IIT-G, Duke-NUS carry out data-driven assessment of COVID-19 situation in India

Researchers from the Indian Institute of Technology Guwahati, India, and the Duke-NUS Medical School, Singapore, have used data science models to analyse and predict the total number of infected people for different States in India in the next 30 days.

The researchers used the Susceptible Infectious Susceptible (SIS) models, along with the model-free daily infection-rate and analyzed factors in the exponential, the logistic model.

The report is based on the growth of recent active cases, along with the daily infection-rate (DIR) values for each State.

A state is labelled as ‘severe’ if there is a non-decreasing trend in DIR values over the last two weeks along with a near exponential growth in active infected cases.

A state is labelled ‘moderate’ if an almost decreasing trend in DIR values is observed over the last two weeks along with neither increasing nor decreasing growth in active infected cases.

A state is labelled ‘controlled’ if a decreasing trend in the last two weeks’ DIR values is observed along with a decreasing growth in active infected cases.

The researchers recommended that this composite prediction will be used for assessment purposes for each State. States that are in a severe category are expected to take serious preventive measures immediately to combat the COVID-19 pandemic.