Pandemic Simulation and Contact Tracing: Identifying Super Spreaders

In the context of infectious human borne diseases, super spreaders are people who can transmit diseases to a larger number of people than the average person. Medically, it is assumed that one in every five people can be a super spreader. Using graph theory and social network analysis, we have identified these super spreaders in Chennai, given a synthetic dataset with the location history of a particular individual. We have also predicted the spread of the disease. Network graphs have been used to visualise the spread. This aids visualization of the spread of the pandemic and reduces the ion that accompanies statistical data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.