scholarly journals Model Reproduces Individual, Group and Collective Dynamics of Human Contact Networks

2016 ◽  
Author(s):  
Michele Starnini
Keyword(s):  
Individual Group ◽  
Contact Networks ◽  
Collective Dynamics ◽  
Human Contact

scholarly journals Model reproduces individual, group and collective dynamics of human contact networks

2016 ◽  
Vol 47 ◽  
pp. 130-137 ◽  
Author(s):  
Michele Starnini ◽  
Andrea Baronchelli ◽  
Romualdo Pastor-Satorras
Keyword(s):  
Individual Group ◽  
Contact Networks ◽  
Collective Dynamics ◽  
Human Contact

scholarly journals Identification of effective spreaders in contact networks using dynamical influence

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruaridh A. Clark ◽  
Malcolm Macdonald
Keyword(s):  
Disease Transmission ◽  
Average Rate ◽  
Laplacian Matrix ◽  
Disease Spread ◽  
Eigenvector Centrality ◽  
Contact Networks ◽  
Human Contact ◽  
Spread Dynamics ◽  
Definition Of ◽  
High Degree

AbstractContact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network’s structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.

Data Delivery Properties of Human Contact Networks

2011 ◽  
Vol 10 (6) ◽  
pp. 868-880 ◽  
Author(s):  
Nishanth Sastry ◽  
D. Manjunath ◽  
Karen Sollins ◽  
Jon Crowcroft
Keyword(s):  
Data Delivery ◽  
Contact Networks ◽  
Human Contact

scholarly journals Using network properties to predict disease dynamics on human contact networks

2011 ◽  
Vol 278 (1724) ◽  
pp. 3544-3550 ◽  
Author(s):  
Gregory M. Ames ◽  
Dylan B. George ◽  
Christian P. Hampson ◽  
Andrew R. Kanarek ◽  
Cayla D. McBee ◽  
...  
Keyword(s):  
Degree Distribution ◽  
Stochastic Simulations ◽  
Disease Spread ◽  
Contact Structures ◽  
Contact Network ◽  
Contact Networks ◽  
Human Contact ◽  
Differential Equation Models ◽  
Network Properties ◽  
Intermediate Density

Recent studies have increasingly turned to graph theory to model more realistic contact structures that characterize disease spread. Because of the computational demands of these methods, many researchers have sought to use measures of network structure to modify analytically tractable differential equation models. Several of these studies have focused on the degree distribution of the contact network as the basis for their modifications. We show that although degree distribution is sufficient to predict disease behaviour on very sparse or very dense human contact networks, for intermediate density networks we must include information on clustering and path length to accurately predict disease behaviour. Using these three metrics, we were able to explain more than 98 per cent of the variation in endemic disease levels in our stochastic simulations.

Characterizing pairwise contact patterns in human contact networks

2012 ◽  
Vol 10 (3) ◽  
pp. 524-535 ◽  
Author(s):  
Lintao Yang ◽  
Hao Jiang ◽  
Sai Wang ◽  
Lin Wang ◽  
Yuan Fang
Keyword(s):  
Contact Networks ◽  
Human Contact ◽  
Contact Patterns

scholarly journals Bootstrapping under constraint for the assessment of group behavior in human contact networks

2013 ◽  
Vol 88 (5) ◽  
Author(s):  
Nicolas Tremblay ◽  
Alain Barrat ◽  
Cary Forest ◽  
Mark Nornberg ◽  
Jean-François Pinton ◽  
...  
Keyword(s):  
Group Behavior ◽  
Contact Networks ◽  
Human Contact
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