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.

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

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.

Contex

1. Information on COVID-19, the infectious disease caused by the most recently discovered coronavirus.
2. Live statistics and coronavirus news tracking the number of confirmed cases, recovered patients, tests, and death. There's a story behind every dataset and here's your opportunity to share yours.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

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

Abstract

An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India’s 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, the World Bank, IDinsight, and the Development Data Lab sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

Geographic coverage

Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, and Uttar Pradesh

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

This dataset includes observations covering six states (Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, Uttar Pradesh) and three survey rounds. The survey did not have a single, unified frame from which to sample phone numbers. The final sample was assembled from several different sample frames, and the choice of frame sample frames varied across states and survey rounds.

These frames comprise four prior IDinsight projects and from an impact evaluation of the National Rural Livelihoods project conducted by the Ministry of Rural Development. Each of these surveys sought to represent distinct populations, and employed idiosyncratic sample designs and weighting schemes.

A detailed note covering key features of each sample frame is available for download.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaires covered the following subjects:

1. Agriculture: COVID-19-related changes in price realisation, acreage decisions, input expenditure, access to credit, access to fertilisers, etc.

2. Income and consumption: Changes in wage rates, employment duration, consumption expenditure, prices of essential commodities, status of food security etc.

3. Migration: Rates of in-migration, migrant income and employment status, return migration plans etc.

4. Access to relief: Access to in-kind, cash and workfare relief, quantities of relief received, and constraints on the access to relief.

5. Health: Access to health facilities and rates of foregone healthcare, knowledge of COVID-19 related symptoms and protective behaviours.

While a number of indicators were consistent across all three rounds, questions were added and removed as and when necessary to account for seasonal changes (i.e: in the agricultural cycle).

Response rate

Round 1: ~55% Round 2: ~46% Round 3: ~55%

Case data from 03-10-2020 to 08-16-2020, this data repository stores COVID-19 virus case data for India, including the daily case, summary data, and base map. Each zip file contains weekly case data from Monday to Sunday.

Abstract

An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India's 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, the World Bank, IDinsight, and the Development Data Lab sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

Geographic coverage

Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The samples for these surveys were drawn from surveys and impact evaluations previously conducted by the World Bank, the Ministry of Rural Development, India and IDInsight. A detailed note on the sampling frames is available for download.

Sampling deviation

Details will be made available after all rounds of data collection and analysis is complete.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire consists of the following modules: - Module 0: Introduction - Module 1: Migration - Module 2: Labor and Income - Module 3: Consumption - Module 4: Agriculture - Module 5: Access to Relief - Module 6: Health

Response rate

~55%

A majority of the coronavirus (COVID-19) cases in India affected people between ages 31 and 40 years as of October 18, 2021. Of these, the highest share of deaths during the measured time period was observed in people under the age of 50 years.

India COVID-19: As on Date: Total Number of Active Cases data was reported at 35.000 Case in 05 May 2025. This records an increase from the previous number of 29.000 Case for 28 Apr 2025. India COVID-19: As on Date: Total Number of Active Cases data is updated daily, averaging 44,029.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 3,745,237.000 Case in 10 May 2021 and a record low of 1.000 Case in 24 Feb 2025. India COVID-19: As on Date: Total Number of Active Cases 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.

Context

Coronavirus is a family of viruses that can cause illness, which can vary from common cold and cough to sometimes more severe disease. SARS-CoV-2 (n-coronavirus) is the new virus of the coronavirus family, which first discovered in 2019, which has not been identified in humans before. It is a contiguous virus which started from Wuhan in December 2019. Which later declared as Pandemic by WHO due to high rate spreads throughout the world. Currently (on date 27 March 2020), this leads to a total of 24K+ Deaths across the globe, including 16K+ deaths alone in Europe.Pandemic is spreading all over the world; it becomes more important to understand about this spread.

The number of new cases are increasing day by day around the world. This dataset has information from the states and union territories of India at daily level.

State Wise data fetched from Ministry of Health & Family Welfare ICMR Testing Data comes from Indian Council of Medical Research

Content

COVID-19 cases at daily level is present in covid_19_india.csv file

COVID-19 State and Union Territory data with latitude and longitude is present in state_wise_data.csv file

COVID-19 cases at daily level is present in data_wise_data.csv and perday_new_cases.csv file

Number of COVID-19 tests and positive cases at daily level in ICMR_Testing_Data.csv file

Acknowledgements

Thanks to Ministry of Health & Family Welfare for making the data available to general public.

This work is highly inspired from few other kaggle kernels , github sources and other data science resources. Any traces of replications, which may appear , is purely co-incidental. Due respect & credit to all my fellow kagglers.

Inspiration

Together we can do this. Help the world to make a better place and with this fight against COVID-19.

In past 24 hours, India, Asia had 68 new cases, N/A deaths and N/A recoveries.

To control the spread of COVID-19 in India and to aid the efforts of the Ministry of Health and Family Welfare (MOHFW), the Population Council and other non-governmental organizations are conducting research to assess residents’ ability to follow sanitation and social distancing precautions under a countrywide lockdown. The Population Council COVID-19 study team is implementing rapid phone-based surveys to collect information on knowledge, attitudes and practices, as well as needs, among 2,041 young people (ages 19–23 years) and/or an adult household member, sampled from an existing prospective cohort study with a total sample size of 20,594 in Bihar (n=10,433) and Uttar Pradesh (n=10,161). Baseline was conducted from April 3–22; subsequent iterations of the survey are planned to be conducted on a monthly basis. Baseline findings on awareness of COVID-19 symptoms, perceived risk, awareness of and ability to carry out preventive behaviors, misconceptions, and fears will inform the development of government and other stakeholders’ interventions and/or strategies. We are committed to openly sharing the latest versions of the study description, questionnaires, de-identified or aggregated datasets, and preliminary results. Data and findings can also be shared with partners working on the COVID-19 response.

please visit the primary dataset page.Announcements:

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally in India. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively.

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.

India COVID-19: As on Date: Total Number of Migrated data was reported at 1.000 Case in 27 Jul 2020. This stayed constant from the previous number of 1.000 Case for 26 Jul 2020. India COVID-19: As on Date: Total Number of Migrated data is updated daily, averaging 1.000 Case from Mar 2020 (Median) to 27 Jul 2020, with 125 observations. The data reached an all-time high of 1.000 Case in 27 Jul 2020 and a record low of 1.000 Case in 27 Jul 2020. India COVID-19: As on Date: Total Number of Migrated 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 Cured/Discharged data was reported at 44,511,086.000 Case in 05 May 2025. This records an increase from the previous number of 44,511,058.000 Case for 28 Apr 2025. India COVID-19: As on Date: Total Number of Cured/Discharged data is updated daily, averaging 42,598,052.500 Case from Mar 2020 (Median) to 05 May 2025, with 1578 observations. The data reached an all-time high of 45,002,325.000 Case in 05 Dec 2023 and a record low of 42.000 Case in 25 Mar 2020. India COVID-19: As on Date: Total Number of Cured/Discharged 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 marks one COVID-19 death every 5 minutes

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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.

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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.

Over the past several months, the world has been facing an unprecedented public health crisis in the form of Covid-19. States and union territories in India have been equal partners of the Central Government in managing the Covid-19 outbreak in the country. This document is a compendium of practices from states and union territories that details information about various initiatives implemented by states, districts, and cities in India for containing and managing the Covid-19 outbreak. The practices in the compendium have been dis-aggregated under six sections: (i) public health and clinical response (ii) governance mechanisms (iii) digital health (iv) integrated model (v) welfare of migrants and other vulnerable groups (vi) other practices. A summary of the relevant Government of India guidelines has been included for the aforementioned categories, wherever applicable.