IIT Kharagpur has developed a prediction system to help predict the future spread of COVID-19 and help decision making in health-care, industry, economy, and even academics.
Prof Abhijit Das from the Dept of Computer Science and Engineering has developed a logistic model which can be used to fit the available daily counts of infection cases.
Through a detailed study following a clear statistical model, it is indicated by Professor Das and his team of researchers that India is yet to achieve a steady pattern in the spread of the disease.
Further, India is unlikely to get rid of Covid-19, before the end of The data used for such predictions pertain to the entire country and certainly for the eight most affected States in the country including West Bengal, Maharashtra, Tami Nadu, Delhi, Gujarat, Uttar Pradesh, Rajasthan and Madhya Pradesh.
According to Professor Das, the data used is only the daily infection counts available in the public domain without accessing sensitive information pertaining to medical records or contact-tracing data for a large fraction of the population.
Despite that, the prediction curves showed remarkably good fitting with the past data and can be used for future planning.
Professor Virendra Kumar Tewari, Director, IIT Kharagpur is very much optimistic about the prediction system as he said, "People have been living in an uncertain black box without the knowledge about which way life is going to turn and how to plan their activities.
A study like this based on a clear statistical model will enable them to understand and plan their way forward.
The model though experimental, could prove to be helpful in planning our academic semester and policy matters related to the Institute and the campus under the current circumstances.
" However, the predictions for future change quite rapidly with time. There are several potential factors for this, such as different mobility patterns of Indian people in different phases of lockdown, large-scale migration of workers, change in diagnostic facilities and evolution of the coronavirus.
These are well beyond the control of the logistic model or any other currently known prediction model for that matter. Although the implementation fails to generate stable and reliable predictions at the moment, the trend clearly reveals that the disease is going to stay in the country for many more months.
Professor Das said, " This does not leave us in a region of comfort, but the reality has to be accepted, and appropriate plans must be chalked out to address all the issues associated with the outbreak of the pandemic.
