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Home > Archives > Volume 20, No 11 (2022) > Article

DOI: 10.14704/NQ.2022.20.11.NQ66026

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


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.


COVID-19; Correlation coefficient; Grading; Prediction; Data Patterns;

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