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IIT Delhi introduces PRACRITI Coronavirus dashboard for COVID-19 tracking

Researchers at the Indian Institute of Technology-Delhi have developed a web-based dashboard to predict the spread of deadly Covid-19 in India. The mobile-friendly dashboard, named as PRACRITI – PRediction and Assessment of CoRona Infections and Transmission in India, gives a detailed state-wise and district-wise predictions of viral cases in the country.

The projections are given for a three-week period, which is updated on a weekly basis. The researchers believe that such a platform will be highly useful for healthcare bodies, local and central authorities, to efficiently plan for different future scenarios and resource allocation.

A key parameter of interest on Covid-19 is the basic reproduction number R0 and its countrywide variability. R0 refers to the number of people to whom the disease spreads from a single infected person. For instance, if an active Covid-19 patient infects two uninfected persons, the R0 is two. Hence, reduction of R0 is the key in controlling and mitigating Covid-19 in India.

PRACRITI provides the R0 values of each district and state in India based on the data available from sources such as the Ministry of Health and Family Welfare, the National Disaster Management Authority (NDMA), and World Health Organisation (WHO).

Led by Professor N. M. Anoop Krishnan of IIT-Delhi’s Civil Engineering Department, in collaboration with Professor Hariprasad Kodamana, a team of volunteers from IIT Delhi, namely, Hargun Singh, Ravinder, Devansh Agrawal, Amreen Jan, Suresh, and Sourabh Singh have developed this dashboard. Krishnan said: “Getting the district-wise R0 is crucial as this will enable authorities to know the exact rate of spread in India locally.”

Kodamana, of the Chemical Engineering Department, said: “Three weeks ahead district-wise prediction of infections in India provided by PRACRITI can be of immense help for policymakers for planning strategic interventions for controlling Covid-19 spread in India.”

The model also accounts for the effect of different lockdown scenarios, such as the effect of locking down the district boundaries and implementing different levels of lockdown within a district.

These predictions can help the districts and states having higher R0 to take rigorous measures to control the spread of Covid-19, while for those with low R0 they need to sustain measures and remain very vigilant.

The predictions in the dashboard are based on a newly-developed mathematical model that divides the population into four classes i.e. susceptible, exposed, infected, and removed.

“Susceptible” refers to people who have not been exposed to the coronavirus, “exposed” refers to those who have been exposed to the virus from an infected person, “infected” refers to those who are actively infected with Covid-19, and “removed” refers to those who are no longer a carrier of the virus.

The distinguishing feature of the model developed by the IIT Delhi researchers is the inclusion of the effect of movement of population across district or state borders in the spread of Covid-19. Based on the computed values of R0, the researchers developed a detailed district-wise model for India to predict the number of actively infected people in each district.

Further, to accommodate various effects due to administrative interventions, the virulence of the viral strain, change of weather patterns, the model will be updated on a weekly basis in an adaptive fashion to account these variations for accurate predictions.

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