An exploration of fractal-based prognostic model and comparative analysis for second wave of COVID-19 diffusion

• Published in: Nonlinear dynamics 2021-10, Vol.106 (2), p.1375-1395
• Main Authors: Easwaramoorthy, D., Gowrisankar, A., Manimaran, A., Nandhini, S., Rondoni, Lamberto, Banerjee, Santo
• Format: Article
• Language: English
• Subjects: Automotive Engineering; Autoregressive moving-average models; Classical Mechanics; Control; Coronaviruses; COVID-19; Datasets; Death; Disease transmission; Dynamical Systems; Engineering; Fractal analysis; Fractal geometry; Fractal models; Fractals; Interpolation; Mechanical Engineering; Original Paper; Pandemics; Statistical analysis; Variance analysis; Vibration; Viral diseases; Viruses
• ISSN: 0924-090X; 1573-269X
• DOI: 10.1007/s11071-021-06865-7

The coronavirus disease 2019 (COVID-19) pandemic has fatalized 216 countries across the world and has claimed the lives of millions of people globally. Researches are being carried out worldwide by scientists to understand the nature of this catastrophic virus and find a potential vaccine for it. The most possible efforts have been taken to present this paper as a form of contribution to the understanding of this lethal virus in the first and second wave. This paper presents a unique technique for the methodical comparison of disastrous virus dissemination in two waves amid five most infested countries and the death rate of the virus in order to attain a clear view on the behaviour of the spread of the disease. For this study, the data set of the number of deaths per day and the number of infected cases per day of the most affected countries, the USA, Brazil, Russia, India, and the UK, have been considered in the first and second waves. The correlation fractal dimension has been estimated for the prescribed data sets of COVID-19, and the rate of death has been compared based on the correlation fractal dimension estimate curve. The statistical tool, analysis of variance, has also been used to support the performance of the proposed method. Further, the prediction of the daily death rate has been demonstrated through the autoregressive moving average model. In addition, this study also emphasis a feasible reconstruction of the death rate based on the fractal interpolation function. Subsequently, the normal probability plot is portrayed for the original data and the predicted data, derived through the fractal interpolation function to estimate the accuracy of the prediction. Finally, this paper neatly summarized with the comparison and prediction of epidemic curve of the first and second waves of COVID-19 pandemic to visualize the transmission rate in the both times.