Volume 20 No 8 (2022)
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COVID-19 Global Prediction: A Mathematical Approach based on Data Trend Lines and Probability
H. R. Bhapkar , Parikshit N. Mahalle , Nilesh P. Sable , Gitanjali R. Shinde
Abstract
To better understand data and its possible consequences, mathematical models are the must. For
COVID-19 outbreak, it helps predict and therefore, policies are guidelines can be designed accordingly.
In this study, we define the practical prediction model for COVID 19 by considering the different
essentials such as the total number of cases, recovery cases and death cases. The special grading for
countries involves the government policies as well as the involvement of the society intended for
controlling COVID 19. We investigate trend lines for the data with the help of correlation coefficients
and coefficient of determination. The linear and the second-degree equations help to make predictions
of active patients of COVID 19 in the future.
The study of existing data patterns is done and is used to predict the spread of COVID in the world. This
analysis assists us to decide the futuristic guidelines, requirements, and policies for governing the spread
of COVID 19
Keywords
COVID-19; Correlation coefficient; Grading; Prediction; Data Patterns;
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