India Research Report
Table of Contents
3. COVID-19 India Cases, Recoveries, and Deaths Data Analysis
4. Impact of COVID-19 in India
8. References
Authors of the report:
Oscar Wollen, Head of Research, CSRN
Divij Shah, Research Analyst
Gian Remnant, Research Analyst
Maanvi Chawla, Research Analyst
Neel Mukhopadhyay, Data Analyst
Sanaa Munjal, Research Analyst
1. Introduction
Since January 2020, the world has been suffering because of the devastation caused by the COVID-19 pandemic. It has led to wide-ranging repercussions that have, and will likely continue to hamper the day-to-day functioning of countries across the world for years to come. India has faced a particularly challenging situation in this regard, where the virus has been impacting millions ever since. This report will look at an overall perspective of how the virus has affected the country, the statistics from official government sources to substantiate the issue at hand, as well as a thorough analysis of the economic, socio-cultural, educational, and environmental elements of the situation. It will also examine the government’s response to the pandemic through its measures such as restrictions, lockdowns, vaccination, etc. The report mainly focuses on the second wave that was faced by the country earlier this year, during the months of February-July, 2021. The data and updates included in the report are till the 21st of June, 2021.
2. Profile of India
The Republic of India is the most populous democracy in the world, and the second-most populous country overall, housing over 1.2 billion people. The secular nation is in South-East Asia, stemming from the historic Indus Valley Civilization. It houses the most ancient scriptures of Hinduism, Buddhism and Jainism, and is rich in intellectual fields of mathematics, astronomy, music and the fine arts. It is one of the most geographically and ethnically diverse countries, with over 22 regional languages. Despite a history of imperialism by the British Empire, circa 2017 India’s economy is the sixth largest by nominal GDP and third largest by purchasing power parity. However, it still faces challenges of poverty, governmental corruption, inadequate public healthcare and remnants of an ancient caste system. The Indian government has recently come under fire from some domestic and most international press organizations for its handling of the COVID-19 crisis. TIME magazine[i], NYT[ii], and Al Jazeera[iii] have been some organizations that have produced critical pieces on India’s response (or lack thereof) to the pandemic.
3. COVID-19 India Cases, Recoveries, and Deaths Data Analysis
To understand the COVID pandemic in India through a data-driven lens, we will look at data provided by a national network of volunteers that aggregate and verify data from state bulletins and official handles in real-time. The result is a time-series dataset on cases, recoveries, and vaccinations — which we have found to match the numbers provided by the Indian Government. In situations where the two sources have not matched, we have found the former stating even higher numbers than the latter. The following report aims to shed some light on the geographical trends underpinning the initial spread of COVID in India, peak points during both the first and second wave, as well as state-level responses to the pandemic (in terms of vaccination).
It is worth noting that the dataset, while vetted by a network of non-government volunteers, is ultimately and primarily based on the figures provided by the Indian Government, which brings about potential issues regarding its reliability. For example, there have been instances of undercounting due to the omittance of deceased patients with co-morbidities. Such limitations decrease the value of our analysis, consequently the value of the insights drawn and these limitations must be kept in mind whilst reading the report.
3.1 High Level Overview
We begin by looking at the daily rate of COVID cases, recoveries, and deaths. Given that daily confirmed cases and recovery rates have been at a much larger scale than daily death rates; we will begin by looking only at these two and then look at death rates in isolation.
Looking at the graph above, we see a significant difference in the peaks (approx. 4x), which highlights the second wave’s severity compared to the first. Another point to note is that, compared to the first wave, we see a significant time lag in the case rate curve (blue) and the recovery rate curve (orange), indicating a longer recovery time in the future than expected.
Having looked at the daily case and recovery rates, let us now look at daily death rates. As mentioned before, compared to the first two, daily death rates have been much lower, which we see once we visualise the data:
Across both graphs, we can loosely divide the timeline into three sections:
- The initial spread of the pandemic (approx. 30th January 2020 to 31st May 2020)
- The first wave (approx. 31st May 2020 to 31st January 2021)
- The second wave (approx. 28th February 2021 to present).
Looking at section (i), we see that this area is unexplained by either graph, as they do not give us much insight (which is expected, given that the disease was spreading back then). We can further explore this period by looking into each state and construct a timeline of how COVID-19 spread across India, which set the stage for the first wave.
3.2 Timeline of Key Events of Initial Spread of COVID-19
On 30th January 2020, the first case appeared in Kerala. However, confirmed cases only began to gain traction on 8th March 2020:
At this initial point, confirmed cases were primarily limited to some northern and southern states. However, the next day (9th March 2020), these ‘clusters’ from both ends of the map began to move towards the centre, with confirmed cases appearing in lower northern states (Punjab), higher southern states (Karnataka), and western states (Maharashtra):
By 12th March 2020, all southern states (except Goa) now had confirmed cases:
On 14th March 2020, cases began spreading to more northern states (such as Himachal Pradesh). Furthermore, this point also saw Maharashtra overtaking Kerala in confirmed cases of the first time, after which Maharashtra continued to (and continues to) lead in confirmed cases nationally:
With the first confirmed cases appearing in Uttarakhand on 16th March 2020, all northern states now had confirmed cases:
The following day (17th March 2020), cases began spreading to eastern states (Odisha and West Bengal):
By 19th March 2020, with the first confirmed cases appearing in Gujarat, all western states now had confirmed cases. Simultaneously, cases also spread to more central states (Chhattisgarh):
The next day (20th March 2020), the first confirmed cases appeared in Madhya Pradesh, hence making the eastern region the last region to have confirmed cases in every state:
On 22nd March 2020, confirmed cases began spreading to central eastern states (Bihar):
By 31st March 2020, all states west of Bangladesh had confirmed cases:
Finally, only by 25th May 2020 did every state have at least one case. Note how quickly it took for the pandemic to spread among the southern, northern, western, and central regions, compared to the eastern region:
Note: the original dataset combines data from the union territories Dadra and Nagar Haveli, as well as Daman and Diu, into one data point. However, the heatmapping software on which the following graphs were made requires this data to be segregated into the two regions. As such, trying to assume a certain split (e.g. 50–50) would decrease the accuracy/validity of the analysis, and hence they were omitted.
Furthermore, there were several entries that were labelled as “State Unassigned”, which for obvious reasons, could not be included on these maps.
The following section of the report will assess and examine the path that COVID has taken in India at 3 points in time. The state of COVID at each of these points in time will be examined using heat maps which have been produced from the use of government data on the number of cases, recoveries and deaths on that particular day. Using these heat maps, comparisons and differences will be drawn from the data to expose trends and anomalies between the states at each stage. The first two sets of heat maps examine the state of COVID in India during the peaks of the respective waves of infection. The final set of heat maps reveals the current situation of COVID in India.
3.3 Peak of COVID-19 during the ‘First Wave’ — 16th September 2020
The figures above are taken from the day of the 16th of September 2020, what is considered to be the ‘peak’ of the first wave of COVID in the country. These heat maps reveal the spread of COVID across the country in what was the less deadly wave compared to the ‘tsunami’ of cases and deaths associated with the second wave in mid-2021.[iv] It has been suggested that the reason for India’s relative success in keeping the pandemic under some control during this first wave compared to other countries was due to the imposition of strict measures from an early stage. Many point to the nationwide lockdown that was imposed from the 25th of March 2020.[v] Although, the imposition of such a strict lockdown at short notice left many of India’s internal migrant workers stranded, who number approximately 40 million.[vi] This in turn led to a mass migration of these workers, moving from states such Uttar Pradesh and Bihar which account for more than 80% of the workers in this sector back to their home states.[vii] This led to many of these workers, who were carrying the virus, to pass it to their communities at home, which, on the whole, were in rural areas of neighboring states.[viii] It is possible that this mass migration may be responsible for the higher proportion of cases and deaths in states such as Punjab and West Bengal.
The heat maps show a clear outlier in cases, recoveries, and deaths, that being the state of Maharashtra which can be considered the epicenter of the pandemic in this wave as well as the second — as we shall see. The state is home to the largest city in India, Mumbai, as of 2011.[ix]
The heat map also reveals that the Southern portion of India was hit worse by the virus than the Northern states as a whole. Although, as is visible, there are a couple of anomalies to this. These are the states of Delhi and Uttar Pradesh. The state of Delhi most likely had a bad outbreak due to the high urban proportion of its inhabitants (97.5%)[x], whereas Uttar Pradesh has the highest population of any Indian state at almost 200 million.[xi] These two variables allow for a higher rate of transmission of the COVID virus within the community.
This heat map also clearly displays the high number of recoveries in the states where cases were high. Unlike the second wave below, as a result, deaths remained relatively low in comparison.
3.4 Peak of COVID-19 during the ‘Second Wave’ — 6th May 2021
The figures above are taken from the day of the 6th of May 2021, what is considered to be the ‘peak’ of the second wave of COVID in the country. These heat maps reveal a much more widespread and intense wave than the prior one in September the year previous.
The heat map showing the daily cases is particularly revealing. Compared to the first wave, it is clear that each state had significantly more COVID cases. Although the second wave was much more widespread than the first wave, it is apparent that the pandemic had concentrated itself primarily in the southern states of India, including Maharashtra, Karnataka, and Kerala.
Interesting to note is Maharashtra in both the first and second wave of the pandemic, which experienced the largest proportion of cases and deaths in each case. It has been suggested by some reports that the reason why Mumbai has remained as the epicenter of the pandemic in the country is because of the highly and densely populated slums in the southern portion of the city.[xii] The nature of the slums in the city leads to a lack of social distancing due to the close proximity of housing, a lack of provision for clean water and a lack of medical supplies such as masks to prevent the spread of the virus. In India, slums make up 17% of the total urban population across the entire country, whereas in Mumbai slums make up 42% of households.[xiii] This suggests a correlation between a higher proportion of cases and deaths on a statewide level to a higher urban population living in slums.
It is also worth comparing the ‘recoveries’ heat map between the first and second wave as well. In the second wave, there were significantly less people recovering from the virus compared to the first wave. As will be explained in greater depth later in the report, this is due to the fact that hospitals became overwhelmed in the second wave of the pandemic. Shortages of hospital beds, oxygen and delays in hospital admissions resulted in a large number of people being unable to receive treatment, hence leading to less recoveries in the second wave compared to the first wave.[xiv]
Drawing these conclusions, it informs the view of the daily ‘deaths’ count. There is a strong correlation, as to be expected, between the number of ‘cases’ to the number of deaths. As expected, Maharashtra and Uttar Pradesh had particularly high death counts during the second wave for the reasons that were explained above. There is an outlier to this rule, though, and that is the state of Kerala. As can be seen from the heat maps, although it had a large proportion of cases, it had a relatively low number of deaths. According to the Indian government, the death rate in the state during this period was around 0.4%, one of India’s lowest.[xv] There is a reason for its success in keeping deaths down during this wave. From the outset, the state set up ‘war rooms’ in each district of the state, which was used to keep close monitoring of oxygen supplies, the number of hospital beds, and other key factors which could affect the success of the response from the state government.[xvi] These war rooms made sure that the state had a steady supply of oxygen to anticipate the spike in cases along with state officials working closely with doctors on the ground. In addition to this, the state has more than 250 hospital beds per 100,000 people, which is about 5 times higher than the average for India. It also had more doctors per person than most states in the country.[xvii] The state recently has been able to keep deaths relatively low despite a high spike in cases, as will be discussed below.
3.5 Current COVID-19 Situation — 7th July 2021
The figures above are taken from the day of the 7th of July 2021. This is an up-to-date heat map revealing the current state of COVID in India.
Similar to the other sets of heat maps, Maharashtra is once again the epicentre of the pandemic. After the state experienced a surge of cases in May 2021, leading to a high number of deaths during the month of June in the same year, both cases and deaths have been reducing since, although they still remain high.[xviii] The other state where cases are particularly concentrated is Kerala, which has seen a surge of cases in recent weeks. According to Indian Medical Association state secretary Dr Gopikumar P., cases have increased in the country due to a “low number of testing and poor tracing measures”.[xix] It is still unclear whether the state has reached the peak of the surge or if its case numbers may continue to grow. Despite the surge in cases, the state has done well in keeping the numbers of deaths low, as displayed by the heat map — this is true especially when compared to Maharashtra. The reason for this was explained in the section above regarding the second wave in India.
Although the southern region of India is, on the whole, still recovering from a recent wave of cases, the eastern and some parts of the north-eastern region have recently been particularly hard hit by the virus. The heat map reveals a steady number of cases as well as deaths still being recorded in Odisha and Andhra Pradesh in the east, along with Assam in the northeast. These states saw a steep surge in cases towards mid-May 2021, which continued into June of the same year.[xx] It is understood that the primary culprit for the sudden rise in infections is due to the development of a new strain of the virus, which is now referred to as the ‘Delta Plus’ variant.[xxi] It is still unknown to a great extent how the variant differs to the ‘Delta’ variant; however, India has labelled the new variant as a ‘variant of concern’, meaning the variant will have one (or more) of the following characteristics: [xxii]
- Increased transmissibility
- Stronger binding to receptors of lung cells
- Potential reduction in monoclonal antibody response
At the moment, the state of Andhra Pradesh is towards the latter end of its recovery as the number of cases and deaths are continuing to decrease at a steady rate[xxiii]. The state of Odisha in the eastern region provides a different story. Although cases are reducing at a relatively steady pace, the death rate has been increasing on average every week since mid-April.[xxiv] At the moment, it is unclear when this rate will begin to decrease. Although, we can speculate that it may reach its peak and consequently decrease within the course of the next two weeks due to the average time between onset of symptoms and death being 7 to 10 days.[xxv]
The state of Assam is experiencing a similar situation to Andhra Pradesh where, on the whole, both cases and deaths are steadily decreasing and will continue to do so for the foreseeable future.[xxvi] The rest of the northeast region has recovered from the sudden surge of cases to a greater extent than Assam, which is why the heat maps show a lighter shade in the cases and deaths maps when compared to Assam. As for the rest of India — in particular the north and central regions of the country — cases remain low, and as a result, so do deaths.
8. References
[i] Chowdhury, Debasish Roy. “Modi Never Bought Enough COVID-19 Vaccines for India. Now the Whole World Is Paying.” Time, Time, 28 May 2021, time.com/6052370/modi-didnt-buy-enough-covid-19-vaccine/.
[ii] Gamio, Lazaro, and James Glanz. “Just How Big Could India’s True Covid Toll Be?” The New York Times, The New York Times, 25 May 2021, www.nytimes.com/interactive/2021/05/25/world/asia/india-covid-death-estimates.html?referringSource=articleShare.
[iii] Sharma, Saurabh. “Tales from an INDIAN CREMATORIUM.” Coronavirus Pandemic | Al Jazeera, Al Jazeera, 27 June 2021, www.aljazeera.com/features/2021/6/27/india-covid-crisis-the-crematorium-workers.
[iv] Jain, Vijay Kumar, et al. Differences between First Wave and Second Wave of COVID-19 in India, US National Library of Medicine National Institutes of Health, www.ncbi.nlm.nih.gov/pmc/articles/PMC8106236
[v] Eysenbach , Gunther, and Guy Fagherazzi. COVID-19 in India: Statewise Analysis and Prediction, US National Library of Medicine National Institutes of Health, Aug. 2020, www.ncbi.nlm.nih.gov/pmc/articles/PMC7431238/.
[vi] Patel, Dr Champa. “COVID-19: The Hidden Majority in India’s Migration Crisis.” 12 July 2020, https://www.chathamhouse.org/2020/07/covid-19-hidden-majority-indias-migration-crisis.
[vii] ibid
[viii] Gupta, Devarupa, et al. “COVID-19 Outbreak and Urban Dynamics: Regional Variations in India.” Springer, https://link.springer.com/article/10.1007/s10708-021-10394-6.
[ix] “Provisional Population Totals, Census of India 2011.” Govt. of India , https://www.censusindia.gov.in/2011-prov-results/paper2/data_files/India2/Table_2_PR_Cities_1Lakh_and_Above.pdf.
[x] “Census Report .” Govt. of India , https://www.censusindia.gov.in/2011census/PCA/PCA_Highlights/pca_highlights_file/India/Chapter-1.pdf.
[xi] “Census Report, Cities with Population Higher than 1000,000.” <i>Govt. of India </i>, https://www.censusindia.gov.in/2011-prov-results/paper2/data_files/India2/Table_2_PR_Cities_1Lakh_and_Above.pdf.
[xii] Gandhi, Sahil, et al. “Are Slums More Vulnerable to the COVID-19 Pandemic: Evidence from Mumbai.” 16 Apr. 2020, https://www.brookings.edu/blog/up-front/2020/04/16/are-slums-more-vulnerable-to-the-covid-19-pandemic-evidence-from-mumbai/.
[xiii] ibid
[xiv] Mohan, Rohini. “Shortage of Hospital Beds and Oxygen as India Battles Second Covid-19 Wave.” Straits Time, 19 Apr. 2021, https://www.straitstimes.com/asia/south-asia/shortage-of-hospital-beds-and-oxygen-as-india-battles-second-wave.
[xv] Bhagat, Shalini Venugopal . “As India Stumbles, One State Charts Its Own Covid Cours.” Nytimes, 25 May 2021, https://www.nytimes.com/2021/05/23/world/asia/coronavirus-kerala.html.
[xvi] ibid
[xvii] ibid
[xviii] “Maharashtra COVID 19 Cases.” Govt.Inida, https://www.covid19india.org/state/MH.
[xix] S, Unnikrishnan. “Maharashtra COVID 19 Cases.” <i>Indian Express</i>, 8 July 2021, https://www.newindianexpress.com/states/kerala/2021/jul/08/renewed-covid-spike-where-did-kerala-go-wrong-2327036.html.
[xx] “COVID 19 Cases .” Govt. of India, https://www.covid19india.org/.
[xxi] “Delta plus Variant of SARS-CoV-2: How Does It Compare with the Delta Variant?” Medicalnewstoday, https://www.medicalnewstoday.com/articles/delta-plus-variant-of-sars-cov-2-how-does-it-compare-with-the-delta-variant.
[xxii] “Delta plus Variant of SARS-CoV-2: How Does It Compare with the Delta Variant?” Medicalnewstoday,https://www.medicalnewstoday.com/articles/delta-plus-variant-of-sars-cov-2-how-does-it-compare-with-the-delta-variant.
[xxiii] “COVID 19 Cases of Andhra Pradesh .” Govt. of India , https://www.covid19india.org/state/AP.
[xxiv] ibid
[xxv] Faes, Christel, et al. “Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients.” US National Library of Medicine National Institutes of Health, 17 Oct. 2020, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589278/.
[xxvi] “COVID 19 Cases in Assam.” Govt. of India, https://www.covid19india.org/state/AS.
