scholarly journals Contact network changes in ordered and disordered disk packings

Soft Matter ◽  
2020 ◽  
Vol 16 (41) ◽  
pp. 9443-9455 ◽  
Author(s):  
Philip J. Tuckman ◽  
Kyle VanderWerf ◽  
Ye Yuan ◽  
Shiyun Zhang ◽  
Jerry Zhang ◽  
...  
Keyword(s):  
Packing Fraction ◽  
Contact Network ◽  
Contact Networks ◽  
Disk Packings

There are two ways to transition between different contact networks, point and jump changes, as shown in a packing fraction-strain landscape.

scholarly journals Spatial analyses of wildlife contact networks

2015 ◽  
Vol 12 (102) ◽  
pp. 20141004 ◽  
Author(s):  
Stephen Davis ◽  
Babak Abbasi ◽  
Shrupa Shah ◽  
Sandra Telfer ◽  
Mike Begon
Keyword(s):  
Critical Role ◽  
Host Density ◽  
Spatial Arrangement ◽  
Spatial Proximity ◽  
Contact Network ◽  
Spatial Constraints ◽  
Contact Networks ◽  
Proximity Graphs ◽  
Contact Rates ◽  
Pathogen Persistence

Datasets from which wildlife contact networks of epidemiological importance can be inferred are becoming increasingly common. A largely unexplored facet of these data is finding evidence of spatial constraints on who has contact with whom, despite theoretical epidemiologists having long realized spatial constraints can play a critical role in infectious disease dynamics. A graph dissimilarity measure is proposed to quantify how close an observed contact network is to being purely spatial whereby its edges are completely determined by the spatial arrangement of its nodes. Statistical techniques are also used to fit a series of mechanistic models for contact rates between individuals to the binary edge data representing presence or absence of observed contact. These are the basis for a second measure that quantifies the extent to which contacts are being mediated by distance. We apply these methods to a set of 128 contact networks of field voles ( Microtus agrestis ) inferred from mark–recapture data collected over 7 years and from four sites. Large fluctuations in vole abundance allow us to demonstrate that the networks become increasingly similar to spatial proximity graphs as vole density increases. The average number of contacts, , was (i) positively correlated with vole density across the range of observed densities and (ii) for two of the four sites a saturating function of density. The implications for pathogen persistence in wildlife may be that persistence is relatively unaffected by fluctuations in host density because at low density is low but hosts move more freely, and at high density is high but transmission is hampered by local build-up of infected or recovered animals.

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.

scholarly journals Incorporating genomic methods into contact networks to reveal new insights into animal behaviour and infectious disease dynamics

Behaviour ◽  
2018 ◽  
Vol 155 (7-9) ◽  
pp. 759-791 ◽  
Author(s):  
Marie L.J. Gilbertson ◽  
Nicholas M. Fountain-Jones ◽  
Meggan E. Craft
Keyword(s):  
Infectious Disease ◽  
Disease Ecology ◽  
Pathogen Transmission ◽  
Contact Network ◽  
Contact Networks ◽  
Host Behaviour ◽  
Infectious Disease Dynamics ◽  
Insight Into ◽  
Dynamic Interplay ◽  
Broad Overview

Abstract Utilization of contact networks has provided opportunities for assessing the dynamic interplay between pathogen transmission and host behaviour. Genomic techniques have, in their own right, provided new insight into complex questions in disease ecology, and the increasing accessibility of genomic approaches means more researchers may seek out these tools. The integration of network and genomic approaches provides opportunities to examine the interaction between behaviour and pathogen transmission in new ways and with greater resolution. While a number of studies have begun to incorporate both contact network and genomic approaches, a great deal of work has yet to be done to better integrate these techniques. In this review, we give a broad overview of how network and genomic approaches have each been used to address questions regarding the interaction of social behaviour and infectious disease, and then discuss current work and future horizons for the merging of these techniques.

The real other? Museum objects in digital contact networks

2012 ◽  
Vol 17 (3) ◽  
pp. 265-286 ◽  
Author(s):  
Carl Hogsden ◽  
Emma K Poulter
Keyword(s):  
British Museum ◽  
Contact Network ◽  
Contact Networks ◽  
The Real ◽  
Meaning Change ◽  
Museum Objects ◽  
Digital Objects ◽  
To Come ◽  
The University ◽  
Relational Capacities

What can museum objects do when they are placed within a digital contact network – a system made up of reciprocally linked but otherwise separate nodes in which control and ownership of content lies with each location? What new connections are enabled through the placement of objects within this contact network and what are the new understandings that result? Dynamics of access, ownership and meaning change when museum collections are transformed into digital forms, in ways that require the reconceptualization of digital objects and their relational capacities. In theory and in practice, the ‘real’ and the digital object are often framed as disconnected and oppositional entities, a separation that hinders approaches to, and uses of, digital forms. Using examples of recent projects at the University of Cambridge Museum of Archaeology and Anthropology, and at the British Museum, it is argued that digital contact networks enable the unique qualities of digital objects to come to the fore, providing platforms for effective engagement and digital reciprocation.

scholarly journals Targeted pandemic containment through identifying local contact network bottlenecks

2021 ◽  
Vol 17 (8) ◽  
pp. e1009351
Author(s):  
Shenghao Yang ◽  
Priyabrata Senapati ◽  
Di Wang ◽  
Chris T. Bauch ◽  
Kimon Fountoulakis
Keyword(s):  
Disease Transmission ◽  
Network Flow ◽  
State Of The Art ◽  
Simulation Models ◽  
Simulation Modelling ◽  
Structural Features ◽  
Contact Network ◽  
Contact Networks ◽  
Edge Betweenness ◽  
Models Of Disease

Decision-making about pandemic mitigation often relies upon simulation modelling. Models of disease transmission through networks of contacts–between individuals or between population centres–are increasingly used for these purposes. Real-world contact networks are rich in structural features that influence infection transmission, such as tightly-knit local communities that are weakly connected to one another. In this paper, we propose a new flow-based edge-betweenness centrality method for detecting bottleneck edges that connect nodes in contact networks. In particular, we utilize convex optimization formulations based on the idea of diffusion with p-norm network flow. Using simulation models of COVID-19 transmission through real network data at both individual and county levels, we demonstrate that targeting bottleneck edges identified by the proposed method reduces the number of infected cases by up to 10% more than state-of-the-art edge-betweenness methods. Furthermore, the proposed method is orders of magnitude faster than existing methods.

scholarly journals Revealing mechanisms of infectious disease spread through empirical contact networks

2021 ◽  
Vol 17 (12) ◽  
pp. e1009604
Author(s):  
Pratha Sah ◽  
Michael Otterstatter ◽  
Stephan T. Leu ◽  
Sivan Leviyang ◽  
Shweta Bansal
Keyword(s):  
Infectious Disease ◽  
Incomplete Data ◽  
Model Comparison ◽  
Transmission Rate ◽  
Disease Spread ◽  
Contact Network ◽  
Statistical Tool ◽  
Contact Networks ◽  
Crithidia Bombi ◽  
Transmission Pathways

The spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling the dynamics of infectious disease spread through contact networks, however, can be challenging due to limited knowledge of how an infectious disease spreads and its transmission rate. We developed a novel statistical tool, INoDS (Identifying contact Networks of infectious Disease Spread) that estimates the transmission rate of an infectious disease outbreak, establishes epidemiological relevance of a contact network in explaining the observed pattern of infectious disease spread and enables model comparison between different contact network hypotheses. We show that our tool is robust to incomplete data and can be easily applied to datasets where infection timings of individuals are unknown. We tested the reliability of INoDS using simulation experiments of disease spread on a synthetic contact network and find that it is robust to incomplete data and is reliable under different settings of network dynamics and disease contagiousness compared with previous approaches. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumblebee colonies and Salmonella in wild Australian sleepy lizard populations. INoDS thus provides a novel and reliable statistical tool for identifying transmission pathways of infectious disease spread. In addition, application of INoDS extends to understanding the spread of novel or emerging infectious disease, an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.

scholarly journals Detecting concurrent mood in daily contact networks: an online participatory cohort study with a diary approach

BMJ Open ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. e020600 ◽  
Author(s):  
Ta-Chien Chan ◽  
Tso-Jung Yen ◽  
Tsuey-Hwa Hu ◽  
Yang-chih Fu ◽  
Jing-Shiang Hwang
Keyword(s):  
Cohort Study ◽  
Well Being ◽  
Contact Network ◽  
Subjective Well Being ◽  
Contact Networks ◽  
Specific Contact ◽  
Mood Score ◽  
Rich Information ◽  
Complete Contact ◽  
Rich Data

ObjectivesThis paper examines how people express personal mood concurrently with those connected with them by one or two degrees of separation.DesignParticipatory cohort study.SettingOnline contact diary.Participants133 participants kept online diaries for 7 months in 2014, which included 127 455 contacts with 12 070 persons.Main outcome measuresDiary keepers rated a contacted person’s mood during each specific contact, as well as the strength of ties between any pairs of such contacted persons. Such rich information about ties and contacts enable us to construct a complete contact network for each diary keeper, along with the network members’ mood and tie strength. We calculate one’s overall mood by that person’s average mood score during the study period and take the shortest path between any given pair of contacted persons as the degree of separation. We further assume that two connecting persons in a contact network have made contact with each other during the study period, which allows us to examine whether and how personal moods occur concurrently within these contact networks.ResultsUsing mixed-effects models while controlling for covariates at individual, tie and contact levels, we show that personal mood score positively and significantly correlates with the average mood among those directly tied to the person. The same effect remains positive and significant for those connected to the person by two degrees, although the effect size is reduced by about one-half. The mood of anyone separated by more than two degrees is statistically irrelevant.ConclusionsApplying network perspectives and rich data at both tie and contact levels to inquiries about subjective well-being, the current study sheds new light on how an improved diary approach can help explain the sophisticated ways in which individuals express their personal moods concurrently during social interactions in everyday life, contact by contact.

scholarly journals Seasonality and pathogen transmission in pastoral cattle contact networks

2017 ◽  
Vol 4 (12) ◽  
pp. 170808 ◽  
Author(s):  
Kimberly VanderWaal ◽  
Marie Gilbertson ◽  
Sharon Okanga ◽  
Brian F. Allan ◽  
Meggan E. Craft
Keyword(s):  
Water Resources ◽  
Disease Outbreaks ◽  
Dry Season ◽  
Pathogen Transmission ◽  
Contact Network ◽  
Wet Season ◽  
Contact Networks ◽  
Contact Rates ◽  
Animal Populations ◽  
The Impact

Capturing heterogeneity in contact patterns in animal populations is essential for understanding the spread of infectious diseases. In contrast to other regions of the world in which livestock movement networks are integral to pathogen prevention and control policies, contact networks are understudied in pastoral regions of Africa due to the challenge of measuring contact among mobile herds of cattle whose movements are driven by access to resources. Furthermore, the extent to which seasonal changes in the distribution of water and resources impacts the structure of contact networks in cattle is uncertain. Contact networks may be more conducive to pathogen spread in the dry season due to congregation at limited water sources. Alternatively, less abundant forage may result in decreased pathogen transmission due to competitive avoidance among herds, as measured by reduced contact rates. Here, we use GPS technology to concurrently track 49 free-roaming cattle herds within a semi-arid region of Kenya, and use these data to characterize seasonal contact networks and model the spread of a highly infectious pathogen. This work provides the first empirical data on the local contact network structure of mobile herds based on quantifiable contact events. The contact network demonstrated high levels of interconnectivity. An increase in contacts near to water resources in the dry season resulted in networks with both higher contact rates and higher potential for pathogen spread than in the wet season. Simulated disease outbreaks were also larger in the dry season. Results support the hypothesis that limited water resources enhance connectivity and transmission within contact networks, as opposed to reducing connectivity as a result of competitive avoidance. These results cast light on the impact of seasonal heterogeneity in resource availability on predicting pathogen transmission dynamics, which has implications for other free-ranging wild and domestic populations.

scholarly journals Spatial utilization predicts animal social contact networks are not scale-free

2017 ◽  
Vol 4 (12) ◽  
pp. 171209
Author(s):  
Alex James ◽  
Jeanette C. McLeod ◽  
Carlos Rouco ◽  
Kyle S. Richardson ◽  
Daniel M. Tompkins
Keyword(s):  
Network Architecture ◽  
Social Contact ◽  
Computational Effort ◽  
Contact Network ◽  
Brushtail Possum ◽  
Contact Networks ◽  
Scale Free ◽  
The Social ◽  
Social Contact Networks ◽  
Analytical Result

While heterogeneity in social behaviour has been described in many human contexts it is often assumed to be less common in the animal kingdom even though scale-free networks are observed. This homogeneity raises the question of whether the patterns of behaviour necessary to account for scale-free social contact networks, where the degree distribution follows a power law, i.e. a few individuals are very highly connected but most have only a few connections, occur in animals, or whether other mechanisms are needed to produce realistic contact network architectures. We develop a space-utilization model for individual animal behaviour to predict the individuals' social contact network. Using basic properties of the χ 2 distribution we present a simple analytical result that allows the model to give a range of predictions with minimal computational effort. The model results are tested on data collected in New Zealand for the social contact networks of the wild brushtail possum ( Trichosurus vulpecula ). Our model provides a better prediction of network architecture than other simple models, including a scale-free model.

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