Update of Coronovirus Stats in India

1. Covid 19 Stats in India –
Update 21
Review of key data and presentation of a projection model
Data updated till 24.05.21
Data Sources: https://www.covid19india.org/; https://www.worldometers.info/;
https://censusindia.gov.in/2011-prov-results/paper2/data_files/india/paper2_1.pdf
https://ig.ft.com/coronavirus-
chart/?areas=eur&areas=usa&areas=bra&areas=gbr&areasRegional=usny&areasRegional=usca&areasRegional=usfl&area
sRegional=ustx&byDate=0&cumulative=0&logScale=1&perMillion=0&values=deaths
https://ourworldindata.org/covid-vaccinations
https://www.mygov.in/aarogya-Setu-app/

2. Agenda
• Presentation of key data for All India
• Review of cases and deaths in states
• Analysis of 2nd wave
• Vaccination
• Discussion

3. Data Integrity
• India data on deaths is being strongly questioned by researchers both in
India and abroad. Anywhere between 2 – 4 times the official death rate is
being talked about as the real figure
• Cases are anyway ‘discovered cases’ and it is well known that the real
figure is multiple times
• Approach
• We will look at surrogate variables to get a directional indication (TPR and Daily
Growth in Active Cases are two such)
• We will also use the official numbers for modelling and look for correlation with the
surrogate variables

4. All India Data

5. • Testing has not been able to keep pace with the
pandemic after the second wave has started
• Positivity rates have crossed 20% (the peak in
September was 15%). However, recently, testing has
been ramped up and TPR is at 9.51% on 23.05.21
• In the second wave, data reliability especially deaths is
questionable. This is due to a variety of reasons:
• The wave has ramped up very fast and normal
medical and registration processes have been
compromised
• The rural areas have been impacted. Reporting is
anyway low in these areas
• Official reluctance to admit to large numbers of
both cases and deaths
• In view of the above I have looked at TPR as a
surrogate variable. This could also be compromised but
it is relatively innocuous parameter
• TPR is coming down from a peak of 24.85% on 9th May.
The rate of decline is steeper than the ascent

6. • Cumulative CFR is trending upwards. This is a
disturbing trend indicating that fatalities in the 2nd
wave are higher
• This is clearly visible when you see the 7DMA CFR.
It is now at 1.7%. In the 1st wave the maximum
level was 1.4%. Clearly the second wave is more
lethal than the 1st wave. The extent of
underreporting is also higher

7. • New infections reached their lowest point on 11.02.21 at
10,983 7DMA
• Cases have galloped after that and the previous peak was
surpassed on 4.04.21
• The highest number has been 414,280 on 6 May. The
highest level on a 7DMA basis was 392.330 on 8th May. The
declining trend in cases is now ell established. When
coupled with a decreasing TPR this is a more robust figure.
The 7DMA figure on 23.05.21 was 245,656 and daily cases
have dipped below 200,000

8. • Active Infections have peaked. From 22nd April, the rate
of growth has been slowing.
• On 10th May for the first time in the second wave, Active
Infections declined by 30,499. Thereafter, the declining
trend has got established
• Daily Growth in Active Infections is a reasonable lead
indicator of what direction the wave is taking
• The load on the healthcare system is also coming down

9. • Deaths had reached a plateau from around the
10th of May. However, the numbers have been
distorted by Previous Period Adjustments carried
out by Maharashtra on several days.
• For this presentation I have shown the raw
numbers without adjustment
• Both the 7DMA and the 30DMA graphs (the
latter is used to smoothen the PPA) are showing
a peaking on 23rd May. However, the polynomial
curve for 7DMA indicates that the peak has
already been attained
• The salient point is that deaths have continued to
grow after cases peaked on 10th May on a 7DMA
basis. This may indicate that serious cases are
taking more time to resolve. Complications such
as mucomycorsis are also gaining ground
• The next week or ten days should clearly
establish the trend

10. 10 Feb Level 10 Times Days
Punjab 229 18-Mar 35
Haryana 77 19-Mar 36
MP 141 23-Mar 40
Chattisgarh 222 24-Mar 41
AP 50 24-Mar 41
Maharashtra 3451 31-Mar 48
Delhi 127 31-Mar 48
Rajasthan 107 31-Mar 48
UP 121 31-Mar 48
Uttarakhand 35 31-Mar 48
Jharkhand 45 31-Mar 48
Karnataka 415 31-Mar 48
Bihar 64 02-Apr 50
West Bengal 179 04-Apr 52
Telengana 157 06-Apr 54
Tamil Nadu 479 09-Apr 57
Odisha 92 09-Apr 57
HP 83 12-Apr 60
All India 12539 07-Apr 55
• An interesting feature of India’s second wave is how
consistently and swiftly the cases have ramped up
• The chart shows how long various states took to reach a level
of 10 times the daily cases that they had registered on 10th
Feb (lowest level). It is remarkable how consistent this data is
• Some speculations:
• Punjab and Haryana had been hit the earliest probably
by the B.1.1.7 (UK Variant)
• The B.1.617 Variant (popularly known as the double
mutant) emerged in Vidarbha and rapidly spread to some
of the adjoining states of MP, Chhattisgarh and AP
• B.1.617 then rapidly overpowered all other strains and
spread all over the country like wildfire. This is the
possible explanation for the consistency of the spread –
that it is caused by the same variant. Genome
sequencing is in progress
• It is becoming increasingly possible that massive second
waves in most countries are due to the emergence of variants.
These, in turn, are nurtured in areas where the infection is
widespread
It is now
increasingly clear
that the 2nd wave
in India was
mainly caused by
the B.1.617.2
variant

11. States

16. State Level
• Most major states apart from Tamil Nadu and Odisha have started
declining in cases
• Deaths have yet to peak in many states. The major issue is of Previous
Period Adjustments by Maharashtra
• There is a remarkable consistency about the 2nd wave as we have
seen in the growth phase and now also in the decline phase. This will
be discussed further

17. 10 Feb Level 10 Times Days
Punjab 229 18-Mar 35
Haryana 77 19-Mar 36
MP 141 23-Mar 40
Chattisgarh 222 24-Mar 41
AP 50 24-Mar 41
Maharashtra 3451 31-Mar 48
Delhi 127 31-Mar 48
Rajasthan 107 31-Mar 48
UP 121 31-Mar 48
Uttarakhand 35 31-Mar 48
Jharkhand 45 31-Mar 48
Karnataka 415 31-Mar 48
Bihar 64 02-Apr 50
West Bengal 179 04-Apr 52
Telengana 157 06-Apr 54
Tamil Nadu 479 09-Apr 57
Odisha 92 09-Apr 57
HP 83 12-Apr 60
All India 12539 07-Apr 55
• An interesting feature of India’s second wave is how
consistently and swiftly the cases have ramped up
• The chart shows how long various states took to reach a level
of 10 times the daily cases that they had registered on 10th
Feb (lowest level). It is remarkable how consistent this data is
• Some speculations:
• Punjab and Haryana had been hit the earliest probably
by the B.1.1.7 (UK Variant)
• The B.1.617 Variant (popularly known as the double
mutant) emerged in Vidarbha and rapidly spread to some
of the adjoining states of MP, Chhattisgarh and AP
• B.1.617 then rapidly overpowered all other strains and
spread all over the country like wildfire. This is the
possible explanation for the consistency of the spread –
that it is caused by the same variant. Genome
sequencing is in progress
• It is becoming increasingly possible that massive second
waves in most countries are due to the emergence of variants.
These, in turn, are nurtured in areas where the infection is
widespread

18. Population
Date No Per Mn CFR Date No Per Mn CFR 90% Days 75% Days 50% Days
Delhi 1,67,87,941 23.04.21 25294 1,507 1.00% 3.05.21 398 23.71 1.70% 5.05.21 12 9.05.21 16 14.05.21 21
Maharashtra 11,23,74,333 24.04.21 65447 582 0.90% 5.05.21 11 13.05.21 19 20.05.21 26
UP 19,98,12,341 27.04.21 34813 174 0.60% 7.05.21 329 1.65 1.10% 4.05.21 7 10.05.21 13 16.05.21 19
Chattisgarh 2,55,45,198 28.04.21 15583 610 1.50% 3.05.21 248 9.71 1.70% 8.05.21 10 12.05.21 14 18.05.21 20
MP 7,26,26,809 29.04.21 13105 180 0.70% 3.05.21 98 1.35 0.80% 10.05.21 11 14.05.21 15 20.05.21 21
Gujarat 6,04,39,692 30.04.21 14305 237 1.20% 1.05.21 169 2.80 1.20% 8.05.21 8 15.05.21 15 21.05.21 21
Telengana 3,50,03,674 1.05.21 8036 230 0.60% 7.05.21 58 1.66 0.80% 5.05.21 4 12.05.21 11 20.05.21 19
Bihar 10,40,99,452 6.05.21 14191 136 0.60% 11.05.21 5 14.05.21 8 19.05.21 13
Rajasthan 6,85,48,437 8.05.21 17590 257 0.90% 12.05.21 162 2.36 0.90% 15.05.21 7 18.05.21 10 22.05.21 14
Haryana 2,53,51,462 9.05.21 14430 569 1.10% 10.05.21 163 6.43 1.10% 14.05.21 5 17.05.21 8 22.05.21 13
Karnataka 6,10,95,297 9.05.21 47502 778 1.00% 13.05.21 500 8.18 1.00% 13.05.21 4 20.05.21 10
Uttarakhand 1,00,86,292 11.05.21 7555 749 1.90% 20.05.21 177 17.55 3.90% 14.05.21 3 18.05.21 7 23.05.21 12
Kerala 3,34,06,061 12.05.21 38153 1,142 17.05.21 5 23.05.21 11
Punjab 2,77,43,338 12.05.21 8576 309 2.10% 20.05.21 203 7.32 3.00% 17.05.21 5 21.05.21 9
West Bengal 9,12,76,115 15.05.21 20085 220 0.70%
AP 4,95,77,103 20.05.21 22051 445 0.50%
Odisha
Tamil Nadu
Peak Cases Peak Deaths Decline in Cases
• States bordering Maharashtra appear to have been hit first. UP and Delhi have got included in this list perhaps due to
high traffic between these states. The rest of the country has followed with the East Coast States to be impacted last.
• There is no consistency in cases or deaths/Mn or CFR
• However the shape of the curve in terms of days taken to decline is quite similar. As the infection spreads further, the
decline is faster

19. Discussion
• The spread of the 2nd wave has been swift. Most of the country has peaked within 3 – 4 weeks of each other. This implies that the
dominant variant B.1.617.2 spreads extremely rapidly
• After the peak, the decline is also quite consistent. There are 2 points here:
• States that peaked close to each other follow a similar decline curve
• The decline curve is steeper for those states that reached peak later – does this indicate a weakening in the virus strain with time?
• Anecdotally, having watched several programs coming in from rural UP, even the rural, uncounted cases and deaths have declined
in the last 2 weeks.
• The consistency of the rise and fall across states, urban and rural implies that human intervention – lockdowns, social behaviour
etc have relatively low impact on the progress of the virus. This time around the states were implementing their own policies and
it is hard to imagine that a poor, rural oriented state like UP or Bihar could implement anything as effectively as Delhi or Mumbai.
Is there something inbuilt in the virus that causes these peaks and troughs?
• Speculatively, are virus mutation cycles and the life cycle of new variants becoming shorter? Both UK with B.1.117 and India with
B.1.617.2 have experienced short, intense peaks
• Clearly, new variants are a big danger. Genome sequencing and big data to throw up abnormal trends are the way forward to
identify these as they emerge

20. Vaccination

21. • I am not commenting on the supply side of
vaccines for India
• We should be primarily concerned about the
output and that should determine how we steer
the program. Our progressive average stands at
just 1.5 Mn doses a day since we started the
program. The current 7DMA is also at 1.5Mn
• The govt has stated that 85Mn doses are going to
be available in the month of May. That translates
to 2.8Mn doses/day. As of now there is no
evidence of that
• Going forward, June and possibly most of July
will still be around this level

22. India Population
Urban Rural Total Urban Rural Total Doses
0 - 5 3,65,79,569 10,22,81,439 13,88,61,008 4,44,94,234 11,47,79,342 15,92,73,576
6 - 12 4,84,03,025 13,56,41,231 18,40,44,256 5,88,75,913 15,18,54,760 21,07,30,673 42,14,61,346
13 -17 3,50,95,752 8,61,52,314 12,12,48,066 4,26,89,366 9,63,82,166 13,90,71,532 27,81,43,063
18 - 25 6,18,67,003 12,61,42,532 18,80,09,535 7,52,53,072 14,09,57,894 21,62,10,965 43,24,21,931
26 - 35 6,61,21,272 12,45,42,197 19,06,63,469 8,04,27,830 13,78,81,842 21,83,09,672 43,66,19,344
36 - 44 4,49,55,830 8,42,00,335 12,91,56,165 5,46,82,854 9,32,00,955 14,78,83,809 29,57,67,618
45 - 60 5,66,66,304 11,16,78,021 16,83,44,325 6,89,27,105 12,46,68,868 19,35,95,974 38,71,91,948
61 + 2,58,41,020 6,01,97,331 8,60,38,351 3,14,32,202 6,83,72,285 9,98,04,487 19,96,08,974
Unstated 15,76,350 29,13,452 44,89,802 19,17,422 32,01,889 51,19,312 1,02,38,624
Total 37,71,06,125 83,37,48,852 1,21,08,54,977 45,87,00,000 93,13,00,000 1,39,00,00,000 2,46,14,52,848
2011 2021 Est

23. A long road ahead
Cum Balance
Upto 30.04.21 1.05.21 15,00,000 20,00,000 50,00,000 80,00,000
0 - 5
6 - 12
13 -17
18 - 25 1,60,68,58,803 1,071 803 321 201
26 - 35
36 - 44
45 - 60 44,20,49,911 295 221 88 55
61 +
15,49,89,635 2,30,64,63,213 1,538 1,153 492 308
No of Days

24. Vaccination - Issues
• Availability
• Local manufacturing capacity
• Imported availability
• Pricing
• Logistics
• Need based focus
• Demand forecasting
• Distribution
• Movement
• Bottlenecks
• Booking and registrations are not possible without a
smart phone
• Cowin App slow
• Way Forward
• Vaccine procurement and movement to States by
Centre via an empowered committee with clearly
defined targets; Application by States. States that have
floated global tenders have met with no response.
• Vaccination just based on Aadhar card and mobile
phone. No need for booking and pre registration
• Uploading to Cowin to be done by vaccination centre
later to capture full picture
• Vaccination centres – open it up for door to door and
chemists/supermarkets. Camps in villages. The risks are
far less than the return
• Massive publicity and carrot and stick approach is
needed. For example, no entry into trains, planes,
movie halls, work places without vaccination

25. Questions for Discussion
• Third wave is inevitable. How to identify new mutant variants early
• Medical Infrastructure and Oxygen Availability
• Vaccination
• Role of Centre/States/Private Sector
• Availability going forward
• Capacity Enhancement of local manufacture of two existing vaccines
• New Vaccines for local manufacture
• Imports of new vaccines
• Effectiveness against mutant strains. Role of local labs and international
support

26. Thank You!
Please mail me at debubhatnagar@gmail.com
with any comments.
Disclaimer: These projections and analysis are not official and are the work of an
amateur. They should not be the basis of any decision making.