OVERVIEW OF COVID-19 AN INDIA PERSPECTIVE - Wave 14 17th Aug 2020 - Times Now
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OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
Wave 14
17th Aug 2020
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
EXECUTIVE SUMMARY
This document presents a study performed by Protiviti and Times Network as of 17th August 2020, to
estimate the extent to which COVID19 is expected to influence India as a country using aggregated
statistical measures computed based on 3 types of forecasting models:
% Based Models, Time Series model & SEIR Model.
We analyzed India as a whole, top 10 Indian states and 26 cities/hot-spots along with the entire country
for a period of close to 50 days to project the evolution of the COVID19 pandemic using the ‘Number of
daily new cases’ along with the total ‘active’ patients count.
The projected evolution of infected cases initially assumed an inherited effect of countrywide lockdown
applied from 24 March 2020 for 45 days or so.
The projections provided in the study are primarily based on time series modeling and therefore, we
understand that this complex and dynamic nature of the influence of COVID19 shall evolve on a daily basis
and is a continuous work in progress.
The models that are used suggest that the peak ranges from around 780,354 cases on an optimistic
side to around 938,306 on a higher side and expected to happen around early September.
Additionally, based on SEIR model, primarily designed to analyze the time based influence of such
pandemics both in smaller and larger cohorts, on an average run down suggests that the closing date
at an India level may fall somewhere towards the end week of November, 2020.
Some states have already started to peak out and some might come out of it during later part of
August to early September while some highly infected ones may take a month longer.
The lockdown plays a key role on the exit. In case of a longer period of lockdown, we can expect the
curve to be flattened but can expect a later exit date (i.e. a flat curve will stretch the pandemic). For
the lockdown to eradicate the pandemic, a robust lockdown and containment is required for a
substantial period of time.
Also, when a lockdown is lifted we expect the cases to rise if proper measures are not taken. The
mode in which lockdown is lifted will impact the outcome / # of cases.
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
SETTING THE CONTEXT
This document presents a study performed by Protiviti and Times Network as of 17th August
2020, to estimate the extent to which COVID19 is expected to influence India as a country using
aggregated statistical measures computed based on 3 types of forecasting models: % Based
Models, Time Series model & SEIR Model.
We analyzed top 10 Indian states and 26 cities/districs along with the entire country for a
period of close to 50 days to project the evolution of the COVID19 pandemic using the ‘Number
of daily new cases’ along with the total ‘active’ patients count.
The projected evolution of infected cases assumes an inherited effect of countrywide lockdown
applied from 24 March 2020 and the numbers proposed for the future also consider that this
period of lockdown continues for the next 45 days or so.
The projections provided in the study are primarily based on time series modeling and
therefore, we understand that this complex and dynamic nature of the influence of COVID19
shall evolve on a daily basis and is a continuous work in progress.
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
SETTING THE CONTEXT
Point to be noted:
The outputs of the modelling are not to be consumed directly for publication by any other
source.
The models presented in the study are based on the fundamental assumptions of time series
modeling well stated in the published academic sources.
The models which are developed using existing standard epidemiological modeling techniques
like SIR and SEIR are with the limitations of limited data, dynamic environmental factors and
external government based interventions.
The proposed SEIR model does not take into account the asymptomatic transmission explicitly,
however, it cannot also be fully discarded in the actual scenario.
Additionally, we have not considered stratified cohorts of population for studying this
transmission based COVID19 pandemic. A later version of the model might include age based
or other stratifying features that may account for differing demographics in India.
We have taken utmost care while collecting, preparing and processing the required infected
count data, however, the overall quality of data will have a material impact on the quality and
reliability of outputs.
Although the modeling period included both the lockdown and pre-lockdown phases in India,
but there is no specific designed parameter available in the proposed model that may help
analyze Government intervention in retarding the growth of this pandemic in India. Therefore,
an effect of an external policy level change might only reflect in our modelling output after a
lag of 3-4 days.
This work is completely a scenario based modeling framework wherein Protiviti along with the
Times Network group have analyzed this pandemic situation and have come up with a robust
statistical way to model it under a number of key assumptions. Therefore, the outputs of the
study are not an indication of the future but rather probable situations for consideration and
further deliberation.
This study does not take into account COVID-19 testing data in India and all the states, timing
of testing, external factors like immunity, BCG vaccination, and international travel history data
for a specific time period, specific cluster density, demographics etc.
This predictive modeling considers the learning of progression rate from other countries like
US, Italy, China, Malaysia, South Korea and incorporate in the models to create scenarios with
certain assumptions.
The study depends on a number of assumptions which may vary at a granular level.
Lastly, the modeling here is regulated assuming that the cases listed on reliable government
sourced websites are an average over time. We completely understand the public health care
system in India and can reasonably assume that the number of cases considered in our study
are on a lower side as many cases are not getting reported and the testing rate of India is
towards the lower side when compared globally.
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
INDIA’s FIGHT AGAINST COVID-19
India's response to COVID-19 has been pre-emptive, pro-active and graded with high-level
political commitment and a ‘whole government’ approach to respond to the COVID-19 pandemic.
Ministry of Health and Family Welfare is working to strengthen surveillance, build capacity of
health system and optimize ‘window of opportunity’ created by mandatory physical distancing in
India.
2,766,511 1.2 to 1.6 16 Weeks 30,041,400
Total Cases on 17th R0 –reproduction rate Of mandatory social Tests completed,
Aug 2020, 3 month of the virus, with Distancing, has helped this has increased
ago, total active cases most estimates contain virus within by 8.4 times in 1
were at 26 averaging at 1.36 404 districts month
Major Affected States
The most affected states / union territories
are Maharashtra, Tamil Nadu and Delhi. Out
of 736 districts, 411 districts have reported
Delhi confirmed numbers. The silver lining is that
10.46%
the poorest of districts have the least number
of cases. Additionally, many of the remaining
325 districts, are also the least capable of
handling an exponential increase in cases.
Fewer cases also mean, quarantine and track
Maharashtra & trace procedures are easier to apply, and
29%
form an effective first line of defense.
3% - 6% of total
for these states & districts to continue social
>6% - 15% of total distancing until appropriate improvements in
Tamil Nadu medical care, and access to medical facility
6.7% >15% - 20% of total
has improved in these districts.
OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
GLOBAL SCENARIO OF COVID-19 EPIDEMIC
The World Health Organization (WHO) declared the 2019–20 coronavirus outbreak a Public Health
Emergency of International Concern (PHEIC) on 30 January 2020, and since then, 21,845,024*
new cases have been registered, of which approx. 93% recovered, and 7% were fatal. A total of
215 countries have since reported an outbreak in a period of 4 months.
* - as of 16th August 2020, 11.59 PM GMT. This is an ever evolving situation, and is also growing exponentially.
% Change of Total Cases over the last 1 month
90%
Italy
80% USA
Spain
70%
Iran
60% SK
India
50%
40% INDIA
30% 11.3%
20%
10%
0%
MUCH OF THE BATTLE IS AHEAD OF US!
The total number of cases confirmed is a function of total tests performed, and seems exaggerated for
countries with smaller infected case count. While this is the case for India, the worrying trend line for
rate of change of cases in India is indicating an upward linear trend , currently at around 21%. Just
like countries battling Covid-19 at least a month prior to India, early indicators depict a movement of
this rate of change up to 30% - 40% range before it will start to drop by around 3rd or 4th week of
April.
Nevertheless, this indicates one thing, as countries improve the rate of testing, and turnaround time
for results from each test, the rate of change increases proportionally, indicating a still persistent
exponential growth rate across the world, and an greater exponent driving the Indian scenario.
Recovered / Total Death / Total cases
Total Cases Total Deaths
cases with outcome with outcome
WORLD
21,845,024 772,900 93.1% 9.5%
INDIA
2,766,511 53,026 50% 3%OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
COUNTRIES NEARING THEIR PEAK
Understanding if a country is nearing its peak of cases is difficult to estimate, especially while the
pandemic is unraveling its full potential. But, fundamentally, the total number of log-log chart of
no. of tests per million vs. no. of cases per million, provides a clear picture of those countries
which are starting to turn the curve.
Spain
US
Number of Cases per Million
(log scale)
UK Italy
1,000
100
South
Korea
10
INDIA
1
1 10 100 1,000 10,000 100,000 1,000,000
Number of Individuals tested per Million
(log scale)
South Korea is a success story, but from the graph it is clear that Italy has turned the curve, and
will start recording fewer cases going forward. It is also worth noting that when the number of
tests reach around 10,000 individuals per million, South Korea was able to successfully curb the
spread. This was due to quick action, and effective social distancing, and quarantine policies.
India could take this road if the current containment policies are effective and peak by the time we
reach 10,000 individuals tested per million. Without proper containment policy, or delayed
implementation of the same, will result in a steeper rise, and subsequently steep fall in cases.
This scenario analysis will help us assess the
model that we can use to estimate the current
state of the pandemic, especially in relation to
THIN CURVE India.
The goal of the country is to hit a flat curve
that will sufficiently spread the cases
encountered to meet the medical supply
FLAT CURVE constraints. Our best case scenario therefore
is to aim for the flat curve.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
WHERE ARE WE & WHAT TO EXPECT
What will be the impact of the novel coronavirus (COVID-19) in India? Answering this question
requires an accurate forecast of the spread of confirmed cases as well as analysis of the number
of deaths and recoveries. Forecasting, however, requires ample historical data, often times, the
correct data useful in forecasting is not available. At the same time, no prediction is certain as the
future rarely repeats itself in the same way as the past. The below graph is an aggregation of 3
types of forecasting model: % Based Models, Time Series model & SEIR Model.
Total Number of Active Forecasted Cases
1,000,000
10^6
100,000
10^5
10,000
10^4
10^3
1,000
10^2
100
20/03 03/04 17/04 01/05 15/05 29/05 12/06 26/06 10/07 24/07 07/08 21/08 04/09 18/09 02/10 16/10 30/10
Best Case Worst Case Most Likely
For each of these model categories, multiple models were built to simulate the situation in progress in
India. These Models are
% Based Model Time Series Model SEIR Model
The model assumes that the The model assumes that past A mathematical prediction
Indian COVID-19 situation events and observations model that divides the
closely approximates one of predict the future situation population into Susceptible
the following countries: accurately. population (S), Exposed
1) Approximation of Italy 1) Hybrid (China & South Population (E), Infected (I) and
(Italy) Korea) Recovered (R) population. It
2) Approximation of US (US) 2) Poly Regression (2nd predicts future values by
Degree) assuming or predicting values for
3) Poly Regression (3rd coefficients for the mathematical
Degree) equations.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
METHODOLOGY
Based on the nuances and the complexity associated with limited pandemic data, we adopted a methodology of
forecasting using aggregated measures computed using 3 types of forecasting models: % Based Models, Time Series
model & SEIR Model.
Percentage Based Model
Apply the growth progression rate of the infected cases for USA and Italy on India data and project the
cases using the same trends over time to get the forecasted figures and no mathematical/statistical
model has been applied
Considering the infected cases as a function of total population and use the percentage of Hubei to
project the trend in India based on early data points available for India
Hybrid Model
Segregate the data on two major segments – before lockdown and after lockdown and 2 distinct
models have been built for two segments considering the trends only and no other external factors
have been taken into account
Within lockdown there are 3 stages- Progression rate, Flattening rate and Decay Rate : 3 different time
series models has been fit separately based on the learning from China, Malaysia and South Korea
All the coefficients are based on Ordinary Least Square methodology and adjusted R-Square is the
primary metric considered for accuracy; R-Square is more than 90% for all the models
Polynomial Regression Models
To overcome the problem of Bias-Variance tradeoff while selecting an appropriate and effective
statistical model, we made use of Polynomial Regression models to model the COVID19 infected
Indians data.
Polynomial Regression model assumes that the relationship between the dependent (Daily Count of
Infected Patients) and independent variable (Time - Days) is curvilinear (specifically Polynomial)
The coefficients of the proposed models are estimated using Ordinary Least Square (OLS) method
while the model accuracy and performance is assessed using adjusted R-square values along with
observing the Mean Squared Error (MSE) values
Polynomial Regression of degree 2 and 3 provided for relatively a better fit along with an average
forecasting accuracy of over 94% & 98% respectively
Susceptible Exposed Infected Recovered (SEIR) Model
The basic Reproduction Number (R0) is the most common measure of estimating the strength of an
epidemic. In simple words, R0 is the secondary cases generated by one primary case in a susceptible
population.
In order to estimate the extent of the Covid19 pandemic in India, we made use of the SEIR model
proposed by Betten Court and Ribeiro1 & Gani et al.2,
Estimation of basic reproduction number (R0) is performed through initial intrinsic growth rate method
using standard deterministic SEIR model.
This standard deterministic SEIR epidemic model classifies each individual into susceptible S(t),
latent/exposed E(t), infective I(t) and recovered R(t) individual.
Our estimate of reproduction number for India is 1.55 with 95% CI [1.52 , 1.61 ], whereas for different
states the effective reproduction number varies in between 1.16 to 1.52
Model assumes that the infectious period, latent period, transmission probability and infection rate per
person per unit time is dynamic and varies based on individuals and their respective location
The pandemic spread curve presents a transmission rate/infection rate and its evolution over a period of
time
1. Bettencourt, L. M. A. and Ribeiro, R. M., Real time Bayesian estimation of the epidemic potential of emerging infectious diseases. PLoS One, 2008, 3(5), e2185.
2. S. R. Gani, Sk. Taslim Ali and A. S. Kadi, The transmission dynamics of pandemic influenza A/H1N1 2009–2010 in India, CURRENT SCIENCE, 101(8) 25 Oct. 2011OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
PROPENSITY TO MANAGE CASES
TOTAL BEDS India is undermanned, underprepared, and is facing the crisis, with an uphill battle
of improving the health infrastructure and increasing capacity to meet the demands
1,872,971 of COVID-19 patients. Worryingly, the total ICU beds with working Ventilators,
which is crucial for severely affected COVID-19 patients, is in the range of few
Total non ICU Beds
available across India thousands. Total susceptible cases requiring intensive care from a population
standpoint is approximately 322 Million Indian citizens.
164,886
ICU beds, or 6.4% of Total Number of Active Forecasted Cases
total hospital beds
10^6
40% - 45% 10^5
Average % of beds
currently occupied, and is
un-usable. 10^4
10^3
126
Will have ICU Beds for 10^2
every million susceptible
20/03 03/04 17/04 01/05 15/05 29/05 12/06 26/06 10/07 24/07 07/08 21/08 04/09 18/09
population, (i.e. all of the
1Million may need
intensive care) Best Case Worst Case Most Likely
At its probable worst, COVID-19 might reach a peak of 7.87 lakh patients. We expect
that in the best case scenario, India will reach around 7.80 lakh cases, around 7.87
lakh cases in a most likely scenario and 9.38 lakh cases in the worst case scenario. In
the most likely scenario we expect that the India will be 95% free around 1st week of
September.
The problem of community spread is greatly concerning, and the country is
scrambling to add new beds, increase capacity of intensive care units, to mitigate
the situation of 100,000 patients not having access to life saving facilities.
Additionally complicated is the scenario where the distribution of beds are not in
proportion to the affected. The cites are disproportionately affected, and therefore
will be the first to run out of beds, even though they are the ones with better
facilities. The % of cases that are fatal in rural regions may be higher due to this
reason.
The government is undertaking medical colleges and railway coaches into isolation
wards, stadiums into quarantine facilities, and readying part of hospitals under
defense, central police forces and railways for Covid-19 patients.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
STATEWISE ANALYSIS
This section represents how some of the states has been doing in the last one month. We can see from the
graphs below that some of the states have started showing of decline while some of the states show growth.
# of Active Cases by Staes over time and Average
100000 Average The first graphs talks about the
Growth Rate ( 7 Days Average)
growth rate growth of the number of active
90000 (Last 7 Days) cases and 7 day moving average.
MH : 2%
80000 TN : 1% The second graph talks about the
UP : 4% Doubling Rate or the number of
70000
KA : 6% days it took to double.
60000 KL : 5%
RJ : 5% If we look at these information we
50000 TG :-1% can clearly see that there are 3
GJ : 2% buckets of states
40000 AP : 9%
WB : 3% 1. Where the growth has gone
30000 DL : -4% done considerably
MP : 3%
20000 HR : 1% 2. Where the growth has
OD : 7% stabilized and
10000
3. Where there are still very high
0 rate of growth.
15/05
11/08
20/03
24/03
28/03
01/04
05/04
09/04
13/04
17/04
21/04
25/04
29/04
03/05
07/05
11/05
19/05
23/05
27/05
31/05
04/06
08/06
12/06
16/06
20/06
24/06
28/06
02/07
06/07
10/07
14/07
18/07
22/07
26/07
30/07
03/08
07/08
15/08
We can categorize Tamil Nadu
MH TN UP KA KL RJ TG (TN), Telangana (TL), Delhi (DL)
AP GJ WB DL MP HR OD and Haryana (HR) in the first
bucket.
Doubling Time for Each State (500+) Maharashtra (MH), Kerala (KL),
Uttar Pradesh (UP), Karnataka
40 (KA), Madhya Pradesh (MP),
35 Rajasthan (RJ), West Bengal (WB)
No of Days to Double (500+)
and Gujarat (GJ) falls under the
30
second bucket with a 7 day moving
25 average ranging between 2%- 6%
20 and a Doubling Rate of 8-15 Days.
15 Finally, there are the high growth
10 states Andhra Pradesh (AP) and
Odisha (OD) where the growth
5 rate is in 7% - 10% and the
0 Doubling rate hovering around 6/7
1K+ 2K+ 4K+ 8K+ 16K+ 32K+ 64K+ 128k+ 256K+ 512K+ days.
No of Cases These states are further analyzed
in details in the following sections
MH TN DL TG KL
UP RJ AP MP KA
GJ JK HR WB OR
11OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
STATEWISE PROJECTIONS
The above model is broken down into below numbers for each of the top 10 affected states. The values
identify the peaks in worst case scenarios
Maharashtra Tamil Nadu
10^5
10^4
10^4
10^3
10^2
2,46,936 57,968
10^1 10^1
Earliest End Date: Mid November Earliest End Date: Late October
Worst Case : Mid December Worst Case : Early November
Uttar Pradesh Karnataka
10^4 10^6
10^3
10^5
10^2
73,243 97,163
10^1 10^1
Earliest End Date: Late October
Earliest End Date: Early November Worst Case : Mid November
Worst Case : Early November
Kerala Rajasthan
10^4 10^4
10^3 10^3
10^2 10^2
26,386 14,762
10^1 10^1
Earliest End Date: Mid October Earliest End Date: End October
Worst Case : Early November Worst Case : Mid DecemberOVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
STATEWISE PROJECTIONS
The above model is broken down into below numbers for each of the top 10 affected states. The values
identify the peaks in worst case scenarios
Telangana Andhra Pradesh
10^4 10^5
10^4
10^3
10^3
10^2 10^2
29,966 99,827
10^1 10^1
Earliest End Date: End October Earliest End Date: End October
Worst Case : Mid December Worst Case : Mid December
Gujarat West Bengal
10^5 10^5
10^4 10^4
10^3 10^3
10^2 10^2
15,331 33,820
10^1 10^1
Earliest End Date: Mid October Earliest End Date: Mid october
Worst Case : Early November Worst Case : Early NovemberOVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
MAHARASHTRA’S FIGHT AGAINST COVID-19
As of 17th August, total 145,802 active COVID-19 cases and
20,686 deaths have been reported in Maharashtra, the
financial capital of India, Mumbai, being the worst affected.
COVID-19 cases reported from Asia’s largest slum, Dharavi has
aggravated the situation Maharashtra government officials
and health care workers are working assiduously to contain the
spread.
Confirmed
Cases
0 - 10000
10000 - 20000
20000 - 30000
30000 - 40000
40000 - 50000
60,4358 20,686 4,37,870
50000+ Total Cases Total Deaths Total Recovered
Projections
32,08,735
# of tests done
Oct 12
End of Infection
30.66 Days
Doubling Rate
0.05
Death to Recovery Ratio
1.30
SEIR Model Reproduction
Rate (R0)
14OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
ANDHRA PRADESH’S FIGHT AGAINST COVID-19
As of 17th July, the total active cases of COVID-19 in
Andhra Pradesh is 75,478, of which the maximum cases
are in Kurnool, Guntur and Krishna districts. %age of
deaths is at 2.8% in comparison to the total number of
cases.
Confirmed Cases
0 - 1000
1000 - 2000
2000 - 3000
3000 - 4000
4000 - 5000
2,96,609 2,820 2,18,311
5000+
Total Cases Total Deaths Total Recovered
Projections
29,05,521
# of tests done
Oct 15
End of Infection
17.26 Days
Doubling Rate
0.o1
Death to Recovery Ratio
1.29
SEIR Model Reproduction
Rate (R0)
15OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
GUJARAT’S FIGHT AGAINST COVID-19
As of 17th August, the total active cases of COVID-19 in
Gujrat is 13,184, of which the maximum cases are in
Ahmedabad, Surat, Vadodara, Rajkot districts. % of
deaths is at 4.6% in comparison to the total number of
cases.
Confirmed Cases
0 - 3000
3000 - 6000
6000 - 9000
9000 - 12000
12000 - 15000 79,816 2,821 63,811
15000+ Total Cases Total Deaths Total Recovered
Projections
13,58,364
# of tests done
Sep 30
End of Infection
39.39 Days
Doubling Rate
0.04
Death to Recovery Ratio
1.19
SEIR Model Reproduction
Rate (R0)
16OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
KARNATAKA’S FIGHT AGAINST COVID-19
As of 17th August, the total active cases of COVID-19 in
Karnataka is 72,125, of which the maximum cases are in
Bengaluru, Mysuru and Belagavi districts. % of deaths is
at 3.8% in comparison to the total number of cases.
Confirmed Cases
0 - 1000
1000 - 2000
2000 - 3000
3000 - 4000
4000 - 5000
5000+
2,33,283 4,208 1,56,950
Total Cases Total Deaths Total Recovered
Projections
20,75,086
# of tests done
Oct 20
End of Infection
19.48 Days
Doubling Rate
0.03
Death to Recovery Ratio
1.52
SEIR Model Reproduction
Rate (R0)
17OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
KERALA’S FIGHT AGAINST COVID-19
As of 17th August, the total active cases of COVID-19
in Kerala is 14,575, of which the maximum cases are
in Kasaragod, Kannur Kozhikode districts. %age of
deaths is at 0.6% in comparison to the total number
of cases.
Confirmed Cases
0 -1000
1000 - 2000
2000+
46,140 176 31,389
Total Cases Total Deaths Total Recovered
Projections
12,05,759
# of tests done
Sep 30
End of Infection
18.71 Days
Doubling Rate
0.01
Death to Recovery Ratio
1.26
SEIR Model Reproduction
Rate (R0)
18OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
RAJASTHAN’S FIGHT AGAINST COVID-19
Rajasthan recorded its first COVID-19 case on 3rd March 2020
and by the mid of March, Bhilwara, a district in Rajasthan,
seemed on the cusp of a large-scale outbreak. However, since
March 30, Bhilwara has witnessed a huge turnaround and there
has been only a few reported cases. A 'ruthless containment'
strategy, timely action, comprehensive screening and strict
enforcement of curfew and lockdown restrictions has helped
Confirmed
Cases Bhilwara immensely.
0 - 1500
1500 - 3000
3000 - 4500
4500 - 6000
6000 - 7500 62,630 898 48,960
7500+
Total Cases Total Deaths Total Recovered
Projections
19,30,842
# of tests done
Oct 20
End of Infection
28.06 Days
Doubling Rate
0.02
Death to Recovery Ratio
1.19
SEIR Model Reproduction
Rate (R0)
19OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
TAMIL NADU’S FIGHT AGAINST COVID-19
Tamil Nadu has the second highest number of COVID-19
patients in India with 48,151 active cases on 17th Aug. It has
witnessed a massive rise in positive cases since the beginning of
April and has identified the majority of cases to a single source
i.e. a religious congregation that took place in Delhi in March. In
light of recent events, the state has allocated ₹9,000 crore to
fight against the coronavirus pandemic.
Confirmed Cases
0 - 8000
8000 - 16000
16000 - 24000
24000 - 32000
32000 - 40000
3,43,945 6,007 289,787
40000+
Total Cases Total Deaths Total Recovered
Projections
37,78,778
# of tests done
Oct 10
End of Infection
31.90 Days
Doubling Rate
0.02
Death to Recovery Ratio
1.41
SEIR Model Reproduction
Rate (R0)
20OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
TELANGANA’S FIGHT AGAINST COVID-19
The first confirmed COVID-19 case in the Indian state of
Telangana was on 2nd March 2020. Less than 100 cases were
reported in month of March, however there has been a sharp
increase in the number of cases since the start of April. The
rapid increase in Covid-19 cases in districts has forced the state
health department to declare nearly 100 villages and areas in
various districts as ‘hotspots’ and impose more restrictions on
Confirmed Cases
the movement of people.
0 - 200
200 - 400
400 - 600
600 - 800
800 - 1000
1000+
92,255 711 72,202
Total Cases Total Deaths Total Recovered
Projections
7,53,349
# of tests done
Oct 01
End of Infection
29.14 Days
Doubling Rate
0.01
Death to Recovery Ratio
1.29
SEIR Model Reproduction
Rate (R0)
21OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
WEST BENGAL’S FIGHT AGAINST COVID-19
Confirmed Cases
0 - 2000
As of 17th August, the total active cases of COVID-19 in
West Bengal is 24,361, of which the maximum cases are
2000 - 4000
in Kolkata, Howrah and North 24 Parganas districts.
4000 - 6000
%age of deaths is at 2.9% in comparison to the total
6000 - 8000 number of cases.
8000 - 10000
10000+
1,19,578 2,528 92,689
Total Cases Total Deaths Total Recovered
Projections
13,47,091
# of tests done
Oct 03
End of Infection
13.05 Days
Doubling Rate
0.03
Death to Recovery Ratio
1.22
SEIR Model Reproduction
Rate (R0)
22OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
UTTAR PRADESH’S FIGHT AGAINST COVID-19
The coronavirus pandemic was first confirmed in the Indian
state of Uttar Pradesh on 5th March 2020, in Ghaziabad. On 17
March, the Uttar Pradesh government extended the closure of
all educational institutions, cinemas, shopping malls, swimming
pool, gyms, multiplexes and tourists places in the state till June
30th.
Confirmed Cases
0 - 2000
2000 - 4000
4000 - 6000 1,58,216 2,585 1,09,607
6000+ Total Cases Total Deaths Total Recovered
Projections
38,72,640
# of tests done
Oct 05
End of Infection
20.09 Days
Doubling Rate
0.02
Death to Recovery Ratio
1.24
SEIR Model Reproduction
Rate (R0)
23OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
APPENDIX : INFORMATION SOURCES
PERCENTAGE OF DISTRIBUTION OF INFECTION FOR BELOW AND OVER 60 YEARS:
For India: We have taken an 80-20 consideration based on initial trends. The most recent number given out by the MHA was 83%
and 17% respectively, but these numbers may keep changing.
For South Korea: https://www.cdc.go.kr/board/board.es?mid=a30402000000&bid=0030
For Italy: https://www.statista.com/statistics/1105061/coronavirus-deaths-by-region-in-italy/
For United States: https://www.businessinsider.in/slideshows/miscellaneous/nearly-30-of-us-coronavirus-cases-have-been-
among-people-20-44-years-old-the-cdc-says-showing-that-young-people-are-getting-sick-too/29-of-confirmed-us-
coronavirus-cases-have-been-in-people-between-the-ages-of-20-and-44-/slideshow/74720295.cms
PERCENTAGE OF MILD, SEVERE AND CRITICAL CASES
WORLD FIGURES - https://www.worldometers.info/coronavirus/#countries (AS OF MARCH 29)
CHINA FIGURES - https://www.worldometers.info/coronavirus/country/china/ (AS OF MARCH 29)
(These are critical and non-critical cases)
For An Overall Estimate Of The Number Of Mild, Severe And Critical Cases Around The World, We Have Taken A Study Conducted
Involving More Than 44,000 Patients In China Who Tested Positive For Covid-19, With Respect To Their Different Levels Of
Severity.
80.9% Of The Cases (36160) Were Categorised As Mild, 13.8% (6168) Were Categorised As Severe And 4.7% (2087) Were
Categorised As Critical. 0.6% (257) Were Categorised As Missing. This Roughly Meets The Global Trend Of Critical And Non-
Critical Cases Of 95% And 5%, But We Have Gone With This Three-Way Break-Up Of Cases And Mapped It To The World And India
Figures.
AGE GROUP DIVISION FOR CASES
We have an average for India based on the cases currently – and that works out to an 80% below 60 and 20% above 60 estimate
for the total number of infections. We have three models for the age group division of cases: The World Model of 95% non-
critical cases and 5% critical cases. For below 60, we have applied the same numbers to extrapolate a figure
However, for above 60, we have factored in a small difference in margin: made it 90% non-critical cases and 10% critical cases –
keeping in mind the fact the possibility of criticality increasing for the older people.
We have applied the China Model of 72% non-critical cases and 28% critical cases – that's the current number among the
ACTIVE cases in China. This gives a possible worst case-scenario. For this, we have applied 72% and 28% for the India data, and
made it 70% non critical and 30% critical for the above 60 category.
We have a third model, which is the Mild, Severe and Critical Model based on a study of 42000 infections in China conducted in
February. We have applied 81% (mild), 14% (severe) and 5% (critical) for the below 60 category, and slightly different numbers
for the above 60 category which is 70% mild, 20% severe and 10% critical.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
APPENDIX : INFORMATION SOURCES
OTHER ASUUMPTIONS:
India data as per date of hospitalisation to recovery or continued hospitalisation: https://www.covid19india.org/
The Mild, Severe and Critical Model
http://weekly.chinacdc.cn/en/article/id/e53946e2-c6c4-41e9-9a9b-fea8db1a8f51
Factoring in China data of hospitalisation in ICU and hospital in WUHAN based on LANCET study:
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30566-3/fulltext
Factoring in China reports of hospitalisation inside and outside Wuhan (though no specific reference here to ICU data):
http://www.xinhuanet.com/english/2020-02/04/c_138755345.htm
Factoring in US studies of potential hospital and ICU days for Covid-19
http://www.healthdata.org/sites/default/files/files/research_articles/2020/covid_paper_MEDRXIV-2020-043752v1-Murray.pdf
Note that we have not applied the standard ICU and ward duration of stay because the averages for the US and China and our
numbers too from data available for CORONA is significantly higher.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
COVID-19
DISCLAIMER
The pandemic novel coronavirus 2019, is rapidly evolving, with
new findings and insights being discovered daily. This document
is a series of observations that represents Protiviti and Times
Network viewpoint, at a certain point in time. This document
does not constitute or claims to serve as an advisory for any
medical, safety or regulatory action.OVERVIEW OF COVID-19
AN INDIA PERSPECTIVE
17th AUGUST, 2020
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