Temporal network structures controlling disease spreading.

@article{Holme2016TemporalNS,
  title={Temporal network structures controlling disease spreading.},
  author={Petter Holme},
  journal={Physical review. E},
  year={2016},
  volume={94 2-1},
  pages={
          022305
        }
}
  • Petter Holme
  • Published 3 May 2016
  • Computer Science
  • Physical review. E
We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks-with respect to time to extinction and average outbreak size-is smaller than between the temporal and static topologies. This suggests… 
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References

SHOWING 1-10 OF 29 REFERENCES
Epidemiologically Optimal Static Networks from Temporal Network Data
TLDR
This paper investigates conceptually simple methods to construct static graphs for network epidemiology from temporal contact data, and evaluates these methods on empirical and synthetic model data.
Birth and death of links control disease spreading in empirical contact networks
TLDR
It is found that the birth and death of links, and the total number of contacts over a link, are essential to predict outbreaks, while the exact times of contacts between the beginning and end, or the interevent interval distribution, do not matter much.
Information content of contact-pattern representations and predictability of epidemic outbreaks
TLDR
This paper studies both outbreak sizes from unknown sources, and from known states of ongoing outbreaks, using empirical proximity data to investigate the effect of successive inclusions of more information in the temporal network structure of the data sets.
Predicting and controlling infectious disease epidemics using temporal networks
TLDR
This work reviews recent results of network epidemiology for such temporal network data with time stamps, and calls for extended analysis tools for network Epidemiology, which has, to date, mostly viewed networks as static entities.
Networks and epidemic models
TLDR
A variety of methods are described that allow the mixing network, or an approximation to the network, to be ascertained and how the two fields of network theory and epidemiological modelling can deliver an improved understanding of disease dynamics and better public health through effective disease control are suggested.
Temporal Networks
Extinction Times of Epidemic Outbreaks in Networks
TLDR
This work characterize how the maximal extinction time in SIR simulations on networks depend on the network structure, and finds that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction.
Modern temporal network theory: a colloquium
TLDR
This colloquium reviews the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years, which includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more.
Spreading dynamics following bursty human activity patterns.
TLDR
The susceptible-infected model with power-law waiting time distributions P(τ)~τ^{-α), as a model of spreading dynamics under heterogeneous human activity patterns, is studied to unify individual activity patterns with macroscopic collective dynamics at the network level.
Epidemic spreading in scale-free networks.
TLDR
A dynamical model for the spreading of infections on scale-free networks is defined, finding the absence of an epidemic threshold and its associated critical behavior and this new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.
...
...