IISc model simulates COVID spread

However, researchers make it clear the model is a measure for qualitative predictions (for instance to get an overall picture about the rise and fall of the curve) 
File Photo of Indian Institute of Science (IISC) in Bengaluru. (Photo | Express Photo Services)
File Photo of Indian Institute of Science (IISC) in Bengaluru. (Photo | Express Photo Services)

BENGALURU: How would the novel coronavirus spread if there was no lockdown? If you’re curious about this, an online model developed by the Indian Institute of Science can help you understand the possible spread of the pandemic without interventions. Prof Vishwesha Guttal and Pranav Minasandra of the Centre for Ecological Sciences at IISc have developed an age-structured SIER model which allows users to see how the pandemic could have grown between March 15 and May 15. The model can be accessed at guttal.shinyapps.io/seir-agestr-covid/. 

However, researchers make it clear the model is a measure for qualitative predictions (for instance to get an overall picture about the rise and fall of the curve) but not to make forecasts about the pandemic. 
The SEIR model helps you understand that a hypothetical number of healthy people are Susceptible (S) to the virus and could be Exposed (E) to people who may have the virus, but do not show symptoms. They may then become Infectious (I) and can transmit it to others. Lastly, they would Recover (R) from either mild or severe infection or may even die. 

The model allows users to change all parameters such as numbers of days over which you want to check the spread, intervention measures, strength of the intervention, how many days a lockdown lasts, and whether results are calibrated for states such as Karnataka, Maharashtra, Tamil Nadu, or all of India.
The population is categorised into two age groups, above and below 60 years of age as the virus has different effects on the two groups. One can also see how ‘quarantining vulnerable’ (or reverse quarantine that Kerala has adopted) will change the rate of transmission. The app also shows graphs for the predicted number of cases and hospitalisations.

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