Pertinence of contact duration as edge feature for epidemic spread analysis

Identifying superspreading nodes has attracted greater attention because of its wide practical significance in various applications. Existing studies consider the edges mostly equally while designing the algorithms for the unweighted contact networks, where each connection explicitly shows whether the individuals are in contact or not. It will not consider other relevant information in the context of epidemiology study or infectious disease spread, such as proximity or total time spent between the contact nodes. The recent studies focused on the weighted network, where most of the methods have computed the edge weights by utilizing degree and k-shell measure, which captures the topological structure of the network but not the interaction duration between pair of contacts. In this study, we mainly aim to generate weighted networks to model the pathogen spread by optimal calculation of the edge weight in terms of contact duration (time spent) between individual contacts. Leveraging this interaction duration as the edge weight, we further design a novel technique, namely Real Weighted Influence (RWInf), for identifying the superspreading nodes during an epidemic outbreak. The empirical study revealed that the proposed approach outperforms with an improvement of 0.146-0.473 kendall's score in comparison with baseline approaches.