Researchers at the Indian Institute of Technology in Delhi have taken a significant step towards fighting Covid-19 in India. They have developed a web-based dashboard named PRACRITI, which stands for PRediction and Assessment of CoRona Infections and Transmission in India. It aims to predict the spread of Covid-19 across the country. This tool is designed to provide detailed, timely, and essential predictions to aid in the management of the disease.
Predicting Covid-19 Cases With PRACRITI
PRACRITI has been designed to provide detailed predictions of Covid-19 cases across India, both on a state-wise and a district-wise basis, for a span of three weeks. The prediction data is updated every week to account for various factors including administrative interventions, severity of the viral strain, and changes in the weather. It also considers the effects of different lockdown scenarios, such as the implications of shutting down district boundaries and implementing varied levels of lockdown within a district. Importantly, it also incorporates the impact of population movement across district or state borders due to Covid-19.
Determining the R0 Value
An essential feature of PRACRITI is its ability to provide the Reproduction number (R0) values for each district and state. These values are based on data obtained from reliable sources, such as the Ministry of Health and Family Welfare, National Disaster Management Authority (NDMA), and the World Health Organization (WHO). The R0 value, pronounced ‘R naught,’ represents the number of individuals a single infected person can infect. For instance, if an infected person spreads Covid-19 to two others, the R0 value is two. Controlling and reducing this number is crucial in managing the spread of Covid-19 in India.
The Working Model
The predictions generated by PRACRITI are based on a mathematical model named the Adaptive, Interacting, Cluster-based, Susceptible, Exposed, Infected, Removed (AICSEIR) model. It is a modified version of the traditional SEIR model and takes into account interactions between sub-populations like districts or states. The model classifies the population into four categories: those who have not been exposed to the virus (Susceptible), those exposed to the virus from an infected person (Exposed), those actively infected with Covid-19 (Infected), and those no longer carrying the virus (Removed).
Benefits of PRACRITI
The PRACRITI platform holds immense potential for healthcare organizations as well as local and central authorities. It allows efficient planning for various future scenarios and aids in optimizing resource allocation. By identifying districts and states with higher R0 values, rigorous measures can be implemented to control the spread of Covid-19 in these areas. Conversely, regions exhibiting low R0 values can focus on sustaining their preventive measures and ensuring constant vigilance.
