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.

India recorded 531794 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, India reported 44983152 Coronavirus Cases. This dataset includes a chart with historical data for India Coronavirus Deaths.

This dataset is a comprehensive collection of data related to the spread of COVID-19 in India. It captures the number of confirmed cases and deaths in each state and union territory of India from the first reported case in January 2020 to the present day. The dataset was created to provide an understanding of the extent of the COVID-19 pandemic in India. It is important because it allows researchers, policy-makers and citizens to gain insights into the various factors that may be driving the spread of the virus in different states and regions of India. It also provides valuable information for researchers trying to understand the dynamics of the pandemic in India.

This dataset is important because it allows us to understand the current situation of the pandemic in India and to monitor the progress of the virus in each state. It can also be used to measure the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus. The dataset is applicable to anyone interested in understanding the dynamics of the COVID-19 pandemic in India, such as policy-makers, researchers, citizens, NGOs and media. It can be used to gain insights into the current situation and to track the progress of the virus in each state. It can also be used to monitor the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus.

Overall, this dataset provides a comprehensive view of the COVID-19 pandemic in India. It is updated on a daily basis, and provides essential information that is useful for researchers, policy-makers and citizens. It is an invaluable resource that can be used to understand the dynamics of the virus and to monitor the progress of the virus in each state.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

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

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.

Dataset

This dataset was created by Advik Maniar

Contents

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.

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.

COVID-19: As on Date: Number of Death: Gujarat data was reported at 11,101.000 Case in 28 Apr 2025. This stayed constant from the previous number of 11,101.000 Case for 21 Apr 2025. COVID-19: As on Date: Number of Death: Gujarat data is updated daily, averaging 10,944.000 Case from Mar 2020 (Median) to 28 Apr 2025, with 1581 observations. The data reached an all-time high of 11,101.000 Case in 28 Apr 2025 and a record low of 0.000 Case in 21 Mar 2020. COVID-19: As on Date: Number of Death: Gujarat 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.

India COVID-19: As on Date: Total Number of Death data was reported at 533,665.000 Case in 05 May 2025. This stayed constant from the previous number of 533,665.000 Case for 28 Apr 2025. India COVID-19: As on Date: Total Number of Death data is updated daily, averaging 524,260.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 533,665.000 Case in 05 May 2025 and a record low of 2.000 Case in 16 Mar 2020. India COVID-19: As on Date: Total Number of Death 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.

The Indian state of Punjab reported the highest number of active coronavirus (COVID-19) cases of over one thousand cases as of October 20, 2023. Kerala and Karnataka followed, with relatively lower casualties. That day, there were a total of over 44 million confirmed infections across India.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. 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.

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. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

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.

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.

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.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

India COVID-19: As on Date: Number of Death: Dadra and Nagar Haveli data was reported at 0.000 Case in 11 Jun 2020. This stayed constant from the previous number of 0.000 Case for 10 Jun 2020. India COVID-19: As on Date: Number of Death: Dadra and Nagar Haveli data is updated daily, averaging 0.000 Case from May 2020 (Median) to 11 Jun 2020, with 37 observations. The data reached an all-time high of 0.000 Case in 11 Jun 2020 and a record low of 0.000 Case in 11 Jun 2020. India COVID-19: As on Date: Number of Death: Dadra and Nagar Haveli 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.

COVID-19: As on Date: Number of Death: Assam data was reported at 8,038.000 Case in 05 May 2025. This stayed constant from the previous number of 8,038.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Death: Assam data is updated daily, averaging 7,986.000 Case from Apr 2020 (Median) to 05 May 2025, with 1570 observations. The data reached an all-time high of 8,038.000 Case in 05 May 2025 and a record low of 0.000 Case in 10 Apr 2020. COVID-19: As on Date: Number of Death: Assam 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.

This dataset consists of COVID-19 time series data of India since 24th March 2020. The data set is for all the States and Union Territories of India and is divided into five parts, including i) Confirmed cases; ii) Death Count; iii) Recovered Cases; iv) Temperature of that place; and v) Percentage humidity in the region. The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020. The end user can contact the corresponding author (Rohit Salgotra : nicresearchgroup@gmail.com) for more details. . [Dataset is updated Twice a Week]