Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)

Abstract

The outbreak of coronavirus COVID-19 is spreading at an unprecedented rate to the human populations and taking several thousands of life all over the world. Scientists are trying to map the pattern of the transmission of coronavirus (SARS-CoV-2). Many countries are in the phase of lockdown in the globe. In this paper we predict about the effect of coronavirus COVID-19 and give a sneak peak when it will reduce the transmission rate in the world via mathematical modelling. In this research work our study is based on extensions of the well-known susceptible-exposed-infected-recovered (SEIR) family of compartmental models and later we observe the new model changes into (SEIR) without changing its physical meanings. The stability analysis of the coronavirus depends on changing of its basic reproductive ratio. The progress rate of the virus in the critically infected cases and the recovery rate have major roles to control this epidemic. The impact of social distancing, lockdown of the country, self-isolation, home quarantine and the wariness of global public health system have significant influence on the parameters of the model system that can alter the effect of recovery rates, mortality rates and active contaminated cases with the progression of time in the real world. The prognostic ability of mathematical model is circumscribed as of the accuracy of the available data and its application to the problem.