Mathematical models to predict COVID-19 outbreak : An interim review
Priyanka Harjule, Vinita Tiwari, Anupam Kumar
Abstract
AbstractWorld Health Organization (WHO) announced novel-coronavirus (COVID-19) disease, a pandemic on March 12, 2020, a disease caused by SARS-CoV2 virus. The pandemic has now affected 213 countries and territories around the world having over 9.07 million confirmed cases as on Jun 22, 2020. A Timely response during pandemic is beneficial for risk mitigation options on a global scale. In this manuscript,a scoping review of recent studies involving mathematical and stochastic models, to tackle and analyse the epidemiological characteristics of the COVID-19 crisis at different geographical grounds is presented. The main purpose behind this review paper is to convey to the readers the different dimensions of already existing applications and present an initial description of how mathematical modelling can help predict the spread of COVID-19 more accurately and reliably. Finally, a conclusion is drawn regarding the current state-of-the art methods and their challenges.Subject Classification: Probability theory and stochastic processesStatisticsNumerical analysisComputer scienceKeywords: Mathematical modelsStatistical modelsBasic reproduction numberCOVID-19Epidemiology