How network properties and epidemic parameters influence stochastic SIR dynamics on scale-free random networks
arXiv:2011.10595 · doi:10.1080/17477778.2022.2100724
Abstract
With the premise that social interactions are described by power-law distributions, we study a SIR stochastic dynamic on a static scale-free random network generated via configuration model. We verify our model with respect to deterministic considerations and provide a theoretical result on the probability of the extinction of the disease. Based on this calibration, we explore the variability in disease spread by stochastic simulations. In particular, we demonstrate how important epidemic indices change as a function of the contagiousness of the disease and the connectivity of the network. Our results quantify the role of starting node degree in determining these indices, commonly used to describe epidemic spread.
22 pages, 9 figures
References in corpus (10)
- Scale-free brain functional networks
- Scale-free networks are rare
- A message passing approach for general epidemic models
- Fundamentals of spreading processes in single and multilayer complex networks
- Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: results of a census-calibrated model
- Identifying an influential spreader from a single seed in complex networks via a message-passing approach
- Impact of network assortativity on epidemic and vaccination behaviour
- The configuration model for Barabasi-Albert networks
- Assessing node risk and vulnerability in epidemics on networks
- Epidemic extinction in networks: Insights from the 12,110 smallest graphs