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 :

1. India - State-wise Analysis
2. Duration of illness
3. Global vs India - Number of cases
   • Confirmed
   • Cured
   • Active
   • Deaths
4. 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

1. Number and types of ICMR labs present
2. Number and type of Health Facilities available
3. Number of Confirmed, Cured, Active cases and Deaths occurred
4. 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 :

• Simple Moving Average
• Weighted Moving Average
• Exponential Moving Average
• Auto ARIMA