbreaks – Table IN.HLF006: Disease Outbreaks: Coronavirus 2019: MOHFW.

  13. f

    Summary of nationwide mortality data from included studies in India from...

    • plos.figshare.com
    • figshare.com
    xls
    Updated May 31, 2023
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    Lauren Zimmermann; Bhramar Mukherjee (2023). Summary of nationwide mortality data from included studies in India from 2020–2021. [Dataset]. http://doi.org/10.1371/journal.pgph.0000897.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Lauren Zimmermann; Bhramar Mukherjee
    License

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

    Area covered
    India
    Description

    Seroprevalence of 67.6% is used with 765 million infectionsa from an age-adjusted population as of 14 Jun-6 Jul 2021 from the 4th nationwide serosurvey [6].

  14. COVID-19: Predicting 3rd wave in India

    • kaggle.com
    Updated Feb 5, 2022
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    Aayush Kumar (2022). COVID-19: Predicting 3rd wave in India [Dataset]. https://www.kaggle.com/aayush7kumar/covid19-predicting-3rd-wave-in-india/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 5, 2022
    Dataset provided by
    Kaggle
    Authors
    Aayush Kumar
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    India
    Description

    Content

    The WHO coronavirus (COVID-19) dashboard presents official daily counts of COVID-19 cases, deaths and vaccine utilization reported by countries, territories and areas. Through this dashboard, we aim to provide a frequently updated data visualization, data dissemination and data exploration resource, while linking users to other useful and informative resources.

    Caution must be taken when interpreting all data presented, and differences between information products published by WHO, national public health authorities, and other sources using different inclusion criteria and different data cut-off times are to be expected. While steps are taken to ensure accuracy and reliability, all data are subject to continuous verification and change. All counts are subject to variations in case detection, definitions, laboratory testing, vaccination strategy, and reporting strategies.

    Acknowledgements

    © World Health Organization 2020, All rights reserved.

    WHO supports open access to the published output of its activities as a fundamental part of its mission and a public benefit to be encouraged wherever possible. Permission from WHO is not required for the use of the WHO coronavirus disease (COVID-19) dashboard material or data available for download. It is important to note that:

    WHO publications cannot be used to promote or endorse products, services or any specific organization.

    WHO logo cannot be used without written authorization from WHO.

    WHO provides no warranty of any kind, either expressed or implied. In no event shall WHO be liable for damages arising from the use of WHO publications.

    For further information, please visit WHO Copyright, Licencing and Permissions.

    Citation: WHO COVID-19 Dashboard. Geneva: World Health Organization, 2020. Available online: https://covid19.who.int/

    Inspiration

    Daily cases start increasing suddenly just before the new year and there's a fear for the upcoming wave. Everybody starts to predict the peak cases in the 3rd wave and the date the peak will be reached. Assume you are in the 1st week of January 2022 and there's panic in the country, for the Omicron variant is said to be highly transmittable. Using your machine learning and deep learning skills, you have to create a model that predicts accurately the peak for the 3rd wave.

  15. India Covid 19 Cases (Statewise and overall)

    • kaggle.com
    Updated Jun 17, 2020
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    rutvikbaxi (2020). India Covid 19 Cases (Statewise and overall) [Dataset]. https://www.kaggle.com/rutvikbaxi/inida-covid-19-cases-statewise-and-overall/notebooks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 17, 2020
    Dataset provided by
    Kaggle
    Authors
    rutvikbaxi
    Area covered
    India
    Description

    The following is the dataset consisting of Covid19 cases in India since 10th march on a daily basis. It also contains statewide data. It has got separate for active, total, discharged cases and deaths.

    Acknowledgements

    This dataset is built by converting the JSON file available from the opensource website https://api.rootnet.in. URL for the json datafile: https://api.rootnet.in/covid19-in/stats/history

    Inspiration

    I struggled a lot to find data in the form of csv file for doing analysis of Covid19 impact on India but I wa u unable to find any good dataset. Hence I had to spend a lot of time learning how to extract JSON files and write codes to convert that into a usable form. Hence I thought I will upload it so that in future aspiring Data analysts can have easy access to the dataset.

  16. India Non Virus Deaths During lockdown

    • zenodo.org
    • data.niaid.nih.gov
    csv
    Updated Mar 24, 2021
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    Aman; Kanika Sharma; Krushna R; Thejesh GN; Thejesh GN; Aman; Kanika Sharma; Krushna R (2021). India Non Virus Deaths During lockdown [Dataset]. http://doi.org/10.5281/zenodo.4630198
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    csvAvailable download formats
    Dataset updated
    Mar 24, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Aman; Kanika Sharma; Krushna R; Thejesh GN; Thejesh GN; Aman; Kanika Sharma; Krushna R
    License

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

    Area covered
    India
    Description

    This is a public database of reported deaths that have happened as a result of the lockdown. These include deaths due to starvation and financial distress, exhaustion, accidents during migration, lack or denial of medical care, suicides, police brutality, crimes, and alcohol-withdrawal. We also have a few deaths wherein more details are needed, or where conflicting reports emerge. We put such deaths in the ‘unclassified’ category. More details.

  17. COVID-19 cases in India as of October 2023, by type

    • statista.com
    Updated Dec 4, 2024
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    Statista (2024). COVID-19 cases in India as of October 2023, by type [Dataset]. https://www.statista.com/statistics/1101713/india-covid-19-cases-by-type/
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    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    India reported over 44 million confirmed cases of the coronavirus (COVID-19) as of October 20, 2023. The number of people infected with the virus was declining across the south Asian country.

    What is the coronavirus?

    COVID-19 is part of a large family of coronaviruses (CoV) that are transmitted from animals to people. The name COVID-19 is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged. Symptoms of COVID-19 resemble that of the common cold, with fever, coughing, and shortness of breath. However, serious infections can lead to pneumonia, multi-organ failure, severe acute respiratory syndrome, and even death, if appropriate medical help is not provided.

    COVID-19 in India

    India reported its first case of this coronavirus in late January 2020 in the southern state of Kerala. That led to a nation-wide lockdown between March and June that year to curb numbers from rising. After marginal success, the economy opened up leading to some recovery for the rest of 2020. In March 2021, however, the second wave hit the country causing record-breaking numbers of infections and deaths, crushing the healthcare system. The central government has been criticized for not taking action this time around, with "#ResignModi" trending on social media platforms in late April. The government's response was to block this line of content on the basis of fighting misinformation and reducing panic across the country.

  18. A

    ‘COVID-19 India dataset’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 3, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘COVID-19 India dataset’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-covid-19-india-dataset-ae82/c43338d1/?iid=041-528&v=presentation
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    Dataset updated
    Aug 3, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    India
    Description

    Analysis of ‘COVID-19 India dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/dhamur/covid19-india-dataset on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

     This data set contains the data of covid-19 Conformed, Recovered and Deaths in India. This data is took from the non-governmental organization. 
    

    Website

    COVID-19 Daily updates

    My Github

    Profile Data Set

    Data collected from

    COVID19-India - The data from 31-Jan-2020 to 31-Oct-2021. Remaining data from

    --- Original source retains full ownership of the source dataset ---

  19. d

    COVID-19: Daily Cases Data

    • dataful.in
    Updated Apr 30, 2025
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    Dataful (Factly) (2025). COVID-19: Daily Cases Data [Dataset]. https://dataful.in/datasets/1311
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    application/x-parquet, xlsx, csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    COVID-19 Cases
    Description

    This Dataset contains day-wise cumulative total positive cases, active cases, recoveries and death statistics due to COVID-19 in India up to 10 June 2024

  20. Covid19_India_Cases

    • kaggle.com
    Updated Apr 12, 2020
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    Chaitanya (2020). Covid19_India_Cases [Dataset]. https://www.kaggle.com/crbelhekar619/covid19-india-cases/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 12, 2020
    Dataset provided by
    Kaggle
    Authors
    Chaitanya
    License

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

    Area covered
    India
    Description

    Context

    • A new coronavirus designated 2019-nCoV was first identified in Wuhan, the capital of China's Hubei province
    • People developed pneumonia without a clear cause and for which existing vaccines or treatments were not effective.
    • The virus has shown evidence of human-to-human transmission
    • Transmission rate (rate of infection) appeared to escalate in mid-January 2020
    • As of 16 March 2020, approximately 170,237 cases have been confirmed
    • In India, 110 cases have been confirmed until 15th March, 2020.

    Content

    Each row represent the daily confirmed cases in India.

    Acknowledgements

    Ministry of Health and Family Welfare.

    Inspiration

    To create awareness among Indians regarding the spread of Covid-19.

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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/
Organization logo

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

Explore at:
171 scholarly articles cite this dataset (View in Google Scholar)
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.

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