Publication

Abstract : Since 2019, the globe has been observing the rise of the novel coronavirus pandemic brought on by the ``severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)" virus. Humanity has been badly impacted by the outbreak of Covid-19, which also has wider consequences for health, the economy, and education. The nations have made several steps to pinpoint the disease's origin and examine its transmission pattern for predicting future trends. According to the WHO, India experienced a spike in Covid-19 confirmed cases from 2565 to 26246 between June 2020 and May 2022. This chapter intends to provide a fractal-based approach to analyze Covid- 19 data set in India from June 2020 to May 2022. The entire study period is divided into four half-years, and the analysis is to be carried out separately for each half-year. Covid-19 data analysis begins with the reconstruction of the curves representing the number of daily confirmed cases and the curves for the number of daily tests through the fractal interpolation technique. A linear iterated function system is formulated using the considered data set with a proper vertical scaling factor. Then, the attractor of this iterated function system is the required fractal interpolation curve. Fractal interpolation offers the benefit of minimizing data loss when creating curves. In addition to the reconstruction of the curves, this chapter proposes a more straightforward method to find the cumulative number of Covid-19 cases during each half-year by calculating the area under the curve using fractal numerical integration. It is easier to compute the number of cumulative cases using fractal numerical integration instead of adding up each day's number of cases separately. By determining the ratio of cumulative cases to the entire population, this chapter concludes by analyzing the virus' growth rate in the nation.