Modeling infectious diseases: Understanding social connectivity to control infectious diseases. (2021)

• Record Type: Journal Article
• Authors: Wazir, Samar; Gour, Surendra; Nafis, Md Tabrez; Khan, Rijwan
• Is Part Of: Informatics in medicine unlocked. Volume 26(2022)
• Publication Date: 2021
• Subjects: Infectious diseases -- Susceptible population -- Social networks -- Epidemiological model -- Clustering -- Probability; Medical informatics -- Periodicals; 610.285
• DOI: 10.1016/j.imu.2021.100761
• Languages: English
• ISSNs: 2352-9148

Abstract

Abstract: Contagious diseases and their impacts can be modulated to a higher extent by implementing proper mathematical or statistical models that comprehend connectivity and the spreading patterns among populations. An approach has been presented throughout this paper to find the optimal connectivity. And thus, this is possible only by analyzing the models of the network formation and comparing them with the real-world data. The study uses the connectivity coefficient for improving the infectious disease modelling and testing the Susceptible-Infectious-Removed stochastic model. In addition, the results of the proposed model are discussed in the context of quantification of risk as it helps trace and avoid infections to prevent any further outbreak of the diseases.