Why is India struggling to fight against COVID 19?
This post (Writing a Data Science Blog Post) is part of Udacity Data Scientists-Nanodegree Program. This is my first attempt using this platform. Please forgive if there is any flaw in this article.
COVID 19 has spread across the world so fast that it was impossible to take measures against it. First reported in December 2019, in China, but it was confirmed as a Coronavirus in January 2020. Gradually it started spreading across the globe. In India the outbreak reached a bit late (in March 2020) as compared to the other countries, but it started to pick up pace within a short duration.
With limited testing, lesser healthcare professionals and not a well-funded healthcare system, India is facing a challenge to fight against COVID 19. The fight is still on after four lockdowns and the virus shows no signs of slowing down. With around 14,64,000 cases India ranks third in World for number of cases. With such a large population density and Second largest Population let’s see how India fares with other countries and how successful are the lockdowns.
To come across this scenario, we need to answer few questions. Here are those questions:
- Did India fail to take necessary measures?
- What is the effect of doubling rate in India?
- Is healthcare in India good enough to handle spread of Covid-19 on large scale?
- Does Population Density have anything to do with the spread?
With around 14,64,000 cases India ranks third in World for the number of cases. With such a large population density and Second largest Population let’s see how India Fares with other countries and how successful are the lockdowns.
The table below shows the current figures and ranking for India in the World and in Asia.
Impact of lockdown — Did India fail to take necessary measures?
The plot below shows the total cases, deaths and recoveries reported on a daily basis. The worrying point is that even after almost four nation-wide lockdowns the cases are increasing.
Government of India declared its first lockdown on 23 March 2020 to prevent further spread of COVID when the first reports of patients being affected were observed. While lockdown was extended in further three stages as on 15 April 2020, 4 May 2020 and 18 May 2020 respectively. After putting lockdown for almost for two months, it was then lifted in stages and steps to avoid spread of COVID including certain measures such as social distancing, closed public places, etc. From the above plot, in the initial stages of lockdown the curve is bit flattening i.e. the rate of spread of disease was slow. As soon as lockdown was lifted, that is during the unlock phases, the curve seems to be increasing exponentially, meaning the virus started spreading drastically after May 2020.
What is the effect of doubling rate in India?
The doubling time is time taken for a population to double in size. When the relative growth rate is constant, the quantity undergoes exponential growth and has a constant doubling time or period, which can be calculated directly from the growth rate.
Following table shows the doubling rates of COVID-19 across whole India and its states respectively.
The above table shows the doubling rate for each state and the number of confirmed cases with Maharashtra at top. The following plot shows statistics of zones being observed in each state differentiating as red, orange and green zone. Red zone shows maximum number of people being infected, orange zone being moderately affected while green zone being the least infected cases.
Is healthcare in India not good enough?
The following table shows the statistics of states in India including number of patients cured and confirmed, deaths, mortality rate, recovery rate, cases/million, beds/million and health facilities/100 sq. km. While looking through the statistics, the health facilities/100 sq. km is 11 and beds/million are 1072 which is not enough to provide people. Only Delhi seems to have better facilities than any other state in India which is certainly not sufficient to handle overall cases in India. Though the facilities don’t seem to be good enough, India managed to keep the mortality rate as low as possible excluding the few states.
Following plot shows the number of COVID-19 testing labs per State/Union Territory depicting Maharashtra having the highest numbers of testing labs (39).
Having able to set up the testing labs, Indian states managed to carry out more number of tests as possible. The highest number of tests done till date are almost 6.5 million in Uttar Pradesh, followed by Tamil Nadu and Maharashtra being second and third respectively.
Does Population Density have to do anything with the spread?
Here, I have studied the impact of population density (per km square) on the total confirmed cases, deaths and recoveries. I’ll be using a scatter plot with total cases, deaths or recoveries on the X-axis, population density on the Y-axis and population representing the size of the bubble.
Uttar Pradesh with highest population density has not reported as many cases as Maharashtra or Gujarat have. Although, there population density is not even less than half of that of Uttar Pradesh’s. So, there seems to be so concrete relation.
Studying the trend
In the below three plots, I have plotted the 7-day rolling mean of daily cases, deaths and recoveries reported against the day it’ s first instance was reported.
Conclusion
So, from the above plots, it’s pretty evident that out of all states only Kerala has been able to flatten the curve. While Maharashtra, Gujarat, Delhi and Madhya Pradesh are still fighting hard to curb the spread of infection. The positive is that the recoveries have started to pick up pace in all the states whiles death rate is slowing down.
The following plot shows the statistics for the worst affected state in India i.e. Maharashtra.
Having been able to set up the testing labs, Indian states have managed to carry out more number of tests possible at their level. India has 1072 beds/million available during pandemic which is very much less than the required number. Only Delhi has the best healthcare facilities in India which is not sufficient to handle the overall cases in India. Though Indian states were not able to provide good facilities, they somehow managed to keep the mortality rates as low as possible.
Indian government declared lockdown as soon as the first case was reported. the lockdown was extended in four phases and then it was unlocked in three different phases step by step specifying few terms to be followed by people. During this lockdown for almost three months, India managed to flatten the curve but as soon as it was unlocked the curve raised exponentially and the disease started spreading as per the doubling rate.
Moreover there seems to be so concrete relation between population density and spread of Covid-19 as Maharashtra, Gujrat reported as the most affected states while Uttar Pradesh is the state with maximum population density.
