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.

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 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.

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?

Hello all, this notebook consists of the patients suffering from corona virus from various states of India. This pandemic started from Kerala and it spread all over. If you will try to analyze the dataset, you will come to know that Maharashtra state have large number of positive results, also the recovery rate is high over there. This notebook clearly categorizes the positive result, death rates and the recovery rates of different states. Data visualization is done here which makes the case study more attractive and informative.

Analysis of ‘Covid_cases_in_India’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/luvharishkhati/covid-cases-in-india on 30 September 2021.

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

Hello all, this notebook consists of the patients suffering from corona virus from various states of India. This pandemic started from Kerala and it spread all over. If you will try to analyze the dataset, you will come to know that Maharashtra state have large number of positive results, also the recovery rate is high over there. This notebook clearly categorizes the positive result, death rates and the recovery rates of different states. Data visualization is done here which makes the case study more attractive and informative.

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

Content

District-wise Covid-19 data of Maharashtra, a state in India as on April 29, 2022. The data include number of positive cases, active cases, recovered, deceased cases, recovery rate and fatality rate.

Attribute Information

Cumulative Cases by Districts

1. Districts - Name of districts in Maharashtra, India
2. Positive Cases - Number of positive cases
3. Active Cases - Number of active cases
4. Recovered - Number of recovered cases
5. Deceased - Number of deaths
6. Recovery Rate (%) - Ratio of number of recovered cases to positive cases
7. Fatality Rate (%) - Ratio of number of deaths to positive cases

Source

Link : https://www.covid19maharashtragov.in/mh-covid/dashboard

Other Updated Covid19 Datasets

Link : https://www.kaggle.com/anandhuh/datasets

If you find it useful, please support by upvoting 👍

Thank You

Acknowledgements

Source: Tamilnadu Government https://stopcorona.tn.gov.in/ It's a great dataset for learning to work with data analysis and visualization.

Context

WHO has declared the recent COVID-19 epidemic affecting most of the countries as Public Health Emergency of International Concern (PHEIC). In this Dataset, we have included that India's one of the states is Tamilnadu and its district wise corona cases, recovery, deaths.

Content

47 columns * 'Date' - From the beginning date of the corona cases in Tamilnadu. * After that 37 district name and the value of their case on that day * Airport (International and Domestic), Railway surveillance - cases on that day
* 'Active_cases' - Cases still in positive * 'Confirmed_cases_on_day' - total of cases on that day * 'Death_on_day' - Death on that day * 'Total_death' - Total death till that date * 'Total_Recoveries' - Total Recoveries till that date * 'Total_Confirmed_cases' - Total Confirmed cases till that date

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.

Analysis of ‘COVID-19 India Time Series’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ravichaubey1506/covid19-india on 28 January 2022.

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

Context

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment.

Content

COVID-19 cases at daily level is present in covid_time_series.csv COVID-19 cases for different states till 1 may 2020 is present in covid_india_states.csv

Acknowledgements

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

Thanks to covid19india.org for making the individual level details and testing details available to general public.

Thanks to Wikipedia for population information.

Inspiration

Forecast for next 15 days and some EDA on Spread of Corona Virus

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

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.

IntroductionThere have been large geographical differences in the infection and death rates of COVID-19. Foods and beverages containing high amounts of phytochemicals with bioactive properties were suggested to prevent contracting and to facilitate recovery from COVID-19. The goal of our study was to determine the correlation of the type of foods/beverages people consumed and the risk reduction of contracting COVID-19 and the recovery from COVID-19.MethodsWe developed an online survey that asked the participants whether they contracted COVID-19, their symptoms, time to recover, and their frequency of eating various types of foods/beverages. The survey was developed in 10 different languages.ResultsThe participants who did not contract COVID-19 consumed vegetables, herbs/spices, and fermented foods/beverages significantly more than the participants who contracted COVID-19. Among the six countries (India/Iran/Italy/Japan/Russia/Spain) with over 100 participants and high correspondence between the location of the participants and the language of the survey, in India and Japan the people who contracted COVID-19 showed significantly shorter recovery time, and greater daily intake of vegetables, herbs/spices, and fermented foods/beverages was associated with faster recovery.ConclusionsOur results suggest that phytochemical compounds included in the vegetables may have contributed in not only preventing contraction of COVID-19, but also accelerating their recovery.

At a time when the Indian economy is in full swing and the growth rate has been declining since 2014, the picture is that Covid 19 has reached the economy by early 2020. Corona, a contagious disease that originated in China, is now spreading all over the world and across India. The disease has infected over 41,94,728 people worldwide to date. And you see it growing steadily. Developed as well as developing countries have not escaped its effects. The result of this Covid 19 is a question mark over human existence. The question is how to sustain the means of survival. The development to date has been hampered by Covid 19. It will create new solutions on how to sustain the development, but it will be difficult and laborious to fill the gaps that have been reached. The lockdown accepted by India has had an impact on the entire economy. In this, many global organizations have indicated that India's growth rate will be 0%.

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.

Itolizumab, an anti-CD6 monoclonal antibody, down-regulates COVID-19-mediated inflammation and the acute effects of cytokine release syndrome. This study aimed to evaluate the safety and efficacy of itolizumab in hospitalized COVID-19 patients with PaO2/FiO2 ratio (PFR) ≤200 requiring oxygen therapy. This multicenter, single-arm, Phase 4 study enrolled 300 hospitalized adults with SARS-CoV-2 infection, PFR ≤200, oxygen saturation ≤94%, and ≥1 elevated inflammatory markers from 17 COVID-19 specific tertiary Indian hospitals. Patients received 1.6 mg/kg of itolizumab infusion, were assessed for 1 month, and followed-up to Day 90. Primary outcome measures included incidence of severe acute infusion-related reactions (IRRs) (≥Grade-3) and mortality rate at 1 month. Incidence of severe acute IRRs was 1.3% and mortality rate at 1 month was 6.7% (n = 20/300). Mortality rate at Day 90 was 8.0% (n = 24/300). By Day 7, most patients had stable/improved SpO2 without increasing FiO2 and by Day 30, 91.7% patients were off oxygen therapy. Overall, 63 and 10 patients, respectively, reported 123 and 11 treatment-emergent adverse events up to Days 30 and 90. No deaths were attributable to itolizumab. Patient-reported outcomes showed gradual and significant improvement for all five dimensions on EQ-5D-5L. Itolizumab demonstrated acceptable safety with a favorable prognosis in hospitalized COVID-19 patients. CTRI/2020/09/027941 (Clinical Trials Registry of India).

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.

Objectives: From the beginning of the COVID-19 pandemic, clinical practice and research, globally, have centered on the prevention of transmission and treatment of the disease. The pandemic has had a huge impact on the economy and stressed the healthcare systems worldwide. The present study estimates Disability-Adjusted Life Years (DALYs), Years of Potential Productive Life Lost (YPPLL), and Cost of Productivity Lost (CPL) due to premature mortality and absenteeism, secondary to COVID-19 in Kerala state, India.

Setting: Details on sociodemography, incidence, death, quarantine, recovery time, etc were derived from public sources and CODD-K for Kerala. The working proportion for 5-year age-gender cohorts and corresponding life expectancy were obtained from the Census of India 2011.

Primary and secondary outcome measures: The impact of disease was computed through model based analysis on various age-gender cohorts. Sensitivity Analysis has been conducted by adjusting six variables across 21 scenarios. We present two estimates, one till November 15, 2020, and later updated till June 10, 2021.

Results: Severity of infection and mortality were higher among the older cohorts, with males being more susceptible than females in most sub-groups. The DALYs for males and females were 15954.5 and 8638.4 till November 15, 2020, and 83853.0 and 56628.3 till June 10, 2021. The corresponding YPPLL were 1323.57 and 612.31 till November 15, 2020, and 6993.04 and 3811.57 till June 10, 2021 and CPL (premature mortality) were 263780579.94 and 41836001.82 till November 15, 2020, and 1419557903.76 and 278275495.29 till June 10, 2021.

Conclusions: Most of the COVID-19 disease burden was contributed by YLL. Losses due to YPPLL were reduced as the impact of COVID-19 infection was lesser among productive cohorts. CPL values for 40-49 year-olds were the highest. These estimates provide the data necessary for policymakers to work on, to reduce the economic burden of COVID-19 in Kerala.

The impact of the coronavirus (COVID-19) pandemic had not only brought the global economy to a standstill but set the clock backwards on the developmental progress of several nations. While the rate of infection in India did not appear to be as high as in other countries, precautionary measures adopted dealt a severe blow to the country’s major industries - with the service sector bearing the largest brunt of estimated loss. Manufacturing made a swift recovery in the following months.

Impact of key industries

The loss incurred by enforcing a lockdown in the country was estimated at 26 billion U.S. dollars and a significant decline in GDP growth is also expected in the June quarter of 2020. With the imposition of restrictions on transportation worldwide, the trade sector also took a hit. Exports and imports saw a drastic decline in the country especially in the case of essential commodities such as petroleum, food crops, and coal, among others.

Effect on business in India

The growth rate of the automotive business in India was expected to be the most adversely affected followed by the power supply and IT sectors. Furthermore, many startups, small and medium enterprises in India expected to face issues of supply disruption and a decrease in demand. The effects of aid from the Narendra Modi-led government arguably did little to help in the face of a faltering economy.

The southern Indian state of Kerala had almost 8,417 people under observation due to the coronavirus (COVID-19) as of April 10, 2022. Of these, over eight thousand were confined to home or institutions, while over 150 patients were quarantined in designated isolation facilities. India recorded over 62 thousand active cases of the virus as September 1, 2022. The regions of Kerala , Karnataka and Maharashtra had the highest number of confirmed cases in the same time period.

Kerala’s links to Wuhan

On February 7, 2020, three Indians from Kerala were tested positive for COVID-19 after returning to India from Wuhan- the epicenter of the virus that has infected over 90 thousand people. Wuhan has been a popular destination among Keralites for its quality and affordable medical education. After conducting test swabs on all returnees, the Kerala government swung into immediate action by advising home quarantines for the people suspected to have been in contact with this coronavirus.

A state known for its healthcare performance

Kerala’s last major health scare was the Nipah virus in 1998, that returned in 2018, killing 17 people, along with almost six million cases of acute respiratory infections in 2016. Even then, Kerala is known to be India’s leading state for healthcare and medical literacy compared to the rest of the country. The southern state’s health department was reported to have been strictly following the protocols given by the World Health Organization to combat COVID-19. This preparedness seems to have borne good results so far with a high rate of recovery and containment of the virus.

Despite COVID-19 vaccines being available to pregnant women in India since summer 2021, little is known about vaccine uptake among this high-need population. We conducted mixed methods research with pregnant and recently delivered rural women in northern India, consisting of 300 phone surveys and 15 in-depth interviews, in November 2021. Only about a third of respondents were vaccinated, however, about half of unvaccinated respondents reported that they would get vaccinated now if they could. Fears of harm to the unborn baby or young infant were common (22% of unvaccinated women). However, among unvaccinated women who wanted to get vaccinated, the most common barrier reported was that their healthcare provider refused to provide them with the vaccine. Gender barriers and social norms also played a role, with family members restricting women’s access. Trust in the health system was high, however, women were most often getting information about COVID-19 vaccines from sources that they did not trust, and they knew they were getting potentially poor-quality information. Qualitative data shed light on the barriers women faced from their family and healthcare providers but described how as more people got the vaccine, that norms were changing. These findings highlight how pregnant women in India have lower vaccination rates than the general population, and while vaccine hesitancy does play a role, structural barriers from the healthcare system also limit access to vaccines. Interventions must be developed that target household decision-makers and health providers at the community level, and that take advantage of the trust that rural women already have in their healthcare providers and the government. It is essential to think beyond vaccine hesitancy and think at the system level when addressing this missed opportunity to vaccinate high-risk pregnant women in this setting. Methods To understand vaccine uptake, barriers, hesitancy, facilitating factors and sources of trusted information among pregnant and breastfeeding women, we conducted mixed-methods research in northern India in November 2021. In total, we conducted 300 phone surveys and 15 in-depth interviews with women from lower and upper middle-class populations. The eligibility criteria were to include pregnant and recently delivered women who were breastfeeding (up to one year postpartum). The surveys were conducted telephonically. The participants were active members of WhatsApp groups run by a local NGO that was a collaborator on the project. All women in the WhatsApp group were connected to the government health care system, which provides free services. A list of 552 eligible women, from a sample of about 5,000, was provided to the research assistants. Women who were either pregnant or had delivered within 1 year were eligible for the survey. The list included their name, mobile and date of delivery. These women were called one by one down the list provided by the research assistant. Women were read an informed consent and asked to provide verbal consent. A survey call was scheduled based on a time convenient for the women. Most of the surveys were completed in one call and few were done in parts based on the availability of the participant. Out of about 450 women called, 300 complete surveys were taken. Some women did not pick up the call or only completed half of the survey. The team began to take the surveys in the first week of November 2021, and 300 surveys were completed by November 27, 2021. The survey included questions on vaccine acceptance, barriers, hesitancy and socio-demographics.