Scientists from Ashoka University, Sonepat and ThoughtWorks Technologies, Pune have developed BharatSim - a virtual world filled with virtual people called “agents” to study how diseases spread among them. They used a computer simulation called an agent-based model (ABM) to create a digital mini-world with rule-following agents to study complex systems. BharatSim is a computer program that uses ABM to imitate real-life situations in India by creating a "synthetic population." This population can then be subject to constraints and rules to see how things like disease spread over time.
To build BharatSim, scientists used data from census reports, surveys, and other studies to create digital versions of the Indian population—complete with details like age, gender, job, health conditions, and where they live and work. Once the synthetic population was ready, scientists made their agents interact in a computerized version of Indian society. This means simulating daily activities, work routines, and school attendance—basically, all the places people might meet and interact.
With this virtual world in place, BharatSim became a platform to study how diseases spread among these virtual people. For example, during the COVID-19 pandemic, scientists used BharatSim to see when it might be safe to reopen schools or how new virus strains could affect the population. By simulating how these virtual people move and interact, BharatSim can predict what might happen if a new disease enters the picture or if the government implements certain health policies, like lockdowns.
One of the biggest questions during the COVID-19 pandemic was when it would be safe to reopen schools in India. BharatSim offered insights into this by simulating the situation considering how many people had hybrid immunity (immunity from both vaccination and infection). The results suggested that schools could have reopened as early as August 2021 with only a slight increase in COVID-19 cases. This insight could help policymakers make informed decisions that balance safety and education.
BharatSim also proved useful in studying how new variants of COVID-19 could change the disease dynamics. For example, it highlighted that the milder wave of infections caused by the Omicron variant was largely due to the pre-existing immunity among the population. It also helps in understanding the effects of different non-pharmaceutical interventions, like lockdowns, on slowing down disease spread. It showed that smartly timed lockdowns and vaccination drives could significantly reduce the number of cases.
Apart from major pandemics like COVID-19, scientists could adapt BharatSim to explore the spread of other communicable diseases, like malaria and typhoid. Apart from health interventions, BharatSim could also be used to explore how social factors, like community gathering practices or economic status, influence the spread of diseases.
Importantly, it lets scientists and policymakers explore different "what if" scenarios without affecting real people. They can test new ideas or interventions in the virtual world to see what works best before applying them in real life. This is especially important in dealing with diseases and other public health challenges. Whether in handling a pandemic or understanding complex health issues, BharatSim can be a crucial companion in making data-driven health decisions for millions of people.
This research news was partly generated using artificial intelligence and edited by an editor at Research Matters