Community Size Effects on Epidemic Spreading in Multiplex Social Networks

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people’s reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals’ alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals’ risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals’ protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.     

Bursty Communication Patterns Facilitate Spreading in a Threshold-Based Epidemic Dynamics

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.     

Strong Impact of Temporal Resolution on the Structure of an Ecological Network

Most ecological networks are analysed as static structures, where all observed species and links are present simultaneously. However, this is over-simplified, because networks are temporally dynamical. We resolved an arctic, entire-season plant-flower visitor network into a temporal series of 1-day networks and compared the properties with its static equivalent based on data pooled over the entire season. Several properties differed. The nested link pattern in the static network was blurred in the dynamical version, because the characteristic long nestedness tail of flower–visitor specialists got stunted in the dynamical networks. This tail comprised a small food web of pollinators, parasitoids and hyper-parasitoids. The dynamical network had strong time delays in the transmission of direct and indirect effects among species. Twenty percent of all indirect links were impossible in the dynamical network. Consequently, properties and thus also robustness of ecological networks cannot be deduced from the static topology alone.     

Spreading Information in a Network of Interacting Neighbours

Dispersed individuals can coordinate the onset of life history events, like reproduction or migration, on a large (population) spatial scale. However, the mechanism of this synchronisation has not yet been identified. In many species signals produced by one individual stimulate signalling activity of immediate neighbours. I propose that such local focuses of signalling could transform into waves propagating in space. This hypothesis predicts that signalling self-organizes into bursts, because neighbours tend to enter activity and refractory periods together. Temporal characteristics of such pulses should be more similar in locations proximate to one another than in distant ones. Finally, denser populations should produce relatively more complex wave patterns, since the number of propagating waves is proportional to the number of individuals. These predictions were tested in an analysis of time series of numbers of territorial songs in chaffinches, Fringilla coelebs, and the results supported the hypothesis. Time series of singing activity had memory of their past states: they were autoregressive processes with spectra in which low frequency oscillations predominated. The degree of similarity in two synchronously sampled time series, measured as a Euclidean distance between their spectra, decreased with the increasing physical distance of sampling spots and the number of signalling males. It is concluded that networks of interacting neighbours may integrate populations synchronising life cycles of dispersed individuals.     

Temporal Duration and Event Size Distribution at the Epidemic Threshold

The epidemic event, seen as a nonequilibrium dynamic process, is studied through a simple stochastic system reminiscent of the classical SIR model. The system is described in terms of global and local variables and was mainly treated by means of Monte Carlo simulation; square lattices N×N, with N=23, 51, 100, 151, and 211 were used. Distinct extensive runs were performed and then classified as corresponding to epidemic or non-epidemic phase. They were examined with detail through the analysis of the event duration and event size; illustrations, such as density-like plots in the space of the model's parameters, are provided. The epidemic/non-epidemic phase presents smaller/larger relative fluctuations, whereas closer to the threshold the uncertainty reaches its highest values. Far enough from the threshold, the distribution (t) of the events time duration t shows a step-like appearance. However at the threshold line it shows an exponential behavior of the form (t) exp (-t); the same behavior is observed for the event size distribution. These results help to explain why the approach to epidemic threshold would be hard to anticipate with standard census data.     

The Evolution of the Epidemic of Charcoal-Burning Suicide in Taiwan: A Spatial and Temporal Analysis

Background

An epidemic of carbon monoxide poisoning suicide by burning barbecue charcoal has occurred in East Asia in the last decade. We investigated the spatial and temporal evolution of the epidemic to assess its impact on the epidemiology of suicide in Taiwan.

Methods and Findings

Age-standardised rates of suicide and undetermined death by charcoal burning were mapped across townships (median population aged 15 y or over = 27,000) in Taiwan for the periods 1999–2001, 2002–2004, and 2005–2007. Smoothed standardised mortality ratios of charcoal-burning and non-charcoal-burning suicide and undetermined death across townships were estimated using Bayesian hierarchical models. Trends in overall and method-specific rates were compared between urban and rural areas for the period 1991–2007. The epidemic of charcoal-burning suicide in Taiwan emerged more prominently in urban than rural areas, without a single point of origin, and rates of charcoal-burning suicide remained highest in the metropolitan regions throughout the epidemic. The rural excess in overall suicide rates prior to 1998 diminished as rates of charcoal-burning suicide increased to a greater extent in urban than rural areas.

Conclusions

The charcoal-burning epidemic has altered the geography of suicide in Taiwan. The observed pattern and its changes in the past decade suggest that widespread media coverage of this suicide method and easy access to barbecue charcoal may have contributed to the epidemic. Prevention strategies targeted at these factors, such as introducing and enforcing guidelines on media reporting and restricting access to charcoal, may help tackle the increase of charcoal-burning suicides. Please see later in the article for the Editors'' Summary     

Temporal Reliability and Lateralization of the Resting-State Language Network

The neural processing loop of language is complex but highly associated with Broca''s and Wernicke''s areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca''s and Wernicke''s areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca''s area was found to be left lateralized, while the Wernicke''s area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.     

Disrupted Ipsilateral Network Connectivity in Temporal Lobe Epilepsy

ObjectiveThe current practice under which patients with refractory epilepsy are surgically treated is based mainly on the identification of specific cortical areas, mainly the epileptogenic zone, which is believed to be responsible for generation of seizures. A better understanding of the whole epileptic network and its components and properties is required before more effective and less invasive therapies can be developed. The aim of the present study was to partially characterize the evolution of the functional network during the preictal-ictal transition in partial seizures in patients with temporal lobe epilepsy (TLE).MethodsScalp and foramen ovale (FOE) recordings from twenty-two TLE patients were analyzed under the complex network perspective. The density of links, average path length, average clustering coefficient, and modularity were calculated during the preictal and the ictal stages. Both linear–Pearson correlation–and non-linear–phase synchronization–measures were used as proxies of functional connectivity between the electrode locations areas. The transition from one stage to the other was evaluated in the whole network and in the mesial sub-networks. The results were compared with a voltage-dependent measure, namely, the spectral entropy.ResultsChanges in the global functional network during the transition from the preictal to the ictal stage show, in the linear case, that in sixteen cases (72.7%) the density of the links increased during the seizure, with a decrease in the average path length in fifteen cases (68.1%). There was also a preictal and ictal imbalance in functional connectivity during both stages (77.2% to 86.3%). The SE dropped during the seizure in 95.4% of the cases, but did not show any tendency towards lateralization. When using the nonlinear measure of functional connectivity, the phase synchronization, similar results were obtained.ConclusionsIn TLE patients, the transition to the ictal stage is accompanied by increasing global synchronization and a more ordered spectral content of the signals, indicated by lower spectral entropy. The interictal connectivity imbalance (lower ipsilateral connectivity) is sustained during the seizure, irrespective of any appreciable imbalance in the spectral entropy of the mesial recordings.     

Precise Calculation of a Bond Percolation Transition and Survival Rates of Nodes in a Complex Network

Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition.     

基于多目标评价方法的乳腺癌易感基因排序及其网络表达研究

目的利用已有的研究结果和数据,采用多目标评价方法建立乳腺癌易感基因评价模型,对与已知乳腺癌基因关系密切的其它基因进行分析和排序,并给出结果的网络表达模式。方法通过分析已有的文献,并利用有关的基因数据库和已有文献中的数据,提炼出乳腺癌易感基因的多目标评价体系,构建基于加权和法的乳腺癌易感基因评价模型,并利用Cytoscape软件进行评价结果计算和评价结果的网络模式表达。结果利用多目标模型所得到的评价结果,与已有的研究结果一致。其中,乳腺癌易感基因TopBP1排名第二,已知乳腺癌候选易感基因HMMR排名第六。结论文章提出的多目标评价模型能够准确评价被选基因与乳腺癌易感性之间的关系,所提出的评价方法与相关软件结合使用,将成为癌症易感基因研究方面有效的分析方法和途径。     

Estimating a Markovian Epidemic Model Using Household Serial Interval Data from the Early Phase of an Epidemic

The clinical serial interval of an infectious disease is the time between date of symptom onset in an index case and the date of symptom onset in one of its secondary cases. It is a quantity which is commonly collected during a pandemic and is of fundamental importance to public health policy and mathematical modelling. In this paper we present a novel method for calculating the serial interval distribution for a Markovian model of household transmission dynamics. This allows the use of Bayesian MCMC methods, with explicit evaluation of the likelihood, to fit to serial interval data and infer parameters of the underlying model. We use simulated and real data to verify the accuracy of our methodology and illustrate the importance of accounting for household size. The output of our approach can be used to produce posterior distributions of population level epidemic characteristics.     

Perfusion Network Shift during Seizures in Medial Temporal Lobe Epilepsy

Background

Medial temporal lobe epilepsy (MTLE) is associated with limbic atrophy involving the hippocampus, peri-hippocampal and extra-temporal structures. While MTLE is related to static structural limbic compromise, it is unknown whether the limbic system undergoes dynamic regional perfusion network alterations during seizures. In this study, we aimed to investigate state specific (i.e. ictal versus interictal) perfusional limbic networks in patients with MTLE.

Methods

We studied clinical information and single photon emission computed tomography (SPECT) images obtained with intravenous infusion of the radioactive tracer Technetium- Tc 99 m Hexamethylpropyleneamine Oxime (Tc-99 m HMPAO) during ictal and interictal state confirmed by video-electroencephalography (VEEG) in 20 patients with unilateral MTLE (12 left and 8 right MTLE). Pair-wise voxel-based analyses were used to define global changes in tracer between states. Regional tracer uptake was calculated and state specific adjacency matrices were constructed based on regional correlation of uptake across subjects. Graph theoretical measures were applied to investigate global and regional state specific network reconfigurations.

Results

A significant increase in tracer uptake was observed during the ictal state in the medial temporal region, cerebellum, thalamus, insula and putamen. From network analyses, we observed a relative decreased correlation between the epileptogenic temporal region and remaining cortex during the interictal state, followed by a surge of cross-correlated perfusion in epileptogenic temporal-limbic structures during a seizure, corresponding to local network integration.

Conclusions

These results suggest that MTLE is associated with a state specific perfusion and possibly functional organization consisting of a surge of limbic cross-correlated tracer uptake during a seizure, with a relative disconnection of the epileptogenic temporal lobe in the interictal period. This pattern of state specific shift in metabolic networks in MTLE may improve the understanding of epileptogenesis and neuropsychological impairments associated with MTLE.