SURVEY ON FORECASTING THE VULNERABILITY OF COVID 19 IN SALEM DISTRICT

Author (s) : A.KOWSALYA and G.SARANYA

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Abstract :
Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this experiment, the number of patients who would contract the virus in the near future is predicted using a machine learning model called linear regression (LR). A region's infection transmission and disease recovery rate can be forecasted using the SIRD model simulation. By tracking the spread of the illness over time, the disease's susceptibility is evaluated. Additionally, a variety of infographic  models and graphs are made to make it simple to interpret the data and gain better understanding of the illness. However, thanks to these prediction models, we can quickly respond to pandemics and put an end to the illness.

Keywords : Covid 19, data science, machine learning, prediction, analysis, pandemic, recovery and infection.

Conference Date : 30/08/2019

Pages : 129

Paper ID : 19127