COVID19_Analysis

Descriptive Analysis, Linear modeling and Forecasting of SARS COVID19

As the world currently faces a pandemic situation due to SARS COVID 2 virus, all countries were in a state of lockdown for a significant period. India also faced a historic lockdown in the last few months. COVID-19 has greatly affected our lives in numerous ways, ranging from lockdown to social distancing. The worldwide spread of coronavirus had sparked my curiosity and hence, performing a detailed analysis of COVID 19, which can be classified into four types :

India - State-wise Analysis
Duration of illness
Global vs India - Number of cases
- Confirmed
- Cured
- Active
- Deaths
Forecasting the number of cases - India
- Confirmed
- Cured
- Active
- Deaths

Task 1

Compiled_code_model.R
In this task, we will be focusing on the state-wise analysis of

Number and types of ICMR labs present
Number and type of Health Facilities available
Number of Confirmed, Cured, Active cases and Deaths occurred
Population - Rural vs Urban
The model used for the analysis of the factors responsible will be :

Linear regression

Task 2

Duration.R
Here, we deduce the infectious period of SARS-CoV-2 based on the Diagnosed date and Status change date.

Task 3

cases_Global_&_India.R_
Comparing and visualizing the spread of COVID19 pandemic at a global as well as national level.

Task 4

Forecast.R
In this task, we will be focusing on forecasting the growth of COVID 19 patients in India using Time Series Analysis. Models used for the analysis will be :