Epidemic dynamics on an adaptive network.

By Thilo Gross, Carlos J Dommar D'Lima, Bernd Blasius. Physical Review Letters, 2005

834 citations recorded by the source corpus.

Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.

Subfields: Public Health, Environmental and Occupational Health, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/5dc655e2834c313bfa0671064a7f70a429edeca4

How researchers see this paper

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

In Public Health, Environmental and Occupational Health

In Statistical and Nonlinear Physics

Citations in the corpus

Statistical physics of vaccination (2016, background): “Early on in epidemiology, it has been pointed out that adaptations of various kinds can lead to a series of interesting phenomena, such as degree mixing patterns, oscillations, hysteresis, and phase transition between disease-free and endemic states [52].”
Structure and Dynamics of Networks (2009, background): “It is as well the reason for the absence of an epidemic threshold in case of disease spreading [Ahn et al., 2006, Boguñá et al., 2003, Boguñá et al., 2003, Gross et al., 2006], which means that a disease will always persist on a scale-free network.”
The spread of awareness and its impact on epidemic outbreaks (2009, background): “Attempts at extending this to incorporate individual behavioral reactions have focused on vaccination decisions and consequences thereof (13–16), dynamic rewiring of transmissive contacts (17), or incidence-dependent reductions in contact rate (18).”
Coupled disease–behavior dynamics on complex networks: A review (2015, background): “first proposed an adaptive scenario: a susceptible node is able to prune the infected link and rewire with a healthy agent with a certain probability [124].”
Social network theory: new insights and issues for behavioral ecologists (2009, background): “The fact that infected individuals might change their behavior (e.g., interact with fewer people), or that uninfected individuals might avoid infected ones is not usually included even though these possibilities seem obvious (but see Gross et al. 2006).”
Moment Closure—A Brief Review (2015, neutral): “If we want to find a closure similar to the approximation (44) for second-order moments with M as in (26), then the classical choice is the pair-approximation [54, 75, 76] mabc ≈ mabmbc mb , a, b, c ∈ {S, I} (47)”
Modelling the influence of human behaviour on the spread of infectious diseases: a review (2010, positive): “In a series of theoretical studies (Gross et al. 2006; Shaw & Schwartz 2008; Zanette & RisauGusmán 2008), it was assumed that healthy individuals cut contact with infected peers while forming a new link with a random person from the remaining population at the same time.”