Covid-19 pandemic has two characteristics: (i) asymptomatic cases (both detected and undetected) that could result in fresh infections, and (ii) time-varying characteristics due to new variants, NPIs etc. We developed a model SUTRA (Susceptible, Undetected, Tested positive, and Removed, Analysis) for predicting the course of COVID-19. All parameters in the SUTRA model can be robustly estimated purely from data and can be re-estimated at any time in the pandemic. The model also indicates when recalibration is needed. SUTRA can also estimate the number of undetected cases. To the best of our knowledge this is the only model with all these capabilities. The SUTRA approach can be applied at various levels of granularity, from national to district, and to any country with data on daily new cases and recoveries. The approach has been validated on the pandemic in India during all three waves, and also on many other countries. A broad conclusion is that the best way to handle the pandemic is to allow the disease to spread slowly in society, and a"zero-COVID"policy is not sustainable. COVID-19 needs a dynamic model like SUTRA which can help plan logistics and interventions by policy makers.
SUTRA: A Novel Approach to Modelling Pandemics with Applications to COVID-19