In 2023, the number of deaths per 1,000 inhabitants in India was ****. Between 1960 and 2023, the figure dropped by *****, though the decline followed an uneven course rather than a steady trajectory.

Actual value and historical data chart for India Death Rate Crude Per 1 000 People

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.

Vital Statistics: Death Rate: per 1000 Population: Uttar Pradesh data was reported at 6.500 NA in 2020. This stayed constant from the previous number of 6.500 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Uttar Pradesh data is updated yearly, averaging 8.200 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 10.500 NA in 1999 and a record low of 6.500 NA in 2020. Vital Statistics: Death Rate: per 1000 Population: Uttar Pradesh data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

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.

The statistic shows the adult mortality rate in India from 2013 to 2023, by gender. According to the source, the adult mortality rate is the probability of dying between the ages of 15 and 60 - that is, the probability of a 15-year-old dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages. In 2023, the mortality rate for women was at ****** per 1,000 female adults, while the mortality rate for men was at ****** per 1,000 male adults in India.

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.

Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data was reported at 5.300 NA in 2020. This records an increase from the previous number of 5.200 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data is updated yearly, averaging 6.200 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 7.700 NA in 1998 and a record low of 5.200 NA in 2019. Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

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.

Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban data was reported at 5.000 NA in 2020. This records a decrease from the previous number of 5.200 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban data is updated yearly, averaging 5.600 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 6.400 NA in 1998 and a record low of 5.000 NA in 2020. Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

Vital Statistics: Death Rate: per 1000 Population: Telangana: Urban data was reported at 4.200 NA in 2020. This records a decrease from the previous number of 4.300 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Telangana: Urban data is updated yearly, averaging 4.500 NA from Dec 2014 (Median) to 2020, with 7 observations. The data reached an all-time high of 4.900 NA in 2015 and a record low of 4.200 NA in 2020. Vital Statistics: Death Rate: per 1000 Population: Telangana: Urban data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

Almost ** percent of all daily deaths in Delhi between 2008 and 2019 were linked to fine particulate matter (PM2.5) levels higher than World Health Organization (WHO) guidelines for safe exposure. Annual average exposure to PM2.5 in Delhi exceeded 100 micrograms per cubic meter of air in 2023. On average, *** per cent of all daily deaths in these ** major Indian cities were linked to PM2.5 air pollution during this period.

Road accidents have been a major cause for concern across the Indian subcontinent. In 2022 alone, the country reported nearly *** thousand fatalities due to road accidents. Each year, about ***** to **** percent of the country’s GDP was invested in road accidents. Notably, while India has about *** percent of the world’s vehicle population, it also accounted for about *** percent of the global road traffic incidents. Almost ** percent of the accidents involved young Indians. Cases and causesTwo-wheelers had the maximum involvement in fatal road accidents across the country in 2018. A major portion of the accidents that year occurred at T-junctions. Over speeding has been a cause for concern throughout the country regardless of day or nighttime. Moreover, fast and risky maneuvers and illegal street races on roads and highways not designed for the purpose created significant trouble for the police. Over ** percent of the accidents occurred on straight roads. Additionally, state highways had a share of about ** percent of the total road accidents in 2018. Future scenarioRoughly around 17 accident-related deaths occur across India every hour. Fewer cops and empty roads at night, and sometimes even during the day seem to enable motorists to do away with the traffic rules. However, efforts were made to reduce these discrepancies. The police had equipped themselves with night vision speed guns to identify the culprits. Over speeding fine was increased in the amendment of the Motor Vehicles Act as well. The road network has played a crucial role in India’s economic development and the government is likely to continue to invest resources in making road safety a vital component of everyday commute.

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.

Vital Statistics: Death Rate: per 1000 Population: Karnataka data was reported at 6.200 NA in 2020. This stayed constant from the previous number of 6.200 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Karnataka data is updated yearly, averaging 7.100 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 7.900 NA in 1998 and a record low of 6.200 NA in 2020. Vital Statistics: Death Rate: per 1000 Population: Karnataka data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

In 2020, the state of Kerala, with 7.1 deaths per 1,000 inhabitants, had the highest urban death rate. It was followed by Odisha and Chhattisgarh . On the contrary, the region of Delhi had the lowest urban deaths during the same period. Death rates for India between 2004 and 2020 can be found here.

Context

This dataset provides a timeseries of COVID-19 reported cases including cured/migrated information of states of India. The data is available from 30th January 2020 onwards.

Content

The data is in CSV format and has 5 columns.

Date: Date in DD-MM-YYYY format State: Name if the state Total Confirmed Cases: Total number of confirmed cases as on Date Cured/Discharged/Migrated: Total number of cured, discharged or migrated cases as on Date Death: Total number of deaths as on Date

All figures are cumulative.

Acknowledgements

This dataset is created and maintained using the data available in public domain. The state-wise COVID-19 cases in India are published by Ministry of Health and Family Welfare, Government of India on their website https://www.mohfw.gov.in/. A snapshot of the data on the above website is taken at 11PM IST(UTC+05.30) daily and appended to this dataset. Part of the data for initial period is taken from India Today COVID-19 Tracker at https://www.indiatoday.in/india/story/coronavirus-cases-in-india-covid19-states-cities-affected-1653852-2020-03-09.

Banner Photo by Martin Sanchez on Unsplash

Vital Statistics: Death Rate: per 1000 Population: Andhra Pradesh: Urban data was reported at 4.900 NA in 2020. This records an increase from the previous number of 4.800 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Andhra Pradesh: Urban data is updated yearly, averaging 5.400 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 6.100 NA in 1998 and a record low of 4.800 NA in 2019. Vital Statistics: Death Rate: per 1000 Population: Andhra Pradesh: Urban data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

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