Asymptomatic community spread of coronavirus disease 2019( COVID 19) outbreak prediction using logistic regression

ABSTRACT

Corona virus disease (COVID-19) pandemic has become a major threat to the entire world. Antidotes and proper medications are still not found and determined to get cure from such virus. The report from World Health Organization (WHO) remits the COVID-19 as severe acute respiratory syndrome (SARS). Such virus is transmitted into human body via a respiratory droplets. Even, major symptoms for coronavirus patience are - tiredness, severe fever and dry cough but in most of the cases such symtoms are not found. This variety of coronavirus symptoms are termed as asymptomatic symptoms. The identification for such disease is very important into human body so that this can be stopped as community spread and reduces the effect of this as global pandemic. This paper provides an extensive study and predicts the outbreak of this disease with the aid of classification techniques of under machine learning. So that, the number of cases related to COVID-19 can be identified and subsequent arrangements have been made from the respective governments and medical doctors for future. Initially, this prediction model is implemented for short-term interval and later, such model based on internet of thing and machine learning, can also be set for estimating into long-term intervals for global as well as Indian perspective. Thelogistic regression and decisiontree techniqueshave been used for such cases predictions for this epidemic. © 2020 Ubiquity Press. All rights reserved.