Bellingeri, M.; Bevacqua, D.; Scotognella, F.; Cassi, D. The Critical Role of Networks to Describe Disease Spreading Dynamics in Social Systems: A Perspective. Mathematics2024, 12, 792.
Bellingeri, M.; Bevacqua, D.; Scotognella, F.; Cassi, D. The Critical Role of Networks to Describe Disease Spreading Dynamics in Social Systems: A Perspective. Mathematics 2024, 12, 792.
Bellingeri, M.; Bevacqua, D.; Scotognella, F.; Cassi, D. The Critical Role of Networks to Describe Disease Spreading Dynamics in Social Systems: A Perspective. Mathematics2024, 12, 792.
Bellingeri, M.; Bevacqua, D.; Scotognella, F.; Cassi, D. The Critical Role of Networks to Describe Disease Spreading Dynamics in Social Systems: A Perspective. Mathematics 2024, 12, 792.
Abstract
This review underscores the critical significance of incorporating network perspectives in epidemiology. Classic compartmental models (CM) employed to describe epidemic spreading often fail to capture the intricacies of real disease dynamics. Rooted in the mean-field assumption, CM models oversimplify by assuming that every individual has the potential to "infect" any other, neglecting the inherent complexity of underlying network structures. Given that social interactions follow a networked pattern with specific links between individuals based on social behaviors, the amalgamation of classic CM and network science in epidemiology becomes essential for a more authentic portrayal of epidemic spreading. This review delves into noteworthy research studies that, from various perspectives, elucidate how the synergy between networks and CM can enhance the accuracy of epidemic descriptions. In conclusion, we explore research prospects aimed at further elevating the integration of networks within the realm of epidemiology, recognizing its pivotal role in refining our understanding of disease dynamics.
Keywords
complex networks; complex systems; statistical mechanics; graph theory
Subject
Physical Sciences, Theoretical Physics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
