Representational image.

Indian Institute of Technology-Guwahati (IIT-Guwahati) and Singapore’s Duke-NUS Medical School have come up with an alternative model to analyse and predict the number of COVID-19 infected people in 30 days in different states of the country.

The data-science model, developed by the team of researchers, is a combination of all three different models being used in the country at present, according to reports.

The model predicts the cases as per logistics method and exponential method (prediction if the situation turns severe).

The states are divided into three categories – moderate, severe and controlled.

The model follows a different categorisation than the currently adopted Green Zone, Orange Zone and Red Zone classification.

According to the team, India will have 1.5 lakh COVID-19 cases in next 30 days as per logistic method and 5.5 lakh cases as per exponential method.

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

The death toll due to COVID-19 rose to 2,206 and the number of cases climbed to 67,152 in the country on Monday, according to the Union Health Ministry.