From UPSC perspective, the following things are important :
Prelims level : Not much
Mains level : Paper 2- Issues with model predicting Covid-19 cases
- SUTRA (Susceptible, Undetected, Tested (positive), and Removed Approach) first came into public attention when one of its expert members announced in October that India was “past its peak”.
- Unlike many epidemiological models that extrapolated cases based on the existing number of cases, the behaviour of the virus and manner of spread, the SUTRA model chose a “data centric approach”.
- However, the surge in the second wave was several times what any of the modellers had predicted.
- The predictions of the SUTRA model were too variable to guide government policy.
So, what went wrong in the model
- The SUTRA model was problematic as it relied on too many parameters, and recalibrated those parameters whenever its predictions broke down.
- The more parameters you have, the more you are in danger of overfitting.
- One of the main reasons for the model not gauging an impending, exponential rise was that a constant indicating contact between people and populations went wrong.
- Further the model was ‘calibrated’ incorrectly.
- The model relied on a serosurvey conducted by the ICMR in May that said 0.73% of India’s population may have been infected at that time.
- This calibration led our model to the conclusion that more than 50% population was immune by January.
- The SUTRA model’s omission of the importance of the behaviour of the virus; the fact that some people were bigger transmitters; a lack of accounting for social or geographic heterogeneity and not stratifying the population by age as it didn’t account for contacts between different age groups also undermined its validity.