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Preliminary Analysis of Excess Mortality in India during the Covid-19 Pandemic (Update June 27).

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Abstract and Figures

The pandemic-related mortality through June 27, 2021 in 14 Indian states was estimated to be 106.3 to 145.4 per 100,000 population. If these rates apply to India as a whole, then between 1.44 to 1.97 million people may have perished in India as a result of the Covid-19 pandemic by June 27, 2021. This per-capita mortality rate is similar to that in the United States and many other regions.
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Preliminary Analysis of Excess Mortality in India During the Covid-19 Pandemic
(Update June 27, 2021).
Christopher T. Leffler, MD, MPH.1,2
June 27, 2021.
1. Department of Ophthalmology. Virginia Commonwealth University. Richmond, VA 23298.
chrislefflermd@gmail.com
2. Department of Ophthalmology. Hunter Holmes McGuire VA Medical Center, Richmond, VA.
Corresponding author: Christopher T. Leffler, MD, MPH.
Department of Ophthalmology. Virginia Commonwealth University. 401 N. 11th St., Box 980209,
Richmond, VA 23298. chrislefflermd@gmail.com.
The author has no conflicts of interest to disclose.
Abstract.
Background. As both testing for SARS Cov-2 and death registrations are incomplete or
not yet available in many countries, the full impact of the Covid-19 pandemic is currently
unknown in many world regions.
Methods. We studied the Covid-19 and all-cause mortality in 14 Indian states, with a
combined population of over 1.11 billion, with available all-cause mortality data during
the pandemic for the state as a whole, or for large cities: Gujarat, Karnataka, Kerala,
Maharashtra, Tamil Nadu, West Bengal, Delhi, Madhya Pradesh, Andhra Pradesh,
Telangana, Assam, Bihar, Odisha and Uttar Pradesh. Excess mortality was calculated
by comparison with available data from years 2015-2019. The known Covid-19 deaths
reported by the Johns Hopkins University Center for Systems Science and Engineering
for a state were assumed to be accurate, unless excess mortality data suggested a
higher toll during the pandemic.
Results. In several regions, fewer deaths were registered in 2020 than expected. The
excess mortality in 2020 was 165.4 / 100K combining data from Mumbai and Nagpur
(both in Maharashtra). Areas in Tamil Nadu, Kolkata (in West Bengal), Delhi, Madhya
Pradesh, Karnataka, and Andhra Pradesh saw spikes in mortality in the spring of 2021.
Conclusions. The pandemic-related mortality through June 27, 2021 in 14 Indian states
was estimated to be 106.3 to 145.4 per 100,000 population. If these rates apply to India
as a whole, then between 1.44 to 1.97 million people may have perished in India as a
result of the Covid-19 pandemic by June 27, 2021. This per-capita mortality rate is
similar to that in the United States and many other regions.
2
Introduction.
As both testing for SARS Cov-2 and death registrations are incomplete or not yet
available in many countries, the full impact of the Covid-19 pandemic is currently
unknown in many world regions. One approach to assess the impact of the pandemic
which is currently gathering momentum is to look at excess mortality from all causes.
When all-cause mortality increases during the pandemic, this is assumed to be a result
of infection with the Sars Cov-2 virus, or indirect effects from health system overload or
social responses to the pandemic.
For many countries, national tallies of mortality during portions of the pandemic
have already become available. In India, regional government websites and data
journalists are publishing up-to-date mortality figures for an ever-increasing number of
cities and states. We sought to integrate these data to estimate the impact of the
Covid-19 pandemic in India as a whole. We understand that the picture might change
as the pandemic proceeds, and as more data become available.
Methods.
We used the publicly available mortality figures published by regional governments
(Kerala, Odisha, Karnataka, and Tamil Nadu) and uncovered by data journalists in India
(Hindustan Times 2021; Ramani “Hindu” 2021; Ramani “docs” 2021; Scroll 2021; Nagar
2021; The Hindu 2020; Khanna 2020; Saikia 2021; Radhakrishnan 2021), such as
reports from Rukmini based on data from the Civil Registration System (Rukmini 2021;
Rukmini “Andhra” 2021). Most of these data are stored on the World Mortality GitHub
websites maintained by Ariel Karlinsky, Dmitry Kobak, and colleagues (Karlinsky 2021;
Karlinsky & Kobak 2021). We also reviewed the publicly available data on Covid-19
mortality tabulated by the Johns Hopkins University Center for Systems Science and
Engineering (CSSE) (2021). For the urban portions of 25 districts in Madhya Pradesh,
the numbers of funerals in April 2021 have been tabulated (Datta 2021). All of these
publicly available regional-level mortality data contain no individually-identifiable
information. The study was approved by the Office of Research Subjects Protection of
Virginia Commonwealth University.
We calculated excess mortality in a region by comparing the mortality for a given
time period in 2020 or 2021 with the value expected based on the years 2015 to 2019.
If data from more than one year before 2020 was available, the expected value was
calculated by creating a trend line for mortality by linear regression for the years 2015 to
2019, and carrying this trend one year (for 2020) or two years (for 2021) into the future.
Carrying the trend line two years into the future for 2021 yielded conservative estimates
of excess deaths.
3
For Gujarat, Karnataka, Bihar, Kerala, and the urban portions of 25 districts in
Madhya Pradesh, mortality from entire year(s) before 2020 was available (Vital
Statistics reports). Therefore, to estimate excess mortality for portions of 2021, it was
necessary to assume that mortality was evenly distributed throughout the year.
The vital statistics reports for India were used to generate a trend line for
expected deaths, using the data from 2015 to 2019. For some states, reported mortality
from the state government websites or right-to-information (RTI) requests was only
available for 2018 and 2019, which was too short a period to generate a robust trend
line. Moreover, the numbers of deaths from the state sources did not match the central
government figures exactly, because the state information systems did not capture all of
the registered deaths. In these cases, the expected number of deaths was scaled up or
down by multiplying the 2015 to 2019 trend line by the ratio of deaths in the state and
federal systems for 2018 and 2019. For instance, if the state website average mortality
for 2018 and 2019 was 97% of the figures for 2018 and 2019 in the federal reports, the
trend line was multiplied by 0.97. This method was used to scale the trend line for
Delhi, Bengaluru, Mumbai, Nagpur, Ahmedabad (for 2020), Madhya Pradesh, Tamil
Nadu, for 6 city hospitals in Tamil Nadu, and for Madurai district.
We assumed that the mortality rate related to the Covid-19 pandemic in a given
region was equivalent to the mortality reported by the Johns Hopkins University CSSE
(based on positive viral testing and clinical symptoms), unless the excess mortality data
suggested a higher toll. When data for a given region and time period were conflicting
or contradictory, we reported a range of estimates to reflect the uncertainty.
The national mortality rate was estimated by summing the estimated pandemic-
related deaths for the states analyzed and dividing by the population of these states.
The population of Indian states was taken from the Hopkins mortality dataset. Selected
raw data are in the appendix (Table S1).
4
Results.
We studied 14 states for which excess mortality data were available for at least a
portion of the state: Gujarat, Karnataka, Kerala, Maharashtra, Tamil Nadu, West
Bengal, Delhi, Madhya Pradesh, Andhra Pradesh, Telangana, Assam, Bihar, Odisha
and Uttar Pradesh. These 14 states have a combined population of 1.11 billion people.
Reported Covid-19 Mortality.
The mortality related to Covid-19, based on viral testing and the clinical picture,
as tabulated by Johns Hopkins, was reasonably low: 11.4 / 100K in 2020, and 12.8 /
100K in 2021, for a combined total of 24.2 / 100K for the pandemic, as of June 5, 2021
(Table 1). There was some variation, with lower mortality rates in Gujarat, West Bengal,
Telangana, Assam, Odisha, Uttar Pradesh, and Bihar and higher mortality rates in
Maharashtra and Delhi (Table 1).
Table 1. Covid-19 Deaths Based on Viral Testing and Clinical Symptoms, as Tabulated
by Johns Hopkins University.
Region.
Population
Reported
Covid
Deaths in
2020
Deaths/100K
in 2020
Reported
Covid
deaths by
June 5,
2021.
Deaths/100K
in 2021 (as
of June 5)
Delhi
18,710,920
10,523
56.240
24,497
74.683
Karnataka
67,562,700
12,081
17.881
30,895
27.847
Maharashtra
123,144,200
49,463
40.167
98,771
40.041
Gujarat
63,872,400
4,302
6.735
9,906
8.774
Tamil Nadu
77,841,270
12,109
15.556
26,128
18.010
West Bengal
99,609,300
9,683
9.721
16,034
6.376
Kerala state
35,699,440
3,042
8.521
6,468
18.118
Madhya Pradesh
85,358,970
3,595
4.212
8,207
5.403
Andhra Pradesh
53,903,393
7,104
13.179
11,296
7.777
Telangana
39,362,732
1,541
3.915
3,346
8.500
Assam State
35,607,039
1,043
2.929
3,577
7.117
Bihar
124,799,930
1,393
1.116
5,319
3.146
Uttar Pradesh
237,882,725
8,352
3.511
21,031
5.330
Odisha
46,356,334
1,871
4.036
2,912
2.246
Total
1,109,711,353
126,102
11.363
268,387
12.822
Data from June 5, 2021.
5
Excess Mortality.
Excess mortality data was available for 12 states in 2020 (Table 2), and 12 states
in 2021 (Table 3). The best available estimates of the mortality range, whether based
on reported Covid-19 deaths, or based on excess mortality, are tabulated in Table 4.
Table 2. Excess mortality in India from Jan. 1, 2020 to Dec. 31, 2020.
Region.
Population
Period in
2020
Excess
deaths
Deaths/100K
Dehli
18,710,920
Apr-May
-9,702
-51.852
Entire state
67,562,700
Entire year
6,406
9.481
Bengaluru
8,443,675
Jan-Jul
9,455
111.986
Mumbai
12,875,213
Jan-Sep
20,859
162.007
Nagpur
2,405,000
Apr-Dec
4,414
183.550
Gujarat
63,872,400
Jan-Nov
-71,664
-112.198
Ahmedabad
8,059,000
Apr to May
5,276
65.466
Tamil Nadu
77,841,270
All
72,052
92.563
Chennai
7,088,000
All
5,921
83.540
6 cities
5,980,370
Jan-May
-1,032
-17.261
Madurai dist.
3,038,250
Entire year
2,018
66.412
Kolkata
4,496,694
All
2,075
46.145
Hyderabad
9,482,000
All
8,359
88.157
Kerala
35,699,440
All
-27,367
-76.659
Madhya Pradesh
85,358,970
All
-26,899
-31.512
Andhra Pradesh
53,903,393
All
48,324
89.649
Assam State
35,607,039
All
3,576
10.043
Uttar Pradesh
237,882,725
All
-14,941
-27.718
The 6 government hospitals in Tamil Nadu studied by Arappor Iyakkam from Jan-May 2020 were in
Madurai, Coimbatore, Trichy, Vellore, Karur, and Tirupur.
6
Table 3. Excess mortality in India, early 2021.
State
Subregion.
Population
Excess
deaths,
Jan-Jun,
2021
Excess
mortality /
100K
Delhi
18,710,920
12,553
67.091
Tamil Nadu
Chennai
7,088,000
11,025
155.545
Entire state
77,841,270
146,085
187.670
6 cities
5,980,370
14,160
236.776
Madurai dist.
3,038,250
2,325
76.508
West Bengal
Kolkata
4,496,694
2,901
64.514
Telangana
Hyderabad
9,482,000
6,805
71.768
Gujarat
Entire state
63,872,400
23,996
37.569
Ahmedabad
8,059,000
2,935
36.417
Madhya
Pradesh
25 districts
25,412,510
11,785
46.376
Entire state
85,358,970
150,890
176.771
Karnataka
Entire state
67,562,700
72,591
107.442
Bengaluru
8,443,675
54,346
643.631
Andhra Pradesh
53,903,393
106,673
197.896
Bihar
124,799,930
81,745
65.501
Kerala
35,699,440
-23,240
-65.099
Uttar Pradesh
237,882,725
40,513
17.031
Odisha
46,356,334
33,680
72.654
Delhi mortality data available for April and May 2021. Gujarat, including Ahmedabad, mortality available
from Mar 1 to May 10, 2021. Kolkata 2021 mortality available through week 20 (ending May 23).
Chennai 2021 mortality available through week 19 (ending May 16). Madhya Pradesh and Hyderabad
data available through May 31. Karnataka data available through June 26, 2021. Bengaluru data
available through June 15, 2021 (Chatterjee 2021). Tamil Nadu data available through June 27, 2021
(crstn.org). The 6 government hospitals in Tamil Nadu studied by Arappor Iyakkam from Jan-May 2021
were in Madurai, Coimbatore, Trichy, Vellore, Karur, and Tirupur. Madurai district data from Jan-May
2021 (Radhakrishnan 2021). Bihar data available Jan to May 2021. Kerala data were available through
June 27, 2021. Uttar Pradesh data available Jan 1-Apr 30, 2021 (Das). The urban areas in Madhya
Pradesh from which funeral counts were tabulated for April 2021 were from the following 25 districts:
Barwani, Bhind, Bhopal, Burhanpur, Chhatarpur, Chhindwara, Dewas, Dhar, Gwalior, Indore, Jabalpur,
Jhabua, Khandwa, Mandsaur, Morena, Neemuch, Ratlam, Sagar, Satna, Seoni, Shahdol, Shivpuri,
Singroli, Tikamgarh, Vidisha (Datta 2021). Odisha data downloaded June 27, 2021.
7
Table 4. Estimated Covid-19 Deaths in India in 2020 and early 2021.
State
Population
Type
Data
Source(s)
2020
2021, by June 27
Deaths/100K
Deaths
Deaths/100K
Deaths
Delhi
18,710,920
--
Hopkins,
Delhi
56.240
10,523
75.154
14,062
Karnataka
67,562,700
Low
Hopkins,
Karnataka
17.881
12,081
107.442
72,591
High
Bengaluru
111.986
75,661
--
--
Maharashtra
123,144,200
--
Mumbai &
Nagpur
165.397
203,676
--
--
Gujarat
63,872,400
Low
Hopkins,
Gujarat
6.735
4,301
37.569
23,996
High
Ahmedabad
65.466
41,815
Tamil Nadu
77,841,270
Low
Hopkins,
Madurai
15.556
12,109
76.508
59,555
High
Tamil Nadu
92.563
72,052
187.670
146,085
West Bengal
99,609,300
--
Kolkata
46.145
45,965
64.514
64,262
Telangana
39,362,732
--
Hyderabad
88.157
34,701
71.768
28,250
Kerala
35,699,440
--
Hopkins
8.521
3,042
18.118
6,468
Madhya
Pradesh
85,358,970
Low
Hopkins, 25
Districts
4.212
3,595
46.376
39,586
High
Entire state
176.771
150,890
Andhra
Pradesh
53,903,393
--
Entire state
89.649
48,324
197.896
106,673
Assam
35,607,039
--
Assam
10.043
3,576
Bihar
124,799,930
--
Bihar
--
--
151.651
81,745
Uttar
Pradesh
237,882,725
--
Uttar
Pradesh
3.511
8,352
17.031
40,513
Odisha
46,356,334
Odisha
--
--
72.654
33,680
Total with
2020 data.
938,555,089
Low
41.579
390,245
High
58.737
551,282
Total with
2021 data
887,087,714
Low
64.754
574,423
High
86.712
769,215
All estimates based on excess deaths, except 2020 Delhi and Kerala data, which are based on known
Covid-19 mortality as reported by Johns Hopkins University, and Gujarat, West Bengal, Madhya Pradesh,
and Tamil Nadu, which included the Hopkins data as the low end of the uncertainty range.
For Kerala, Delhi, Madhya Pradesh, and Uttar Pradesh, the excess mortality
based on registered deaths was actually negative for 2020. This may be because fewer
people were willing to register deaths during lockdown, or because fewer people died
from accidents and other causes during lockdown (Table 1).
At the other extreme, in Maharashtra, the excess mortality in Mumbai and
Nagpur was 165.4 / 100K in 2020, with both cities having similar values (Table 2 and 4).
Similarly, Bengaluru in Karnataka had an excess mortality of 112.0 / 100K in the first 7
months of 2020 (Tables 2 and 4).
For 2020, intermediate levels of excess mortality were seen for Kolkata in West
Bengal (64.5 / 100K), Chennai in Tamil Nadu (83.5 / 100K), and Hyderabad in
Telangana (88.2 / 100K) (Tables 2, 4).
8
The data from Gujarat in 2020 were conflicting. The state as a whole had
negative excess mortality from Jan. 1 to Nov 30, 2020 (Table 2). On the other hand, the
Gujarat city of Ahmedabad (population 8 million) experienced excess mortality in April
and May 2020 of 65.5 / 100K (Table 2). This discrepancy might indicate that people
were reluctant to register deaths with Gujarat authorities. Due to the uncertainties, we
adopted a wide range of Covid-19-related mortality for Gujarat for 2020, with the
Hopkins number (6.7 / 100K) at the low end and the Ahmedabad number (65.5 / 100K)
at the high end (Tables 1, 2, 4).
For 2021, a significant peak in all-cause mortality was seen for March through
early June for Chennai in Tamil Nadu, Kolkata in West Bengal, Delhi, Madhya Pradesh,
and Andhra Pradesh (Tables 3, 4). These findings correspond with news reports of
increasing severity of the pandemic in India. During this portion of 2021, the excess
mortality was 64.5 / 100K for Kolkata, 155.5 / 100K for Chennai in Tamil Nadu, 67.1 /
100K for Delhi, 176.8 / 100K for Madhya Pradesh, and 197.9 / 100K for Andhra Pradesh
(Tables 3, 4).
Integrated Model of Covid-19-related Mortality.
A model of pandemic-related mortality which integrates the available data is
shown in Table 4. Generally, the Covid-19-related mortality is assumed to be the
excess mortality. However, the Hopkins data on reported Covid-19 deaths were used
for Kerala and Delhi in 2020, and for the low end of the uncertainty range for several
regions.
Despite the wide uncertainty ranges for several states and time periods, the
overall uncertainty range is more narrow. For 2020, the pandemic-related mortality for
12 states with a population of 939 million was estimated to be 41.6 to 58.7 / 100K
(Table 4). For 2021, through June 27, the pandemic-related mortality for 12 states with
a population of 887 million was estimated to be 64.8 to 86.7 / 100K (Table 4).
Summing these estimates for 2020 and 2021, we estimate the pandemic-related
mortality to be: 106.3 to 145.4 per 100,000 population for the entire pandemic (through
June 27, 2021). Assuming a population of India of 1,352,642,280, these rates
correspond with a mortality range of 1.44 to 1.96 million people perishing during the
pandemic in India from Covid-19 by June 27, 2021.
9
Discussion.
This analysis of excess mortality found that between 1.44 to 1.96 million people
may have perished in India as a result of the Covid-19 pandemic, as of June 27, 2021.
It should be noted that the estimated per-capita mortality of 106 to 145 per 100,000 in
India is similar to that of the United States and many other regions.
This mortality level is well above the reported Covid-19 mortality in India of
248,016, and above the level of 736,811 estimated by the IHME at the University of
Washington, as of May 13, 2021 (IHME 2021). It should be noted, however, that the
IHME did not actually look at all-cause mortality in India, as far as we know. Rather,
they made a guess about what Indian all-cause mortality might be, based on factors
such as test positivity rates in India, and all-cause mortality data from other countries,
such as Mexico, Brazil, and the United States. Our analysis was based on actual
counts of mortality in India, and therefore was a more direct approach to finding the
answer.
Our method of determining the expected baseline, by making a projection using
linear regression one year (for 2020) or two years (for 2021) into the future, was more
conservative than simply using the baseline average mortality, or projecting just one
year forward (even for 2021). In other words, our analysis used the accepted Covid
mortality, unless there was very compelling excess mortality data to reject the official
numbers. Thus, our estimates of pandemic-related mortality for various regions are
more conservative (i.e. lower) than some news reports.
The analysis has a number of limitations. The data are still incomplete for many
regions and times. There may be delays in registering deaths. Available data obtained
from regional government websites, central government compilations, and by reporters
through RTI requests are not in complete agreement. Some of the data upon which the
model is based may simply be wrong, because early reports can contain errors. All-
cause mortality may be higher not only due to infection with the Sars Cov-2 virus, but
also because of health system overload or social changes, such as lockdowns. We
know that a number of countries experienced lower than normal mortality during the
pandemic. Examples include New Zealand, Australia, and some Asian countries.
Lower mortality rates may occur because there are fewer accidents or homicides, etc.
On the other hand, other factors might lead to higher mortality rates during lockdowns in
some regions.
Time will tell what the true death toll has been, as the early data are confirmed,
and as additional regions in India provide more complete mortality data, and data from
diverse sources are reconciled. The Sample Registration System directly assesses
mortality in India, and may ultimately provide the best estimate of how the pandemic
affected mortality rates.
10
Acknowledgments.
The author would like to acknowledge the data journalists, academicians, and
nonprofits in India who have brought these data to light, such as Rukmini S.
(@Rukmini), Chinmay Tumbe (@ChinmayTumbe), Vignesh Radhakrishnan
(@VigneshJourno), Srinivasan Ramani (@vrsrini), Deepak Patel (@deepakpatel_91),
Murad Banaji (@muradbanaji), Sumitra Debroy (@debroysumitra), Dhanya Rajendran
(@dhanyarajendran), Shiba Kurian (@shiba_kurian), and Arappor Iyakkam. In addition,
we acknowledge the important work of Ariel Karlinsky and colleagues for preparing the
mortality databases we used, and for pointing out to us numerous relevant resources.
However, all errors in the paper are the responsibility of the author.
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mortality-due-covid-19-and-scalars-reported-covid-19-deaths Accessed June 6, 2021.
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do not prove allegations of massive undercounting of Covid deaths. OpIndia. May 15,
2021. Available from: https://www.opindia.com/2021/05/gujarat-covid-19-deaths-death-
certificate-statistics-divya-bhaskar/ Accessed June 14, 2021. [Has Gujarat and
Ahmedabad data.]
Radhakrishnan S. Is Madurai undercounting Covid deaths? Data raise questions. The
New Indian Express. June 18, 2021. Available from:
https://www.newindianexpress.com/states/tamil-nadu/2021/jun/18/is-madurai-
undercounting-covid-deaths-data-raise-questions-2317785.html Accessed June 17,
2021.
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end of May 2021. The News Minute. Available from:
https://www.thenewsminute.com/article/tnm-exclusive-kerala-reports-almost-14000-
excess-deaths-till-end-may-2021-151124 Accessed June 23, 2022.
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COVID-19 toll for Telangana. The Hindu. June 14, 2021. Available from:
https://www.thehindu.com/news/cities/Hyderabad/excess-deaths-in-hyderabad-are-10-
times-the-official-covid-19-toll-for-telangana/article34807214.ece Accessed June 14,
2021.
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xDOkv1zg/edit#gid=0 Accessed June 14, 2021.
Ramani S, Kannan R. Excess deaths in Tamil Nadu over four times official COVID-19
tally. The Hindu. June 16, 2021. https://www.thehindu.com/news/national/tamil-
nadu/excess-deaths-in-tamil-nadu-over-four-times-official-covid-19-
tally/article34834150.ece?homepage=true Accessed June 17, 2021.
Rukmini S. Madhya Pradesh saw nearly three times more deaths than normal after
second wave of Covid-19 struck. Scroll.In. June 12, 2021. Available from:
https://scroll.in/article/996772/madhya-pradesh-saw-nearly-three-times-more-deaths-
than-normal-after-second-wave-of-covid-19-struck Accessed June 12, 2021.
Rukmini S. Andhra Pradesh saw 400% increase in deaths in May, Tamil Nadu saw
more modest excess mortality. Scroll.In. June 13, 2021. Available from:
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17, 2020. Available from: https://www.indiaspend.com/how-india-could-fill-in-the-blanks-
on-excess-mortality/ Accessed June 27, 2021.
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June 16, 2021.
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Covid-19 struck. Scroll.in. June 16, 2021. Available from:
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15
Appendix.
Table S1. Time Series of Mortality from Selected Regions in India.
Region
Year
Period
Deaths
Reference
Andhra Pradesh
2015
All
310,640
Vital Statistics
Andhra Pradesh
2016
All
313,285
Vital Statistics
Andhra Pradesh
2017
All
355,546
Vital Statistics
Andhra Pradesh
2018
All
375,777
Vital Statistics
Andhra Pradesh
2019
All
401,472
Vital Statistics
Andhra Pradesh
2018
All
333,275
Rukmini “AP”
Andhra Pradesh
2019
All
363,414
Rukmini “AP”
Andhra Pradesh
2020
All
428,907
Rukmini “AP”
Andhra Pradesh
2018
Months 1-5
140,102
Rukmini “AP”
Andhra Pradesh
2019
Months 1-5
147,662
Rukmini “AP”
Andhra Pradesh
2020
Months 1-5
134,632
Rukmini “AP”
Andhra Pradesh
2021
Months 1-5
272,910
Rukmini “AP”
Assam State
2015
All
116,778
Vital Statistics
Assam State
2016
All
130,414
Vital Statistics
Assam State
2017
All
141,012
Vital Statistics
Assam State
2018
All
142,605
Saikia, Vital St.
Assam State
2019
All
163,057
Saikia, Vital St.
Assam State
2020
All
187,085
Saikia
Bihar
2015
All
204,093
Vital Statist.
Bihar
2016
All
177,021
Vital Statist.
Bihar
2017
All
261,425
Vital Statist.
Bihar
2018
All
213,989
Vital Statist.
Bihar
2019
All
359,349
Vital Statist.
Bihar
2019
Jan-May
130,000
Alavi
Bihar
2021
Jan-May
220,000
Alavi
Delhi
2015
All
124,516
Vital Statistics
Delhi
2016
All
141,632
Vital Statistics
Delhi
2017
All
136,117
Vital Statistics
Delhi
2018
All
145,533
Vital Statistics
Delhi
2019
All
145,284
Vital Statistics
Delhi
2019
Apr-May
19,047
Hindust. Tim.
Delhi
2020
Apr-May
10,258
Hindust. Tim.
Delhi
2021
Apr-May
33,109
Hindust. Tim.
Gujarat
2015
All
412,322
Vital Statistics
Gujarat
2016
All
417,835
Vital Statistics
Gujarat
2017
All
388,316
Vital Statistics
Gujarat
2018
All
433,256
Vital Statistics
Gujarat
2019
All
462,284
Vital Statistics
Gujarat
2017
Jan 1-Nov 30
368,000
Dave
16
Gujarat
2018
Jan 1-Nov 30
393,000
Dave
Gujarat
2019
Jan 1-Nov 30
419,000
Dave
Gujarat
2020
Jan 1-Nov 30
374,000
Dave
Gujarat
2020
Mar. 1-May 10
58,000
Desai
Gujarat
2021
Mar. 1-May 10
123,871
Desai
Gujarat:
Ahmedabad
2017
Mar. 1-May 10
9,319
Opindia
2018
Mar. 1-May 10
9,866
Opindia
2019
Mar. 1-May 10
9,950
Opindia
2020
Mar. 1-May 10
7,786
Opindia
2021
Mar. 1-May 10
13,593
Opindia
Gujarat:
Ahmedabad
2019
Apr-May
5,490
Khanna
2020
Apr-May
10,708
Khanna
Karnatka:
Bengaluru
2019
Jan-July
37,001
The Hindu
2020
Jan-July
49,135
The Hindu
2021
Jan 1-June 15
87,082
Chatterjee
Karnataka
2015
All
393,731
Srivat., Vit. S.
Karnataka
2016
All
420,774
Srivat., Vit. S.
Karnataka
2017
All
481,747
Srivat., Vit. S.
Karnataka
2018
All
483,511
Srivat., Vit. S.
Karnataka
2019
All
508,584
Srivat., Vit. S.
Karnataka
2020
All
551,808
Srivatsa
Karnataka
2018
Jan-June 15
224,000
Chatterjee
Karnataka
2019
Jan-June 15
235,000
Chatterjee
Karnataka
2021
Jan-June 15
337,580
Chatterjee
Karnataka
2021
Jan 1-June 26
351,255
karnataka.gov
Kerala
2015
Entire year
235,982
Rajendran
Kerala
2016
Entire year
244,900
Rajendran
Kerala
2017
Entire year
252,103
Rajendran
Kerala
2018
Entire year
255,594
Rajendran
Kerala
2019
Entire year
264,150
Rajendran
Kerala
2020
Entire year
252,421
Rajendran
Kerala
2021
Jan 1-May 31
113,372
Rajendran
Kerala
2015
All
252,576
Vital Statistics
Kerala
2016
All
256,130
Vital Statistics
Kerala
2017
All
263,342
Vital Statistics
Kerala
2018
All
258,530
Vital Statistics
Kerala
2019
All
270,567
Vital Statistics
Kerala
2015
All
236,859
lsgkerala.gov
Kerala
2016
All
244,894
lsgkerala.gov
Kerala
2017
All
252,097
lsgkerala.gov
Kerala
2018
All
255,571
lsgkerala.gov
Kerala
2019
All
264,131
lsgkerala.gov
Kerala
2020
All
242,910
lsgkerala.gov
Kerala
2021
Jan 1-June 27
111,747
lsgkerala.gov
Madhya Pradesh
2015
All
311,411
Vital Statistics
17
Madhya Pradesh
2016
All
338,587
Vital Statistics
Madhya Pradesh
2017
All
370,538
Vital Statistics
Madhya Pradesh
2018
All
424,527
Vital Statistics
Madhya Pradesh
2019
All
493,328
Vital Statistics
Madhya Pradesh
2018
Months 1-12
407,172
WM
Madhya Pradesh
2019
Months 1-12
449,819
WM
Madhya Pradesh
2020
Months 1-12
461,057
WM
Madhya Pradesh
2018
Months 1-5
152,346
WM
Madhya Pradesh
2019
Months 1-5
167,549
WM
Madhya Pradesh
2020
Months 1-5
164,191
WM
Madhya Pradesh
2021
Months 1-5
348,708
WM
Madhya
Pradesh: urban
regions of 25
districts
2015
Entire year
119,068
Vital Statistics
2016
Entire year
112,303
Vital Statistics
2017
Entire year
113,612
Vital Statistics
2018
Entire year
112,188
Vital Statistics
2019
Entire year
119,914
Vital Statistics
2021
April 1-30
21,456
Datta
Maharashtra
2015
Entire year
673,824
Vital Statistics
Maharashtra
2016
Entire year
666,448
Vital Statistics
Maharashtra
2017
Entire year
647,161
Vital Statistics
Maharashtra
2018
Entire year
667,900
Vital Statistics
Maharashtra
2019
Entire year
693,800
Vital Statistics
Maharashtra:
Mumbai
2018
Jan-Sep
95,192
WM, Debroy
2019
Jan-Sep
96,956
WM, Debroy
2020
Jan-Sep
117,130
WM, Debroy
Nagpur City
2019
Months 4-12
16,238
WM
Nagpur City
2020
Months 4-12
20,382
WM
Odisha
2015
All year
321,009
Vital statistics
Odisha
2016
All year
345,527
Vital statistics
Odisha
2017
All year
322,660
Vital statistics
Odisha
2018
All year
328,799
Vital statistics
Odisha
2019
All year
342,947
Vital statistics
Odisha
2021
Jan 1-June 27
200,974
odisha.gov.in
Tamil Nadu, 6 cities:
Madurai,
Coimbatore, Trichy,
Vellore, Karur,
Tirupur.
2019
Jan-May
10,587
Nagar
2020
Jan-May
9,432
Nagar
2021
Jan-May
18,587
Nagar
Tamil Nadu:
Madurai District.
2019
All
19,735
Radhakrishnan
2020
All
21,524
Radhakrishnan
2019
Jan-May
8,789
Radhakrishnan
2020
Jan-May
7,724
Radhakrishnan
2021
Jan-May
11,208
Radhakrishnan
Tamil Nadu
2015
All year
568,271
Vital Statistics
2016
All year
563,625
Vital Statistics
2017
All year
580,496
Vital Statistics
18
2018
All year
574,006
Vital Statistics
2019
All year
633,897
Vital Statistics
Tamil Nadu
2018
Entire year
549,209
crstn.org
2019
Entire year
637,270
crstn.org
2020
Entire year
687,488
crstn.org
2021
Jan 1-June 27
453,000
crstn.org
Tamil Nadu
2018
All year
536,192
WM; Ramani
2019
All year
588,221
WM; Ramani
2020
All year
644,291
WM; Ramani
2018
Jan-May
236,838
WM; Ramani
2019
Jan-May
250,289
WM; Ramani
2020
Jan-May
245,328
WM; Ramani
2021
Jan-May
318,245
WM; Ramani
Tamil Nadu:
Chennai
2015
Weeks 1-52
59,875
WM
2016
Weeks 1-52
57,826
WM
2017
Weeks 1-52
63,726
WM
2018
Weeks 1-52
62,793
WM
2019
Weeks 1-52
67,002
WM
2020
Weeks 1-52
73,932
WM
2015
Weeks 1-19
21,790
WM
2016
Weeks 1-19
21,544
WM
2017
Weeks 1-19
22,495
WM
2018
Weeks 1-19
23,002
WM
2019
Weeks 1-19
23,912
WM
2020
Weeks 1-19
22,122
WM
2021
Weeks 1-19
35,854
WM
Telangana:
Hyderabad
2016
Jan-Dec
49,523
WM, Ramani
2017
Jan-Dec
52,710
WM, Ramani
2018
Jan-Dec
55,026
WM, Ramani
2019
Jan-Dec
66,131
WM, Ramani
2020
Jan-Dec
77,241
WM, Ramani
Telangana:
Hyderabad
2016
Jan-May
18,839
WM, Ramani
2017
Jan-May
20,645
WM, Ramani
2018
Jan-May
21,696
WM, Ramani
2019
Jan-May
25,657
WM, Ramani
2020
Jan-May
24,884
WM, Ramani
2021
Jan-May
36,041
WM, Ramani
Uttar Pradesh
2015
Entire year
687,416
Vital Statistics
Uttar Pradesh
2016
Entire year
608,740
Vital Statistics
Uttar Pradesh
2017
Entire year
571,170
Vital Statistics
Uttar Pradesh
2018
Entire year
906,653
Vital Statistics
Uttar Pradesh
2019
Entire year
944,596
Vital Statistics
Uttar Pradesh
2019
Entire year
773,402
Bhawan
Uttar Pradesh
2020
Entire year
793,505
Bhawan
Uttar Pradesh
2019
Jan 1-Apr 30
259,316
Bhawan
19
Uttar Pradesh
2020
Jan 1-Apr 30
188,747
Bhawan
Uttar Pradesh
2021
Jan 1-Apr 30
333,878
Bhawan
West Bengal:
Kolkata
2015
Weeks 1-52
62,710
WM
2016
Weeks 1-52
65,060
WM
2017
Weeks 1-52
69,910
WM
2018
Weeks 1-52
68,998
WM
2019
Weeks 1-52
69,844
WM
2020
Weeks 1-52
74,841
WM
West Bengal:
Kolkata
2015
Weeks 1-20
25,128
WM
2016
Weeks 1-20
24,506
WM
2017
Weeks 1-20
26,980
WM
2018
Weeks 1-20
25,985
WM
2019
Weeks 1-20
29,222
WM
2020
Weeks 1-20
27,674
WM
2021
Weeks 1-20
33,132
WM
WM = World Mortality dataset (Karlinsky 2021).
The urban areas in Madhya Pradesh from which funeral counts were tabulated for April
2021 were from the following 25 districts: Barwani, Bhind, Bhopal, Burhanpur,
Chhatarpur, Chhindwara, Dewas, Dhar, Gwalior, Indore, Jabalpur, Jhabua, Khandwa,
Mandsaur, Morena, Neemuch, Ratlam, Sagar, Satna, Seoni, Shahdol, Shivpuri,
Singroli, Tikamgarh, Vidisha (Datta 2021).
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