ABSTRACT
Coronavirus is the gene emerging from Coronaviridae species encompassing viruses together with a huge plus-strand RNA genome. Genomic RNA has size27–32kbwrapped&polyadenylated. In every cluster, viruses are considered via host ranges and genome sequences. Coronaviruses were found in mice, chickens, turkeys, swine,, cats, rabbits, horses, cattle, and humans, causing multiple diseases comprising gastroenteritis, respiratory tract syndromes, etc. The human-affected CoVs known to occur are human coronavirus-229E (HCoV-229E), OC43 (HCoV-OC43), and severe acute respiratory syndrome (SARS)-associated coronavirus (SARS-CoV). This virus gene got first isolated from the 7-month-old infant experiencing bronchiolitis and conjunctivitis. Thus, comprehensive genomic sequences decipher that the so-called genomic virus cannot be a recombinant, rather a novel cluster one coronavirus. In vitro host cell ranging via HCoV-NL63 is notable as it imitates on the existent tertiary monkey kidney (LLC-MK2) cell lining. Thus, genomic virus consists of distinctive structures, together with a unique N-terminal section within that spike protein. This chapter studies the complexity analysis, including time series and phase dynamics for the development of the virus in China. It aims to develop a mathematical model design towards simulating spread and awareness towards this genomic virus. Analysis aids in the understanding of outbreak of this virus towards the other parts of the continent and the world. Accuracy in addition to validity for the assessment would prove to be superior if models fit less of the data on basis of the features: population mobility with natural history, epidemiological characteristics, and transmission contrivances for virus gene. Mathematical model for the spread of coronavirus is developed. With the help of time-series analysis and phase space, the spread of disease is studied. Also, the case study for China country is studied for the spread of the disease. It is concluded that for China the spread follows Gaussian fitting with peak on February 13, 2020. Also, it is observed that on March 10, 2020, the death rate reduced to 4.89% and the survival rate goes to 95.11%. Now, almost it follows the log-normal behavior with long tail.
