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.

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.

Total Covid cases, end of month in India, March, 2023 The most recent value is 44700000 total Covid cases as of March 2023, no change compared to the previous value of 44700000 total Covid cases. Historically, the average for India from February 2020 to March 2023 is 26611526 total Covid cases. The minimum of 7 total Covid cases was recorded in February 2020, while the maximum of 44700000 total Covid cases was reached in October 2022. | TheGlobalEconomy.com

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.

Context

Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19 - World Health Organization

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.

Data comes from Ministry of Health & Family Welfare

Content

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

Population at state level is present in population_india_census2011.csv file

Acknowledgements

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

Thanks to Wikipedia for population information.

Photo Courtesy - https://hgis.uw.edu/virus/

Inspiration

Looking for data based suggestions to stop / delay the spread of virus

The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

COVID-19: As on Date: Number of Confirmed Cases: Telangana data was reported at 844,923.000 Case in 05 May 2025. This stayed constant from the previous number of 844,923.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Confirmed Cases: Telangana data is updated daily, averaging 792,627.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 844,923.000 Case in 05 May 2025 and a record low of 3.000 Case in 16 Mar 2020. COVID-19: As on Date: Number of Confirmed Cases: Telangana 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.

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

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 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.

BackgroundRecent studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveal that Omicron variant BA.1 and sub-lineages have revived the concern over resistance to antiviral drugs and vaccine-induced immunity. The present study aims to analyze the clinical profile and genome characterization of the SARS-CoV-2 variant in eastern Uttar Pradesh (UP), North India.MethodsWhole-genome sequencing (WGS) was conducted for 146 SARS-CoV-2 samples obtained from individuals who tested coronavirus disease 2019 (COVID-19) positive between the period of 1 January 2022 and 24 February 2022, from three districts of eastern UP. The details regarding clinical and hospitalized status were captured through telephonic interviews after obtaining verbal informed consent. A maximum-likelihood phylogenetic tree was created for evolutionary analysis using MEGA7.ResultsThe mean age of study participants was 33.9 ± 13.1 years, with 73.5% accounting for male patients. Of the 98 cases contacted by telephone, 30 (30.6%) had a travel history (domestic/international), 16 (16.3%) reported having been infected with COVID-19 in past, 79 (80.6%) had symptoms, and seven had at least one comorbidity. Most of the sequences belonged to the Omicron variant, with BA.1 (6.2%), BA.1.1 (2.7%), BA.1.1.1 (0.7%), BA.1.1.7 (5.5%), BA.1.17.2 (0.7%), BA.1.18 (0.7%), BA.2 (30.8%), BA.2.10 (50.7%), BA.2.12 (0.7%), and B.1.617.2 (1.3%) lineages. BA.1 and BA.1.1 strains possess signature spike mutations S:A67V, S:T95I, S:R346K, S:S371L, S:G446S, S:G496S, S:T547K, S:N856K, and S:L981F, and BA.2 contains S:V213G, S:T376A, and S:D405N. Notably, ins214EPE (S1- N-Terminal domain) mutation was found in a significant number of Omicron BA.1 and sub-lineages. The overall Omicron BA.2 lineage was observed in 79.5% of women and 83.2% of men.ConclusionThe current study showed a predominance of the Omicron BA.2 variant outcompeting the BA.1 over a period in eastern UP. Most of the cases had a breakthrough infection following the recommended two doses of vaccine with four in five cases being symptomatic. There is a need to further explore the immune evasion properties of the Omicron variant.

COVID-19: As on Date: Number of Active Cases: Tamil Nadu data was reported at 14.000 Case in 05 May 2025. This records a decrease from the previous number of 16.000 Case for 28 Apr 2025. COVID-19: As on Date: Number of Active Cases: Tamil Nadu data is updated daily, averaging 3,626.000 Case from Mar 2020 (Median) to 05 May 2025, with 1587 observations. The data reached an all-time high of 313,048.000 Case in 28 May 2021 and a record low of 0.000 Case in 21 Apr 2025. COVID-19: As on Date: Number of Active Cases: Tamil Nadu 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.

Insights on Covid spread trend in Mirzapur, Uttar Pradesh, India by a projection based on data from the past 30 days.

Context

Analysis and Visualization of spread of coronavirus in India.

Content

The dataset raw_data.csv file, contains information about the coronavirus infected patients from time period 2-Feb-2020 to 14-April-2020 in India. It has information of all the states, their districts and cities. The data is very much useful in realising the threats that are being caused by the virus and also the source from where it is being spread in India. Also the travel history of patients and their Current health Status makes it easier to develop a model and predict the covid19 hotspots in the nation.

Acknowledgements

We wouldn't be here without the help of covid19india website. The dataset was obtained from website mentioned.

Inspiration

The cases of coronavirus infected people are increasing, this has caused to serious health calamities across the country. This has led to huge crisis on healthcare and Medicine and also the organisations that work to face and tackle coronavirus. Therefore it is of great importance that the data needs to be analysed and solutions need to be found out by looking for parameters that will help take down the virus.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.-- Esri COVID-19 Trend Report for 3-9-2023 --0 Countries have Emergent trend with more than 10 days of cases: (name : # of active cases) 41 Countries have Spreading trend with over 21 days in new cases curve tail: (name : # of active cases)Monaco : 13, Andorra : 25, Marshall Islands : 52, Kyrgyzstan : 79, Cuba : 82, Saint Lucia : 127, Cote d'Ivoire : 148, Albania : 155, Bosnia and Herzegovina : 172, Iceland : 196, Mali : 198, Suriname : 246, Botswana : 247, Barbados : 274, Dominican Republic : 304, Malta : 306, Venezuela : 334, Micronesia : 346, Uzbekistan : 356, Afghanistan : 371, Jamaica : 390, Latvia : 402, Mozambique : 406, Kosovo : 412, Azerbaijan : 427, Tunisia : 528, Armenia : 594, Kuwait : 716, Thailand : 746, Norway : 768, Croatia : 847, Honduras : 1002, Zimbabwe : 1067, Saudi Arabia : 1098, Bulgaria : 1148, Zambia : 1166, Panama : 1300, Uruguay : 1483, Kazakhstan : 1671, Paraguay : 2080, Ecuador : 53320 Countries may have Spreading trend with under 21 days in new cases curve tail: (name : # of active cases)61 Countries have Epidemic trend with over 21 days in new cases curve tail: (name : # of active cases)Liechtenstein : 48, San Marino : 111, Mauritius : 742, Estonia : 761, Trinidad and Tobago : 1296, Montenegro : 1486, Luxembourg : 1540, Qatar : 1541, Philippines : 1915, Ireland : 1946, Brunei : 2010, United Arab Emirates : 2013, Denmark : 2111, Sweden : 2149, Finland : 2154, Hungary : 2169, Lebanon : 2208, Bolivia : 2838, Colombia : 3250, Switzerland : 3321, Peru : 3328, Slovakia : 3556, Malaysia : 3608, Indonesia : 3793, Portugal : 4049, Cyprus : 4279, Argentina : 5050, Iran : 5135, Lithuania : 5323, Guatemala : 5516, Slovenia : 5689, South Africa : 6604, Georgia : 7938, Moldova : 8082, Israel : 8746, Bahrain : 8932, Netherlands : 9710, Romania : 12375, Costa Rica : 12625, Singapore : 13816, Serbia : 14093, Czechia : 14897, Spain : 17399, Ukraine : 19568, Canada : 24913, New Zealand : 25136, Belgium : 30599, Poland : 38894, Chile : 41055, Australia : 50192, Mexico : 65453, United Kingdom : 65697, France : 68318, Italy : 70391, Austria : 90483, Brazil : 134279, Korea - South : 209145, Russia : 214935, Germany : 257248, Japan : 361884, US : 6440500 Countries may have Epidemic trend with under 21 days in new cases curve tail: (name : # of active cases) 54 Countries have Controlled trend: (name : # of active cases)Palau : 3, Saint Kitts and Nevis : 4, Guinea-Bissau : 7, Cabo Verde : 8, Mongolia : 8, Benin : 9, Maldives : 10, Comoros : 10, Gambia : 12, Bhutan : 14, Cambodia : 14, Syria : 14, Seychelles : 15, Senegal : 16, Libya : 16, Laos : 17, Sri Lanka : 19, Congo (Brazzaville) : 19, Tonga : 21, Liberia : 24, Chad : 25, Fiji : 26, Nepal : 27, Togo : 30, Nicaragua : 32, Madagascar : 37, Sudan : 38, Papua New Guinea : 38, Belize : 59, Egypt : 60, Algeria : 64, Burma : 65, Ghana : 72, Haiti : 74, Eswatini : 75, Guyana : 79, Rwanda : 83, Uganda : 88, Kenya : 92, Burundi : 94, Angola : 98, Congo (Kinshasa) : 125, Morocco : 125, Bangladesh : 127, Tanzania : 128, Nigeria : 135, Malawi : 148, Ethiopia : 248, Vietnam : 269, Namibia : 422, Cameroon : 462, Pakistan : 660, India : 4290 41 Countries have End Stage trend: (name : # of active cases)Sao Tome and Principe : 1, Saint Vincent and the Grenadines : 2, Somalia : 2, Timor-Leste : 2, Kiribati : 8, Mauritania : 12, Oman : 14, Equatorial Guinea : 20, Guinea : 28, Burkina Faso : 32, North Macedonia : 351, Nauru : 479, Samoa : 554, China : 2897, Taiwan* : 249634 -- SPIKING OF NEW CASE COUNTS --20 countries are currently experiencing spikes in new confirmed cases:Armenia, Barbados, Belgium, Brunei, Chile, Costa Rica, Georgia, India, Indonesia, Ireland, Israel, Kuwait, Luxembourg, Malaysia, Mauritius, Portugal, Sweden, Ukraine, United Kingdom, Uzbekistan 20 countries experienced a spike in new confirmed cases 3 to 5 days ago: Argentina, Bulgaria, Croatia, Czechia, Denmark, Estonia, France, Korea - South, Lithuania, Mozambique, New Zealand, Panama, Poland, Qatar, Romania, Slovakia, Slovenia, Switzerland, Trinidad and Tobago, United Arab Emirates 47 countries experienced a spike in new confirmed cases 5 to 14 days ago: Australia, Austria, Bahrain, Bolivia, Brazil, Canada, Colombia, Congo (Kinshasa), Cyprus, Dominican Republic, Ecuador, Finland, Germany, Guatemala, Honduras, Hungary, Iran, Italy, Jamaica, Japan, Kazakhstan, Lebanon, Malta, Mexico, Micronesia, Moldova, Montenegro, Netherlands, Nigeria, Pakistan, Paraguay, Peru, Philippines, Russia, Saint Lucia, Saudi Arabia, Serbia, Singapore, South Africa, Spain, Suriname, Thailand, Tunisia, US, Uruguay, Zambia, Zimbabwe 194 countries experienced a spike in new confirmed cases over 14 days ago: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea - South, Kosovo, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Taiwan*, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, US, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza, Yemen, Zambia, Zimbabwe Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had been confirmed in almost every country in the world. The virus had infected over 687 million people worldwide, and the number of deaths had reached almost 6.87 million. The most severely affected countries include the U.S., India, and Brazil.

COVID-19: background information COVID-19 is a novel coronavirus that had not previously been identified in humans. The first case was detected in the Hubei province of China at the end of December 2019. The virus is highly transmissible and coughing and sneezing are the most common forms of transmission, which is similar to the outbreak of the SARS coronavirus that began in 2002 and was thought to have spread via cough and sneeze droplets expelled into the air by infected persons.

Naming the coronavirus disease Coronaviruses are a group of viruses that can be transmitted between animals and people, causing illnesses that may range from the common cold to more severe respiratory syndromes. In February 2020, the International Committee on Taxonomy of Viruses and the World Health Organization announced official names for both the virus and the disease it causes: SARS-CoV-2 and COVID-19, respectively. The name of the disease is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged.

Current Epidemiology Situation and Forecast
To date, the greatest numbers of cases and deaths have occurred in the US, India, and Brazil
The global case fatality rate (%) has continued to decline
Increasing uncertainty of infection rates renders forecasting difficult in the worst-hit countries Read More

Executive summary

The novel coronavirus SARS-CoV2 (COVID-19), first detected by Wuhan Municipal Health Commission, China, in Wuhan, Hubei Province in December 2020 and eventually the disease became pandemic. It was declared as Public Health Emergency of International Concern (PHEIC) by WHO in January 2020. The COVID-19 disease primarily spreads through droplets of saliva or discharge from the nose when an infected person coughs or sneezes. People infected with the COVID-19 virus experiences mild, moderate or serious respiratory illness.

Health workers play a critical role in the clinical management of patients with COVID-19 and hence are likely to be the most vulnerable for contracting the disease. Therefore, investigating the extent of infection in health care settings and identifying risk factors for infection among health workers along with follow-up within a facility in which a confirmed case of COVID-19 infection is receiving care can provide useful information on virus transmissibility and routes of transmission, and will bear important step in limiting amplification events in health care facilities.

Objectives:

1. To find out the extent of human-to-human transmission of the SARS-CoV-2 infection among health workers
2. To study the clinical presentations of COVID-19 infection and the risk factors for infection among health workers.
3 To evaluate the effectiveness of infection prevention and control measures among health workers in protecting against COVID-19.
4. To evaluate the effectiveness of infection prevention and control programmes at health facility level
5. To determine the serological response of health workers with symptomatic and possibly asymptomatic COVID-19 infection.

Materials and Methods:

This was a prospective cohort study conducted over a period of seven months, from December 2020 to June 2021, the period covering India’s deadly second wave of COVID-19 pandemic. This was done among the health care workers working in HIMSR & HAHC hospital, a tertiary health care setting (Dedicated COVID-19 Hospital) providing care to patients with a laboratory-confirmed COVID-19 infection. This hospital located in South East Delhi has 200 bedded COVID-19 Care Hospital and 1050 registered healthcare workers who come in contact with COVID-19-infected persons. The study population (sampling frame) included all the health personnel like doctors, nurses, paramedical staff, housekeeping staff, security staff, students of medical, nursing and paramedical sciences and other front office staff who come in contact with the patients. In this study, the first visit / interview (Baseline) was done when the staff came in contact with a confirmed COVID-19 case. The second visit / interview (Endline) was done between 22-28 days. During each of these two visits, biological sample in the form of serum was collected to check the presence of anti-COVID-19 antibodies

Results:

A total of 192 HCW were recruited in this study. All of them were interviewed and blood was collected for serology at the baseline visit as well as at endline. Out of 192 participants, 119 (61.97%) were detected with SARS-CoV2 antibodies at baseline whereas 73 (38.02%) were seronegative. Again, on22-28 days of follow-up, the seropositivity was 77.7% at the endline. We found that seropositivity was significantly and negatively associated with doctor as profession [OR:0.353, CI:0.176-0.710], COVID-19 symptoms [OR:0.210, CI:0.054-0.820], comorbidities [OR:0.139 , CI: 0.029 - 0.674], recent IPC Training [OR:0.250, CI:0.072 -0.864] , while positively associated with Partially [OR:3.303,CI: 1.256-8.685], as well as fully Vaccinated for COVID-19 [OR:2.428, CI:1.118-5.271]. We also observed seroconversion among 36.7% while 64.0% had increase in titre of antibodies during our follow-up period. The seroconversion was 63.2% in doctors, 42.9% in nurses and 13.0% in paramedics staff. Seroconversion was positively associated with doctor as profession [OR:11.43, CI:2.47 - 52.79] and with partially, as well as fully vaccinated for COVID-19 [OR: 32.63, CI: 5.11 - 208.49]. None of the HCW who were smokers and with any comorbidity did not found to have been seroconversion. We observe a negative and significant relationship of increase in titre of antibodies with recent any ILI symptoms [OR:0.17, 0.13 - 0.94], smokers[OR: 0.35, 95%CI: 0.13 - 0.94], HCW with comorbidities [OR:0.08,95CI: 0.01 - 0.71],, recent full IPC Training [OR:0.07, CI:0.01 -0.63] , while positively associated with partially [OR: 7.87, 95CI: 2.18 - 28.40)], as well as fully Vaccinated for COVID-19 [OR: 3.59, 95CI: 1.46 - 8.87]. Majority of the health care worker enrolled in our study had close contact exposure with COVID-19 patients while 5 had indirect exposure. It was observed that almost all (100% in both) doctors and nurses as well as almost all paramedical staff (99%) were wearing some kind of personal protective equipment (PPE) when they were exposed to a COVID-19 patient. We did not found adherences to any of the infection prevention measure adopted by the enrolled HCW during the recent contact with COVID-19 patients to be significantly associated with seroconversion.

Conclusion:

Majority of the health care worker (67% doctor, 80% nurses & 55% paramedics) enrolled in our study had close contact exposure with COVID-19 patient. The results show that among 192 HCW enrolled, 62% were seropositive at the baseline. At end line the seropositivity was increased to 77.7%. The seroconversion rate was also studied. It was found to be 36.7% in our study population (63.2% in doctors, 42.9% in nurses and 13.0% in paramedic’s staff.). Adherence to the recommended IPC measures was reported by most participants. About two third (63%) of the HCW in our study were not vaccinated against COVID-19; nurses and paramedics were higher in proportion among those who were unvaccinated. Fifteen percentage were partially vaccinated and 22% were fully vaccinated against COVID-19, with doctors comprising majority among them. We also found that vaccination had the strongest association with seropositivity, seroconversion as well as serial rise of titre.

As of April 13, 2024, India had the highest number of confirmed deaths due to the outbreak of the novel coronavirus in the Asia-Pacific region, with over 533 thousand deaths. Comparatively, Indonesia, which had the second highest number of coronavirus deaths in the Asia-Pacific region, recorded approximately 162 thousand COVID-19 related deaths as of April 13, 2024. Contrastingly, Bhutan had reported 21 deaths due to COVID-19 as of April 13, 2024.

Context

As global communities respond to COVID-19, we've heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps could be helpful as they make critical decisions to combat COVID-19.

These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. (https://www.google.com/covid19/mobility/)

Content

The data contains aggregated and anonymised aggregated data per day for each country. For say accessing data for India - the files 2020_IN_Region_Mobility_Report.csv for 2020 data and 2021_IN_Region_Mobility_Report.csv. The aggregated data is not only present at country level, but also at States and district level - as given in sub_region_1 and sub_region_2.

Acknowledgements

This data from report published by Google. https://www.google.com/covid19/mobility/

Inspiration

Some Questions to answer

1. India is having its Second Wave and one of the major causes is considered to the election rallies held in different parts of the country. How does Mobility Impact the COVID Cases?

2. Comparing Mobility across different Countries