| Outcome/Output:||Developed an extended SEIR model with network diffusion models and different kinds of community interaction models to present a more realistic model of the spread of COVID-19 in Bangalore. The underlying network is created in such a way that each node represents a location. It can represent a different entity at different scale and hence, this framework can be expanded to wards, districts or even states-level. These nodes representing locations are connected via edges. The model provides a detailed description of the spread of COVID-19 at a very granular level and hence, was used in predicting epidemic outcome in the dashboard presented.
Developed a game-theoretic agent-based model, assimilating the epidemic information for a meta-population model, to capture the effect of adaptive behavioral responses in the population. The model shows that multiple epidemic waves arise due to the high cost of compliance and protection fatigue, which are in line with current upsurge in the number of cases across the country.|