It is observed that the proposed model is more intuitive than being mathematically effective. The preliminary theoretical study suggested pursuing a more robust model for understanding disease progression. This model suggests weighing the population variables. For getting more insights about the scenario, an interstate network analysis is carried out. The distance between states is defined in the form of the shortest path distance between the corresponding pair of nodes in the interstate network. With the day wise data of infected individuals of COVID-19 across the different states in India, an interstate network has been built. The nodes in these networks are states with labels denoting the count of COVID-19 patients.
The initial analysis highlights that degree of a node (representing the number of COVID-19 affected individuals in a state) has a higher significance than between the centrality of that node. This is possibly because long-distance migration did not happen after the lockdown was imposed. So, the hub nodes did not get affected much.