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

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.

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.

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.

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

On 6/16/2023 CDPH replaced the booster measures with a new “Up to Date” measure based on CDC’s new recommendations, replacing the primary series, boosted, and bivalent booster metrics The definition of “primary series complete” has not changed and is based on previous recommendations that CDC has since simplified. A person cannot complete their primary series with a single dose of an updated vaccine. Whereas the booster measures were calculated using the eligible population as the denominator, the new up to date measure uses the total estimated population. Please note that the rates for some groups may change since the up to date measure is calculated differently than the previous booster and bivalent measures.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Previous updates:

• On March 3, 2023, with the release of HPI 3.0 in 2022, the previous equity scores have been updated to reflect more recent community survey information. This change represents an improvement to the way CDPH monitors health equity by using the latest and most accurate community data available. The HPI uses a collection of data sources and indicators to calculate a measure of community conditions ranging from the most to the least healthy based on economic, housing, and environmental measures.

• Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

• Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

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 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.

IntroductionRecent reviews summarize evidence that some vaccines have heterologous or non-specific effects (NSE), potentially offering protection against multiple pathogens. Numerous economic evaluations examine vaccines' pathogen-specific effects, but less than a handful focus on NSE. This paper addresses that gap by reporting economic evaluations of the NSE of oral polio vaccine (OPV) against under-five mortality and COVID-19.Materials and methodsWe studied two settings: (1) reducing child mortality in a high-mortality setting (Guinea-Bissau) and (2) preventing COVID-19 in India. In the former, the intervention involves three annual campaigns in which children receive OPV incremental to routine immunization. In the latter, a susceptible-exposed-infectious-recovered model was developed to estimate the population benefits of two scenarios, in which OPV would be co-administered alongside COVID-19 vaccines. Incremental cost-effectiveness and benefit-cost ratios were modeled for ranges of intervention effectiveness estimates to supplement the headline numbers and account for heterogeneity and uncertainty.ResultsFor child mortality, headline cost-effectiveness was $650 per child death averted. For COVID-19, assuming OPV had 20% effectiveness, incremental cost per death averted was $23,000–65,000 if it were administered simultaneously with a COVID-19 vaccine

“India tops the world with 11% of global death in road accidents It has 1 per cent of the world's vehicles but accounts for 11 per cent of all road crash deaths, witnessing 53 road crashes every hour; killing 1 person every 4 minutes” – World Bank Report -The Economic Times, Feb 14, 2021

This is indeed an alarming report. With the rapid increase in the number of automobiles and also the heavily congested roads, ensuring road safety has utmost importance for the people in the country. Fatalities and injuries resulting from road traffic accidents can create a heavy burden on the economy and can strain the health, insurance and legal systems of the country.

India has recorded a significant drop in road crashes and deaths in in 2020 when compared to 2019. This is partly due to COVID-19 pandemic-prompted lockdowns and people voluntarily not venturing out to prevent transmission. Hence to get a better view, a detailed analysis was carried out to understand some of the major reasons for the high accident cases in India using the data from 2017-2019. The source of this data is from the official website of Government of India (https://data.gov.in/ )

The Sundarban, spread across India and Bangladesh constitutes the world’s largest and only mangrove habitat of the Royal Bengal Tiger (Panthera tigris tigris). Together, harbouring around 202 tigers, it is also infamous as the worlds most severe human-tiger conflict hotspot. Despite this, very fragmentary and inconsistent information exists on the nature and extent of human-tiger conflicts (HTC) in this landscape. To fill this lacuna, a pan landscape survey was undertaken with the aim to mine information on HTC and explore various facets of HTC occurrence in this landscape. The survey was conducted across 76 villages distributed in the eight administrative blocks on the entire fringe of the Sundarban Biosphere Reserve in India between August 2018 to November 2019. On the whole, human-tiger conflicts (HTC) were reported far more commonly than cases pertaining to conflicts with crocodiles and sharks (species unidentified). The number of cases of human-wildlife conflicts (HWC) recorded were highest in the Gosaba administrative block, followed by Kultali and Patharpratima, which together account for 74% of the recorded cases. This is interesting as in earlier published records almost no consolidated information exists for the south-24-Parganas Forest Division, although it appears that the two administrative blocks here experience the second highest level of HTC in this landscape after Goasba, in north 24 Parganas. Across the forty-year period span of the recorded information, the overall conflicts between humans and tigers appeared to have witnessed a significant increase after 1987. However, this is most likely a result of poor documentation and relatively low probability of people recalling older incidents accurately. The time series change also shows a significant lowering of human-tiger conflicts post year 2000 (Ref. Figure 1.3), which is suggestive of changes brought about by stronger enforcement as well as the beginning of the arrangements for barricading the fringes with nylon nets (Tiger Conservation Plan, STR, 2012; also see, Mukherjee et al., 2012). The level of conflict between humans and crocodiles and humans and sharks, however, did not show significant changes across the same period. The significant lowering of HTC cases held statistically, even when the data was compared across decadal periods. Post completion of the survey, between 1st December 2019 and 31st October 2020, another 22 cases have been recorded, 21 of which resulted in the death of the victims involved. However, these could not be included in the analysis due to the absence of detailed information, which could not be collected due to the paucity of time (and subsequent Covid-19 driven restrictions). Most victims of HTC were males (92%), across all age categories of victims, and the majority of the victims belonged to the working age-class, i.e. 19 to 60 years. On average, HTC victims had at least 5 dependent family members, with majority below the poverty line (BPL, as per classification of Govt. of India), earning on average Rs. 25000 (~ USD 336) per annum. Majority of the victims belonged to classified Schedule Caste groups (~69%) and Other Backward Classes (~13%), while only about ~8% belonged to classified Scheduled Tribal groups (indigenous people). This, however, could simply be reflective of the proportional distribution of the various categories in the region. However, a deeper analysis suggests that across the villages surveyed, those with a higher population of Scheduled Tribes experienced a lowered level of HTC, probably indicating that Scheduled Tribes’ are not engaged extensively in natural resource collection compared to other ethnic populations. 90.14% of the victims were Hindus, and only 9.9% of the victims were Muslim and Christian. Compared to the distribution of different religious groups, where Muslims constitute around 30% of the population of south 24 Parganas, their representation in the sample of victims was relatively low at 9.5% of the total number of victims recorded. Irrespective of the religious background of victims, the majority of HTC victims were illiterate (64 – 77.8%), and around 79% of the victims were dependent on forest-based livelihoods, primarily fishing, crab and prawn collection and honey collection as the primary source of their income. Although around 52.4% of the victims/victim’s family, reported to be owning tillable agriculture land, the average land holding was 0.2 acres, which is extremely small to provide sustainable income from traditional agricultural practices. Further, during interviews, several people reported an increased salinity in their lands due to the inundation of bunds/dykes during natural calamities, leading to saline water inflow into their lands. Such increased salinity of land often renders the land unfit for agriculture. Only 15.6% of the victims or their families owned a fishing boat, indicating that even the majority who were forest-based resource dependent,...

This dataset corresponds to paper titled "A Mathematical Model for COVID-19 Considering Waning Immunity, Vaccination and Control Measures". In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios - in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program can be successful in significantly controlling the size of infected population. We show that for India, a reduction in contact rate by 50% compared to a reduction of 10% in the current stage can reduce death from 0.0268% to 0.0141% of population. Similarly, for Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48% to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30\% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%.

Humanity has seen numerous pandemics during its course of evolution. The list includes several incidents from the past, such as measles, Ebola, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS), etc. The latest edition to this is coronavirus disease 2019 (COVID-19), caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of August 18, 2020, COVID-19 has affected over 21 million people from 180 + countries with 0.7 million deaths across the globe. Genomic technologies have enabled us to understand the genomic constitution of pathogens, their virulence, evolution, and rate of mutation, etc. To date, more than 83,000 viral genomes have been deposited in public repositories, such as GISAID and NCBI. While we are writing this, India is the third most affected country by COVID-19, with 2.7 million cases and > 53,000 deaths. Gujarat is the 11th highest affected state with a 3.48% death rate compared to the national average of 1.91%. In this study, a total of 502 SARS-CoV-2 genomes from Gujarat were sequenced and analyzed to understand its phylogenetic distribution and variants against global and national sequences. Further variants were analyzed from diseased and recovered patients from Gujarat and the world to understand its role in pathogenesis. Among the missense mutations present in the Gujarat SARS-CoV-2 genomes, C28854T (Ser194Leu) had an allele frequency of 47.62 and 7.25% in deceased patients from the Gujarat and global datasets, respectively. In contrast, the allele frequency of 35.16 and 3.20% was observed in recovered patients from the Gujarat and global datasets, respectively. It is a deleterious mutation present in the nucleocapsid (N) gene and is significantly associated with mortality in Gujarat patients with a p-value of 0.067 and in the global dataset with a p-value of 0.000924. The other deleterious variant identified in deceased patients from Gujarat (p-value of 0.355) and the world (p-value of 2.43E-06) is G25563T, which is located in Orf3a and plays a potential role in viral pathogenesis. SARS-CoV-2 genomes from Gujarat are forming distinct clusters under the GH clade of GISAID. This study will shed light on the viral haplotype in SARS-CoV-2 samples from Gujarat, India.