Modelling Analysis of Covid-19 Infections in India and Prediction of Daily Cases in 2021

Authors

  • M N Anandaram Bangalore University
  • N G Puttaswamy Bangalore University

DOI:

https://doi.org/10.12723/mjs.54.5

Keywords:

Covid - 19 Data, Least square model fitting, prediction of fall times in 2021

Abstract

In this paper the data for dailyconfirmed new casesconcerning the rise and fall of the Covid-19 (aka, coronavirus) pandemic infection in India for the nine month period starting from the first March 2020 has been subjected to a non linear least square fitting analysis using Gaussian, Skewed-Gaussian, Moffat, andVoigt model functions.The fitting parameters determined by the Python software package LMFIT are then used to compare the predicted remission times of Covid-19pandemic during 2021. It is found that while the Gaussian, Skewed-Gaussian and Moffat models predictlowlevels byabout March/April 2021; Voigt and other models predict longertimes to reach samelow endemic levels.

Author Biographies

M N Anandaram, Bangalore University

Professor of Physics (Retired), Bangalore University, Bangalore, India.

N G Puttaswamy, Bangalore University

Professor of Physics (Retired), Bangalore University, Bangalore, India.

References

Additional Files

Published

2021-09-07