Coupled disease–behavior dynamics on complex networks: A review

By Zhen Wang, Michael A. Andrews, Zhi-Xi Wu, Lin Wang, Chris T. Bauch. Physics of Life Reviews, 2015

500 citations recorded by the source corpus.

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease–behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease–behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

Subfields: Experimental and Cognitive Psychology, Modeling and Simulation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/22e55ee34096aa9025327edade92e3e52456af4e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Experimental and Cognitive Psychology

  1. Zhen Wang
  2. Nicola Perra
  3. Matjaz Perc
  4. Attila Szolnoki

In Modeling and Simulation

  1. Zhen Wang
  2. Chris T. Bauch
  3. Nicola Perra
  4. Alberto d'Onofrio
  5. Marcel Salathé
  6. Matjaz Perc

In Statistical and Nonlinear Physics

  1. Matjaz Perc
  2. Zhen Wang
  3. Alberto d'Onofrio
  4. Dawei Zhao
  5. Samit Bhattacharyya
  6. Nicola Perra
  7. Piero Manfredi
  8. Chris T. Bauch

Citations in the corpus