Modeling Behavioral and Epidemic Dynamics in Social Contact Networks

Contagious diseases spread in population through the contact network and their spread is a function of the complex interplay of the biology of the contagion and behavior of the population. In this paper, we present an Individual-based Fear Model (IBFM) that associates fear-index with the individuals to indicate the extent to which an individual follows health and hygiene protocols as a self-protective measure against disease. We also study the impact of the collective behavior of individuals in communities on the size and span of the epidemic. We propose a framework to create a wire-frame that mimics the social contact network of the population in a geography by lacing it with demographic information and improves the estimates of epidemic variables for network simulation. We test the effectiveness of the demography-laced contact network using real-life COVID data for two Indian states. Since network simulations of epidemic spread are computationally expensive, we launch a systemic investigation into the possibility of predicting three epidemic variables, viz. peak day, peak infections, and span of the epidemic using the Regression Chain Model. We find that the predictions are fairly accurate for two out of three variables.