Quantitative effects of network connectivity on epidemics

2020 ◽  
Vol 34 (28) ◽  
pp. 2050262
Author(s):  
Zhenzhen Liu ◽  
Xiaoke Xu ◽  
Jianyun Zhou
Keyword(s):  
Early Stage ◽  
Network Connectivity ◽  
Transmission Dynamics ◽  
Spreading Speed ◽  
Connection Strength ◽  
Epidemic Spreading ◽  
Infection Transmission ◽  
Rich Club ◽  
Node Connectivity ◽  
Disease Diffusion

Epidemics are affected by the connectivity of nodes in networks in addition to the cooperation of infection transmission. We investigate quantitatively the effects of node connectivity on transmission dynamics by comparing epidemic diffusion in null models with gradual connection strength. Results show that: (1) the inhomogeneity of network connectivity accelerates the spreading of epidemics, this phenomenon is more significant in the early stage of propagation; (2) the enhancement of connectivity of homogenous nodes restrains epidemic spreading, and the spreading speed correlates negatively with connection strength; (3) the spreading speed of epidemics does not change linearly with the strength of rich-club property, which means that the connectivity among hub nodes does not appreciably affect disease diffusion.

scholarly journals Alzheimer’s Disease Projection From Normal to Mild Dementia Reflected in Functional Network Connectivity: A Longitudinal Study

2021 ◽  
Vol 14 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Robyn L. Miller ◽  
Zening Fu ◽  
Yuhui Du ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Early Stage ◽  
Network Connectivity ◽  
Functional Network ◽  
Normal Brain ◽  
Whole Brain ◽  
Mild Dementia ◽  
Sensorimotor Network ◽  
Functional Network Connectivity ◽  
The Brain

BackgroundAlzheimer’s disease (AD) is the most common age-related problem and progresses in different stages, including mild cognitive impairment (early stage), mild dementia (middle-stage), and severe dementia (late-stage). Recent studies showed changes in functional network connectivity obtained from resting-state functional magnetic resonance imaging (rs-fMRI) during the transition from healthy aging to AD. By assuming that the brain interaction is static during the scanning time, most prior studies are focused on static functional or functional network connectivity (sFNC). Dynamic functional network connectivity (dFNC) explores temporal patterns of functional connectivity and provides additional information to its static counterpart.MethodWe used longitudinal rs-fMRI from 1385 scans (from 910 subjects) at different stages of AD (from normal to very mild AD or vmAD). We used group-independent component analysis (group-ICA) and extracted 53 maximally independent components (ICs) for the whole brain. Next, we used a sliding-window approach to estimate dFNC from the extracted 53 ICs, then group them into 3 different brain states using a clustering method. Then, we estimated a hidden Markov model (HMM) and the occupancy rate (OCR) for each subject. Finally, we investigated the link between the clinical rate of each subject with state-specific FNC, OCR, and HMM.ResultsAll states showed significant disruption during progression normal brain to vmAD one. Specifically, we found that subcortical network, auditory network, visual network, sensorimotor network, and cerebellar network connectivity decrease in vmAD compared with those of a healthy brain. We also found reorganized patterns (i.e., both increases and decreases) in the cognitive control network and default mode network connectivity by progression from normal to mild dementia. Similarly, we found a reorganized pattern of between-network connectivity when the brain transits from normal to mild dementia. However, the connectivity between visual and sensorimotor network connectivity decreases in vmAD compared with that of a healthy brain. Finally, we found a normal brain spends more time in a state with higher connectivity between visual and sensorimotor networks.ConclusionOur results showed the temporal and spatial pattern of whole-brain FNC differentiates AD form healthy control and suggested substantial disruptions across multiple dynamic states. In more detail, our results suggested that the sensory network is affected more than other brain network, and default mode network is one of the last brain networks get affected by AD In addition, abnormal patterns of whole-brain dFNC were identified in the early stage of AD, and some abnormalities were correlated with the clinical score.

scholarly journals The effect of heterogeneous infectious period and contagiousness on the dynamics ofSalmonellatransmission in dairy cattle

2008 ◽  
Vol 136 (11) ◽  
pp. 1496-1510 ◽  
Author(s):  
C. LANZAS ◽  
S. BRIEN ◽  
R. IVANEK ◽  
Y. LO ◽  
P. P. CHAPAGAIN ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
Infectious Period ◽  
Specific Group ◽  
Infection Transmission ◽  
Force Of Infection ◽  
The Impact

SUMMARYThe objective of this study was to address the impact of heterogeneity of infectious period and contagiousness onSalmonellatransmission dynamics in dairy cattle populations. We developed three deterministic SIR-type models with two basic infected stages (clinically and subclinically infected). In addition, model 2 included long-term shedders, which were defined as individuals with low contagiousness but long infectious period, and model 3 included super-shedders (individuals with high contagiousness and long infectious period). The simulated dynamics, basic reproduction number (R0) and critical vaccination threshold were studied. Clinically infected individuals were the main force of infection transmission for models 1 and 2. Long-term shedders had a small impact on the transmission of the infection and on the estimated vaccination thresholds. The presence of super-shedders increasesR0and decreases the effectiveness of population-wise strategies to reduce infection, making necessary the application of strategies that target this specific group.

scholarly journals Assessment of Effective Network Connectivity among MEG None Contaminated Epileptic Transitory Events

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Abir Hadriche ◽  
Ichrak Behy ◽  
Amal Necibi ◽  
Abdennaceur Kachouri ◽  
Chokri Ben Amar ◽  
...  
Keyword(s):  
Inverse Problem ◽  
Clinical Performance ◽  
Signal To Noise Ratio ◽  
Statistical Parametric Mapping ◽  
Simulated Data ◽  
Network Connectivity ◽  
Propagation Delay ◽  
Connection Strength ◽  
Advanced Technique ◽  
Epileptiform Discharges

Characterizing epileptogenic zones EZ (sources responsible of excessive discharges) would assist a neurologist during epilepsy diagnosis. Locating efficiently these abnormal sources among magnetoencephalography (MEG) biomarker is obtained by several inverse problem techniques. These techniques present different assumptions and particular epileptic network connectivity. Here, we proposed to evaluate performances of distributed inverse problem in defining EZ. First, we applied an advanced technique based on Singular Value Decomposition (SVD) to recover only pure transitory activities (interictal epileptiform discharges). We evaluated our technique’s robustness in separation between transitory and ripples versus frequency range, transitory shapes, and signal to noise ratio on simulated data (depicting both epileptic biomarkers and respecting time series and spectral properties of realistic data). We validated our technique on MEG signal using detector precision on 5 patients. Then, we applied four methods of inverse problem to define cortical areas and neural generators of excessive discharges. We computed network connectivity of each technique. Then, we confronted obtained noninvasive networks to intracerebral EEG transitory network connectivity using nodes in common, connection strength, distance metrics between concordant nodes of MEG and IEEG, and average propagation delay. Coherent Maximum Entropy on the Mean (cMEM) proved a high matching between MEG network connectivity and IEEG based on distance between active sources, followed by Exact low-resolution brain electromagnetic tomography (eLORETA), Dynamical Statistical Parametric Mapping (dSPM), and Minimum norm estimation (MNE). Clinical performance was interesting for entire methods providing in an average of 73.5% of active sources detected in depth and seen in MEG, and vice versa, about 77.15% of active sources were detected from MEG and seen in IEEG. Investigated problem techniques succeed at least in finding one part of seizure onset zone. dSPM and eLORETA depict the highest connection strength among all techniques. Propagation delay varies in this range [18, 25]ms, knowing that eLORETA ensures the lowest propagation delay (18 ms) and the closet one to IEEG propagation delay.

scholarly journals SARS-CoV-2: Insights from the Immunopathogenesis and Current Clinical Diagnosis and Therapeutic Strategies

2021 ◽  
Vol 5 (2) ◽  
pp. 1-11
Author(s):  
Shruti Sharma ◽  
Ujjawal Sharma ◽  
Anupama Chaudhary ◽  
Manisha Naithani ◽  
Priyanka x Priyanka Naithani ◽  
...  
Keyword(s):  
Early Stage ◽  
Pathological Condition ◽  
Therapeutic Strategies ◽  
Transmission Dynamics ◽  
Present Review ◽  
Global Public Health ◽  
Host Immune Responses ◽  
Therapeutic Regime ◽  
Humoral Responses

The global public health scenario is worsening gradually as the confirmed cases of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections are incessantly escalating with every passing day. The pathological condition caused by SARS-CoV-2 is termed as Coronavirus disease 2019 (COVID-19). The understanding of SARS-CoV-2 transmission dynamics, immunopathogenesis, and the need for early-stage diagnosis and the effective therapeutic regime are the few immediate challenges faced by healthcare professionals worldwide. More specifically, the role of SARS-CoV-2 in the host’s immunopathogenesis response is crucial to determine the disease severity and its clinical outcome in COVID-19 patients. In the present review, we provide insights into the SARS-CoV-2 pathology, host immune responses including innate, cellular, and humoral responses, and immunomodulatory functions of SARS-CoV-2 including cytokine storm and immune evasion. We also shed light upon the present clinical and laboratory-based applications enrolled in the SARS-CoV-2 diagnosis. Taking into consideration the pathogenesis and SARS-CoV-2 immune function, in the present review, we finally provide succinct insights into the SARS-CoV-2 transmission dynamics, immunopathogenesis, with the assessment of the current diagnostic and preventive/ therapeutic strategies.

scholarly journals Genomic epidemiology reveals how restriction measures shaped the SARS-CoV-2 epidemic in Brazil

2021 ◽  
Author(s):  
Marta Giovanetti ◽  
Svetoslav Nanev Slavov ◽  
Vagner Fonseca ◽  
Eduan Wilkinson ◽  
Houriiyah Tegally ◽  
...  
Keyword(s):  
Public Health ◽  
Latin America ◽  
Early Stage ◽  
Virus Transmission ◽  
Transmission Dynamics ◽  
Genomic Epidemiology ◽  
Immunization Strategies ◽  
Adjacent Country ◽  
Time Spread ◽  
Local Transmission

Brazil has experienced some of the highest numbers of COVID-19 infections and deaths globally and made Latin America a pandemic epicenter from May 2021. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of local virus transmission dynamics. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and an adjacent country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed, the absence of effective restriction measures led to the local emergence and international spread of Variants of Concern (VOC) and under monitoring (VUM), including the Gamma (P.1) and Zeta (P.2) variants. In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring and providing a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies.

scholarly journals Unraveling the spatiotemporal spread of COVID-19 in Brazil through spatial network connectivity

2021 ◽  
Author(s):  
Ligia V Barrozo ◽  
Christopher Small
Keyword(s):  
Function Analysis ◽  
Network Connectivity ◽  
Spatial Network ◽  
Orthogonal Function ◽  
Network Transmission ◽  
Geographic Expansion ◽  
Disease Diffusion ◽  
Second Wave ◽  
Full Network ◽  
Spatiotemporal Transmission

Background: Describing and understanding the process of diffusion can allow local managers better plan emergence scenarios. Thus, the main aim of this study was to describe and unveil the spatiotemporal patterns of diffusion of the COVID-19 in Brazil from February 2020 until April 2021. Methods: This is a retrospective purely observational ecologic study including all notified cases and deaths. We used satellite-derived night light imagery and spatiotemporal Empirical Orthogonal Function analysis to quantify the spatial network structure of lighted development and the spatiotemporal transmission of the pathogen through the network. Results: The more populous state capitals within the largest network components presented higher frequency of deaths and earlier onset compared to the increasing numbers of smaller, less populous municipalities trending toward lower frequency of deaths and later onset. By week 48 2020, the full network was almost completely affected. Cases and deaths showed a distinct second wave of wider geographic expansion beginning in early November 2020. Conclusions: The spatiotemporal diffusion in Brazil was characterized by an intertwined process of overseas relocation, hierarchical network transmission and contagious effects. A rapid response as the immediate control of all ports, airports and borders combined with mandatory quarantine are critical to retard disease diffusion.

scholarly journals Connection strength of the macaque connectome augments topological and functional network attributes

2019 ◽  
Vol 3 (4) ◽  
pp. 1051-1069 ◽  
Author(s):  
Siemon C. de Lange ◽  
Dirk Jan Ardesch ◽  
Martijn P. van den Heuvel
Keyword(s):  
Functional Organization ◽  
Kuramoto Model ◽  
Global Network ◽  
Local Network ◽  
Network Clustering ◽  
Connection Strength ◽  
Rich Club ◽  
Specific Distribution ◽  
Binary Network ◽  
Connectivity Strength

Mammalian brains constitute complex organized networks of neural projections. On top of their binary topological organization, the strength (or weight) of these neural projections can be highly variable across connections and is thus likely of additional importance to the overall topological and functional organization of the network. Here we investigated the specific distribution pattern of connection strength in the macaque connectome. We performed weighted and binary network analysis on the cortico-cortical connectivity of the macaque provided by the unique tract-tracing dataset of Markov and colleagues (2014) and observed in both analyses a small-world, modular and rich club organization. Moreover, connectivity strength showed a distribution augmenting the architecture identified in the binary network version by enhancing both local network clustering and the central infrastructure for global topological communication and integration. Functional consequences of this topological distribution were further examined using the Kuramoto model for simulating interactions between brain regions and showed that the connectivity strength distribution across connections enhances synchronization within modules and between rich club hubs. Together, our results suggest that neural pathway strength promotes topological properties in the macaque connectome for local processing and global network integration.

Flat for the Few, Steep for the Many

2010 ◽  
Vol 2 (2) ◽  
pp. 14-28
Author(s):  
Guido Conaldi
Keyword(s):  
Social Network ◽  
Communication Networks ◽  
Open Source Software ◽  
Network Node ◽  
Community Members ◽  
Rich Club ◽  
Node Connectivity ◽  
Hierarchical Communication ◽  
The Many

A discrepancy exists between the emphasis posed by practitioners on decentralized and non-hierarchical communication in Free Libre/Open Source Software (FLOSS) communities and empirical evidence of their hierarchical structure. To explain this paradox, it is hypothesized firstly that in FLOSS communities local sub-groups exist and are less hierarchical, more decentralized than the whole social network. Secondly, it is hypothesized that the bulk of communication exchanges taking place in the community happens inside local sub-groups formed by the most active community members. The recollection that practitioners have of FLOSS communities to which they participate would then be influenced by the position that they occupy inside those sub-groups. A measure of structural cohesion based on network node connectivity is proposed as an effective method to test whether FLOSS communication networks can be decomposed in nested hierarchies of progressively less centralized sub-groups. The recently introduced measure of weighted rich-club effect is adopted to test for the tendency of the most active community members to control communication by interacting more intensely with each other than with other members of the network. Results from a case study that are consistent with the hypotheses are presented and discussed.

scholarly journals Adaptive Rewiring in Non-Uniform Coupled Oscillators

2021 ◽  
pp. 1-40
Author(s):  
MohammadHossein Manuel Haqiqatkhah ◽  
Cees van Leeuwen
Keyword(s):  
Information Processing ◽  
Small World ◽  
Network Evolution ◽  
Memory Storage ◽  
Network Activity ◽  
Stimulus Selection ◽  
Connection Strength ◽  
Rich Club ◽  
Coupling Strengths ◽  
Random Coupling

Abstract Structural plasticity of the brain can be represented in a highly simplified form as adaptive rewiring, the relay of connections according to the spontaneous dynamic synchronization in network activity. Adaptive rewiring, over time, leads from initial random networks to brain-like complex networks, i.e., networks with modular small-world structures and a rich-club effect. Adaptive rewiring has only been studied, however, in networks of identical oscillators with uniform or random coupling strengths. To implement information processing functions (e.g., stimulus selection or memory storage), it is necessary to consider symmetry-breaking perturbations of oscillator amplitudes and coupling strengths. We studied whether non-uniformities in amplitude or connection strength could operate in tandem with adaptive rewiring. Throughout network evolution, either amplitude or connection strength of a subset of oscillators was kept different from the rest. In these extreme conditions, subsets might become isolated from the rest of the network or otherwise interfere with the development of network complexity. However, whereas these subsets form distinctive structural and functional communities, they generally maintain connectivity with the rest of the network and allow the development of network complexity. Pathological development was observed only in a small proportion of the models. These results suggest that adaptive rewiring can robustly operate alongside information processing in biological and artificial neural networks.

scholarly journals Indigenous Women in Scandinavia and a Potential Role for ICT

2011 ◽  
pp. 802-807 ◽  
Author(s):  
Avri Doria ◽  
Maria Uden
Keyword(s):  
Cultural Values ◽  
Communication Networks ◽  
Early Stage ◽  
Local Population ◽  
Solution Space ◽  
Network Connectivity ◽  
Northern Sweden ◽  
Reindeer Herding ◽  
National Agency ◽  
Gender Based

From a distance, the Sámi Network Connectivity initiative (SNC) does not necessarily appear as anything but another technical research project with certain science-fiction (sci-fi) connotations. It is aimed to create Internet connectivity for communications-challenged terrestrial settings using a protocol currently being developed for communications in space. However, while being a highly technical project, SNC emerged from an unexpected setting: an Indigenous women’s initiative to save their traditional livelihood from threats of social and economic drain and to create better opportunities for women and youth to remain within the traditional community. The first step towards the formation of SNC was taken in June 2001 when a group of women reindeer herders in Sirges Sámi Village in Jokkmokk, Norrbotten County in northern Sweden decided to start a gender equality project, Kvinna i sameby (KIS).1 To the Sámi, reindeer herding serves not only as an economic base but also as a foundation for reproduction of cultural values. Already in the KIS planning stage, Susanne Spik, the project leader, contacted the Division for Gender and Technology at Luleå University of Technology (LTU) to invite scientific assistance from the early stage of the project. LTU is the regional technical university for northern Sweden and is situated in the Norrbotten County capital of Luleå 200 km southeast of Jokkmokk. Promoting women’s possibilities to remain in reindeer herding and the traditional Sámi community, especially social and technical conditions for work and business development, were the focus in the discussions. An associated but separately funded project was subsequently formed by LTU researcher Maria Udén. A solution to the project requirements came from a guest researcher at the computer science department, Avri Doria, an Internet systems architect. In spring 2002, after initial discussions with members of the Interplanetary Networking Research Group (IPNRG) at the NASA Jet Propulsion Lab, she contributed the proposal that came to be referred to as Sámi Network Connectivity. With a decision to accept this project, the establishment of SNC as both a technical idea and a concrete gender-based project became a prime goal for the cooperation between the women in Sirges and the scholars at LTU, and continued after the KIS project ended in December 2003. The SNC objective is to provide connectivity where other sources are not available, while making the local population part of the development of the technical system. To develop the technical solution space of SNC, the Sámi Network Connectivity proposition gained research funding from the Swedish national agency for innovation systems, Vinnova, for the period 2004 to 2006. This funding is distributed through the Vinnova program “New communication networks.”

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