ArticleScientific reports2017
Dynamics of epidemic diseases on a growing adaptive network.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Evolution Equations on Co-evolving Graphs: Long-Time Behaviour and the Graph-Continuity Equation.Journal of nonlinear science · 2026Article
- Cross-feeding creates tipping points in microbiome diversity.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Dynamics of phase oscillator networks with synaptic weight and structural plasticity.Scientific reports · 2022Article
- Article
- How do mobility restrictions and social distancing during COVID-19 affect oil price?Journal of statistical theory and practice · 2022Article
- Contact Adaption During Epidemics: A Multilayer Network Formulation Approach.IEEE transactions on network science and engineering · 2019Article
- Information Spread and Topic Diffusion in Heterogeneous Information Networks.Scientific reports · 2018Article
- Coupled disease-behavior dynamics on complex networks: A review.Physics of life reviews · 2015Review
- Epidemic cycles driven by host behaviour.Journal of the Royal Society, Interface · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.