COVID-19 Analysis in India - OptiSol Datalabs

COVID-19 Analysis in India

Detailed Data visualization of the impact of COVID-19 in India using Plotly


Coronavirus is spreading exponentially and has caused so much damage to mankind across the globe. Several countries like the USA, Russia, UK, France, Brazil have been heavily impacted. Currently, India is also affected hugely by this virus. The spread of the disease is increasing on a day-to-day basis almost in an exponential manner and the condition is worsening.

In this article, we will look at the regions in India which are most hampered by the outbreak.

Before focussing on India, let’s try to get an overview of how the virus has impacted globally.

Top 5 affected countries globally

On inspecting the above Data visualization, we see that the US has the most number of infected cases as of now. The US is almost touching 32 Million cases but there is a gradual decrease in the daily infected cases from January 8, 2020 (Jan 8 is reported as the highest infection rate by a day with 300,000 confirmed cases) to March 12, 2021, with 35,000 plus confirmed cases.

But the situation in India is so grave because the daily cases are increasing gradually and total cases have crossed over 23 million cases.

France and Russia are about to touch the 5.8 million mark whereas Brazil crossed over 15 million cases.


In India, there were only 500 plus cases of COVID-19 when the first lockdown was imposed in the country on March 25, 2020, and now if we look at numbers there are more than 23 million cases of coronavirus in the country.

Let us see the infection rate of India below,

Here, we can infer that India has reported

  • 24 million-plus infected cases of the coronavirus (COVID-19),
  • with more than 20 million-plus recoveries and
  • about 260 thousand plus fatalities

When we look at the rate of case classification, India has recorded 23 million-plus confirmed cases of which the recovered rate is 83.2% and 15.7% of active cases.

The Trend of Daily Cases

Looking at the graph above, we notice that India’s daily case numbers have begun rising at the end of February after falling steadily from mid-September 2020. Again has picked up sharply in March, and has reached record highs in April, outpacing the rate of growth seen in the first wave which hit India in 2020.

Top 10 Infected States in India

Maharashtra tops the list of most Coronavirus-affected states with 5.2 million-plus confirmed cases and followed by Kerala and Karnataka.

Case Fatality Rate (CFR)

The case-fatality rate (CFR) is the proportion of people who die out of those who test positive.

total_confirm = state_df["Confirmed"].sum()
total_death = state_df["Deceased"].sum()
CFR = round(((total_death/total_confirm)*100),2)

On performing analysis, it is found that for every 100 positive tests, approximately 1 person dies and the CFR is 1.09%. The big problem with this number is that, unlike most other diseases that have ended, new COVID-19 cases and deaths are being reported every day. A country’s age demographic and healthcare infrastructure have been shown to play a role in determining this number.

Case Positivity Rate

Total Positive cases / Total COVID-19 Tests taken

Case Positivity rate = 

The overall Case Positivity Rate of India is found as 7.66%. Now let’s look at the positivity rate of different states in India below.

The increases in confirmed cases aren’t occurring just because there is more testing. The high test positivity rates in states show that the virus is in fact spreading quicker and the testing rate must also be increased.

Goa has the highest Positivity Rate of 17.39% followed by Maharashtra (17.36%), Dadra and Nagar Haveli and Daman and Diu (13%), and Chandigarh (12%).

COVID-19 Test Rate

Total Test / Total Population

test_rate = round(((df["Tested"].sum()/df["Populations"].sum())*100),2)

Only 24.8% of the Indian population has been tested so far. To beat back corona, one of the first things that we need to do is to increase the testing rate of our Country.

Above is the Data visualization of the Test rates of different states in India. We see that Lakshadweep has the highest COVID-19 test rate which is more than 100% (which implies Lakshadweep has done repetitive tests for an individual) followed by Delhi (96%) and A & N Island (91%).

We found previously that there was a sudden spike in the cases during March and a record-high increase in the month of April. We’ll see whether there was any significant reason for the change in trend.

After some research, I found that India has had the State election in 5 states and the historic Kumbh Mela during the above-mentioned period of the pandemic. So let’s start analyzing them.

Impact of Political Rallies

India’s political parties had campaigned a series of State Elections in West Bengal, Assam, Kerala Tamil Nadu, and Puducherry. The campaigns had often involved numerous rallies with large crowds — with minimal social distancing and very little mask-wearing.

The dotted vertical line indicates the before and after the impact of the Election in COVID-19

In Kerala, Tamil Nadu, and West Bengal, there’s a clear upward trend in daily coronavirus cases starting in the second part of March and then a clear spike in April.

But some of the non-election states also experienced a huge spike after the end of April. So we can’t conclude that elections played a vital role in the sudden increase of COVID-19 cases in India.

Impact of Kumbh Mela

Kumbh Mela is a religious event that is celebrated four times over the course of 12 years. It is attended by millions of devotees around the world. This year, it was celebrated on April 01, 2021, amid the pandemic in Haridwar, Uttarakhand.

So, let us see the COVID cases in Uttarkhand and see whether there is an impact of Kumbh Mela on the COVID infection rate in Uttarakhand.

Kumbh Mela Districts (4): Haridwar and its neighbor districts (ie., Dehradun, Pauri Garhwal, Tehri Garhwal) Non-Kumbh Mela Districts (9): Almora, Bageshwar, Chamoli, Champawat, Nainital, Pithoragarh, Rudraprayag, Udham Singh Nagar, Uttarkashi

The total active cases in Uttarakhand is around 59 Thousand (till March 12, 2021), in which 65.3% of the active cases are from Haridwar and its neighboring districts and the rest 34.7% are from other districts of Uttarakhand.

We can infer that the happening of the Kumbh Mela Event has played a vital role in the severe increase of COVID-19 Cases in Uttarakhand.

COVID-19 Vaccination

First Dose vs Second Dose

The above plot shows that Out of 140 million first dose vaccinated persons, only 38 million persons were vaccinated with the second dose.

Of the total vaccinations administered (178 million) up to March 12, 2021, 78.28 percent are recipients of the first dose while 21.72 percent have received the second dose.

CoviShield Vs Covaxin

CoviShield is the widely used vaccine variant in India. Nearly 160 Million are vaccinated by CoviShield and around 17 Million are vaccinated by Covaxin.

Vaccination Details (by Age Group)

From the above plot, we can infer that in India, people within 40–60 yrs age are highly vaccinated with a rate of 45.7% followed by 60+ years age category(40.3%) and the least group to be vaccinated is 18–30yrs(4.86%)

Vaccination Details (By Gender)

Males in India have vaccinated the most around 72 million so far, Females- around 65 million, and Transgenders are the least to be vaccinated of around 19000.

Vaccination Rate (By State-wise)

Among the states, Ladakh has administered the most vaccination with the rate of 29.49%, followed by Lakshadweep (29.17%) and Sikkim (24%).


  • This analysis gives a clear picture of how COVID-19 has impacted India, the number of fatalities, and the impact of recent large crowd gatherings that have played their part in the Second wave of COVID-19.
  • The charts can be used to infer key data insights which show that the current COVID -19 condition is worsening.
  • The only way we can as a whole prevent this impending crisis is by flattening the curve. To do this, we should follow the Guidelines and Protocols issued by the Government of India.
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