Contact tracing Archives - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

Complete study of COVID-19 in India (Part II) – Laboratory and Testing

Posted on May 13, 2020May 23, 2020 by Dexlab

The first case of the 2019-2020 Coronavirus pandemic in India was reported on January 30, 2020, originating in China. Experts suggest the number of infections could be much higher as India’s testing rates are among the lowest in the world. The infection rate of COVID-19 in India is 1.7, significantly lower than in the worst affected countries.

The World Health Organisation chief executive director of health emergencies program Michael Ryan said that India has “tremendous capacity” to deal with the coronavirus outbreak, and as the second most populous country, will have enormous impact on the world’s ability to deal with it.

DexLab Analytics, in the first part of this blog series, studied the statewise breakup of COVID-19 cases in India through a Jupyter Notebook. Libraries were called, maps were drawnand data was taken from Kaggle.

The data and code sheet can be found below.

In this part of the blog series we will study how states are performing with regard to laboratories and testing. First we make three data sets – that of confirmed cases, recovered cases and cases of deaths.

We first plot this data on a graph and study it carefully. Then we make a pivot table and study the data. We then also study which state is performing how many tests on people. Kerala is found to have done the maximum number of tests (Fig.1.).

Fig. 1.

The purpose of this video is to teach you how to use visual graphs in Python. Now we aim to find why testing is underdone in states. Is there a possibility of a lesser number of labs in the first place? We get a graph (Fig. 2.) that shows us how many labs each state has for testing COVID-19 samples.

Fig. 2.

For the complete study watch the video attached herewith. This study was brought to you by DexLab Analytics. DexLab Analytics is a premiere Artificial Intelligence training institute in Gurgaon.

Complete Statewise Study on COVID-19 in India (Part I)

Posted on May 11, 2020July 7, 2020 by Dexlab

The first case of the 2019-2020 Coronavirus pandemic in India was reported on January 30, 2020, originating in China. Experts suggest the number of infections could be much higher as India’s testing rates are among the lowest in the world. The infection rate of COVID-19 in India is 1.7, significantly lower than in the worst affected countries.

The World Health Organisation chief executive director of health emergencies program Michael Ryan said that India has “tremendous capacity” to deal with the coronavirus outbreak, and as the second most populous country, will have enormous impact on the world’s ability to deal with it.

Other commentators worried about the economic devastation caused by the lockdown that has huge effects on informal workers, micro and small enterprises and farmers and self employed people who are left without a livelihood in the absence of transportation and access to markets.

The lockdown was justified by the government and other agencies for being pre-emptive to prevent India from entering a higher stage which could make handling very difficult and cause even more losses thereafter. According to a study by Shiv Nadar University, India could have witnesses a surge of 31,000 cases between March 24 and April 14 without lockdown.

So we call a Jupyter Notebook in Python to study India’s COVID-19 story.

The data and code sheet used in this study can be found below.

We will first import all libraries like pandas and numpy. All the data has been taken from kaggle. We then take the data and work a dataframe on it. And then we generate an India map to study the spread of SARS-CoV-2.

Fig. 1.

For more on this, please watch the complete video attached herewith. This study was brought to you by DexLab Analytics. DexLab Analytics is a premiere Artificial Intelligence training institute in Gurgaon.

A Deep Dive Into The US Healthcare System in New York

Posted on May 7, 2020May 23, 2020 by Dexlab

Unlike India’s healthcare system wherein both public and private entities deliver healthcare facilities to citizens, in the US, the healthcare sector is completely privatised.

The aim of this notebook is to study some of the numerical data we have for the US and especially data for New York. Most of us know about New York’s situation that is one of the worst in the world.

Therefore, analysing data may clarify a few things. We will be using three sets of data – urgent care facilities, US county healthcare rankings 2020 and Covid sources for counties.

For the data and codesheet click below.

Now pick key column names for your study with ‘.keys’ as the function name. We are interested in a few variables from health rankings so we take only the ones we think will be useful in a new data frame.

We will study each data set one by one so that we can get an understanding of the data before combining them. For this we call the plotly library that has very interactive graphs. We use the choropleth to generate a heat map over the country in question.

Fig. 1.

It is clear form the heat map that New York has a very high incidence of infections vis a vis other states. We then begin working with data on the number of ICU beds in each state. Since each state will have different populations, we cannot compare the absolute number of ICU beds. We need the ratio of ICU beds per a given number of inhabitants.

Fig. 2.

The generated heat map (Fig. 2.) shows the ICU density per state in the US. For more on this do watch the complete video tutorial attached herewith.

This tutorial was brought to you by DexLab Analytics. DexLab Analytics is a premiere data analyst training institute in Gurgaon.

Call us to know more

Gurgaon

Kolkata