An epidemic model SIPHERD and its application for prediction of the spread of COVID-19 infection in India.

• A novel compartmental epidemic model SIPHERD is employed for COVID-19 prediction for India where it has reached at alarming level. • Impact of lockdown and the number of tests conducted per day on predictions of containment is studied. • Purely Asymptomatic cases and spread from them as well as Exposed in incubation period considered. • Increasing the tests per day by 10k every day, stringent measures on social-distancing and strict lockdown in July have significant impact on the disease spread. Originating from Wuhan, China, in late 2019, and with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread. [ABSTRACT FROM AUTHOR]