It is the continuation of the paper COVID-19 status in India by Sopher Index and Weighted Index analysis. In the previous part, we already discussed the COVID-19 scenario by the Indexes. In this part, we will discuss the recovery status of the same in the different Indian states.
The vulnerable map on the basis of data 7th May 2020:
On the basis of the latest data sample here the map represents the latest scenario of COVID-19 vulnerability. The states Maharashtra, Gujarat, Rajasthan, and Delhi are the most vulnerable states in India.
Comparative Study of Weighted Index value:
Here is the table, map, and chart that represent the result outcomes of three Weighted Index values (W) of sampled dates. Data is the abstract form but maps and charts are reality or concrete forms of a topic. So it is easy to understand the facts from the map and chart rather than in interpretation. Let’s come to understand the comparison.
Recovery rate analysis by Sopher Index:
In the following table, I calculate the Sopher Disparity index by using the percentage of the confirmed population and the percentage of the recovered population. I consider the log10 value of each attribute and tabulate the data as per the formula. I also consider the total confirmed population of Indian states to be equal to zero and precedes the analysis accordingly. Then as per the calculated D.I. value (Disparity Index Value), I prepare the map through the executions of data output in the QGIS platform.
Recovery map by Shopper Index:
In the following map as per the Sopher Disparity index value, the states Punjab and Tripura show a higher rate of recovery. Maharashtra, West Bengal & Gujarat are in 2nd successive order of recovery. Tamil Nadu, Andhra Pradesh, Orissa, Jharkhand, Bihar, Madhya Pradesh, Uttar Pradesh, Delhi, Haryana, and Jammu and Kashmir lie in 3rd of recovery. Other states are at a negligible rate of recovery.
I use the data to visualize the present scenario of COVID-19 status in India by Sopher and Weighted Index analysis. It is clear that all the questions in the introduction part are easy to understand from the above analysis. The scenario will change soon if the data structure changes. Some states and union territory do not reveal their actual statistics for their administrative issues. Some states are deliberately tempered their data before publication. In spite of this, the analysis exposed an important meaningful impression of the present spreading status of COVID-19.
To check who much you understood you can try to solve this problem. If you need any help of mine you can leave a comment below I will surely try to solve your problem.
Here is video in the topic Sopher and Weighted Index analysis
Questions on the Topic, Sopher and Weighted Index analysis :
Q1. What are the answers to the questions in the introduction part?
Q2. Calculate the upper limit of (X– ± 1.5 Ϭ) in the ‘W’ value of the 7th May 2020 data set and mentioned the name of the State/states beyond the boundary of it.
Q3. Name the State who belongs in zero vulnerable groups of state in spite of her deceased population found in 7th May 2020 data. Explain why?