Short-term predictions and prevention strategies for COVID-2019: A model based study

An outbreak of respiratory disease caused by a novel coronavirus is ongoing till December 2019. As of March 16 2020, It has caused an epidemic outbreak with more than 1,79,073 confirmed infections and 7,074 reported deaths worldwide. During the period of an epidemic when human-to-human transmission is established and reported cases of coronavirus disease (COVID) are rising worldwide, forecasting is of utmost importance for health care planning and control the virus with limited resource. In this study, we propose and analyze a compartmental epidemic model of COVID to predict and control the outbreak. The basic reproduction number and control reproduction number are calculated analytically. A detailed stability analysis of the model is performed to observe the dynamics of the system. We calibrated the proposed model to fit daily data from five provinces of China namely, Hubei, Guangdong, Henan, Zhejiang and Hunan. Our findings suggest that independent self-sustaining human-to-human spread ($R_0>1$, $R_c>1$) is already present in all the five provinces. Short-term predictions show that the decreasing trend of new COVID cases is well captured by the model for all the five provinces. However, long term predictions for Hubei reveals that the symptomatic COVID cases will show oscillatory behaviour. Further, we found that effective management of quarantined individuals is more effective than management of isolated individuals to reduce the disease burden. Numerical results show that the modification factor for quarantine, modification factor for isolation and transmission rate are quite effective in reduction of the COVID cases in Hubei. Thus, COVID is controllable by reducing contacts with infected people and increasing the efficiency of quarantine and isolation. Health care officials should supply medications, protective masks and necessary human resources in the affected areas.