Rumor Propagation in Temporal Contact Network from Polish Polls

Author(s):  
Andrzej Grabowski ◽  
Andrzej Jarynowski
2018 ◽  
Vol 77 (4) ◽  
pp. 222-229 ◽  
Author(s):  
A. V. Paranin ◽  
A. B. Batrashov

The article compares the results of calculation of the finite element simulation of current and temperature distribution in the scale model of the DC catenary with the data of laboratory tests. Researches were carried on various versions of the structural design of catenary model, reflecting the topological features of the wire connection, characteristic of the DC contact network. The proportions of the cross-sectional area of the scaled model wires are comparable to each other with the corresponding values for real DC catenary. The article deals with the operating conditions of the catenary model in the modes of transit and current collection. When studying the operation of the scale catenary model in the transit mode, the effect of the structural elements on the current distribution and heating of the wires was obtained. Within the framework of the scale model, theoretical assumptions about the current overload of the supporting cable near the middle anchoring have been confirmed. In the current collection mode, the experimental dependences of the current in the transverse wires of the scale model are obtained from the coordinate of the current collection point. Using the model it was experimentally confirmed that in the section of the contact wire with local wear, not only the temperature rise occurs but also the current redistribution due to the smaller cross section. Thus, the current share in other longitudinal wires of the scale model increases and their temperature rises. Scale and mathematical models are constructed with allowance for laboratory clamps and supporting elements that participate in the removal of heat from the investigated wires. Obtained study results of the scale model allow to draw a conclusion about the adequacy of the mathematical model and its correspondence to the real physical process. These conclusions indicate the possibility of applying mathematical model for calculating real catenary, taking into account the uneven contact wear wire and the armature of the contact network.


Author(s):  
Yunpeng Xiao ◽  
Wen Li ◽  
Shuai Qiang ◽  
Qian Li ◽  
Hanchun Xiao ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Charlotte Warembourg ◽  
Guillaume Fournié ◽  
Mahamat Fayiz Abakar ◽  
Danilo Alvarez ◽  
Monica Berger-González ◽  
...  

AbstractFree roaming domestic dogs (FRDD) are the main vectors for rabies transmission to humans worldwide. To eradicate rabies from a dog population, current recommendations focus on random vaccination with at least 70% coverage. Studies suggest that targeting high-risk subpopulations could reduce the required vaccination coverage, and increase the likelihood of success of elimination campaigns. The centrality of a dog in a contact network can be used as a measure of its potential contribution to disease transmission. Our objectives were to investigate social networks of FRDD in eleven study sites in Chad, Guatemala, Indonesia and Uganda, and to identify characteristics of dogs, and their owners, associated with their centrality in the networks. In all study sites, networks had small-world properties and right-skewed degree distributions, suggesting that vaccinating highly connected dogs would be more effective than random vaccination. Dogs were more connected in rural than urban settings, and the likelihood of contacts was negatively correlated with the distance between dogs’ households. While heterogeneity in dog's connectedness was observed in all networks, factors predicting centrality and likelihood of contacts varied across networks and countries. We therefore hypothesize that the investigated dog and owner characteristics resulted in different contact patterns depending on the social, cultural and economic context. We suggest to invest into understanding of the sociocultural structures impacting dog ownership and thus driving dog ecology, a requirement to assess the potential of targeted vaccination in dog populations.


2021 ◽  
pp. 1-15
Author(s):  
V. Indu ◽  
Sabu M. Thampi

Social networks have emerged as a fertile ground for the spread of rumors and misinformation in recent times. The increased rate of social networking owes to the popularity of social networks among the common people and user personality has been considered as a principal component in predicting individuals’ social media usage patterns. Several studies have been conducted to study the psychological factors influencing the social network usage of people but only a few works have explored the relationship between the user’s personality and their orientation to spread rumors. This research aims to investigate the effect of personality on rumor spread on social networks. In this work, we propose a psychologically-inspired fuzzy-based approach grounded on the Five-Factor Model of behavioral theory to analyze the behavior of people who are highly involved in rumor diffusion and categorize users into the susceptible and resistant group, based on their inclination towards rumor sharing. We conducted our experiments in almost 825 individuals who shared rumor tweets on Twitter related to five different events. Our study ratifies the truth that the personality traits of individuals play a significant role in rumor dissemination and the experimental results prove that users exhibiting a high degree of agreeableness trait are more engaged in rumor sharing activities and the users high in extraversion and openness trait restrain themselves from rumor propagation.


Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 22
Author(s):  
Sung Jin Lee ◽  
Sang Eun Lee ◽  
Ji-On Kim ◽  
Gi Bum Kim

In this study, we address the problem originated from the fact that “The Corona 19 Epidemiological Research Support System,” developed by the Korea Centers for Disease Control and Prevention, is limited to analyzing the Global Positioning System (GPS) information of the confirmed COVID-19 cases alone. Consequently, we study a method that the authority predicts the transmission route of COVID-19 between visitors in the community from a spatiotemporal perspective. This method models a contact network around the first confirmed case, allowing the health authorities to conduct tests on visitors after an outbreak of COVID-19 in the community. After securing the GPS data of community visitors, it traces back to the past from the time the first confirmed case occurred and creates contact clusters at each time step. This is different from other researches that focus on identifying the movement paths of confirmed patients by forward tracing. The proposed method creates the contact network by assigning weights to each contact cluster based on the degree of proximity between contacts. Identifying the source of infection in the contact network can make us predict the transmission route between the first confirmed case and the source of infection and classify the contacts on the transmission route. In this experiment, we used 64,073 simulated data for 100 people and extracted the transmission route and a top 10 list for centrality analysis. The contacts on the route path can be quickly designated as a priority for COVID-19 testing. In addition, it is possible for the authority to extract the subjects with high influence from the centrality theory and use them for additional COVID-19 epidemic investigation that requires urgency. This model is expected to be used in the epidemic investigation requiring the quick selection of close contacts.


2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Chris Groendyke ◽  
Adam Combs

Abstract Objectives: Diseases such as SARS-CoV-2 have novel features that require modifications to the standard network-based stochastic SEIR model. In particular, we introduce modifications to this model to account for the potential changes in behavior patterns of individuals upon becoming symptomatic, as well as the tendency of a substantial proportion of those infected to remain asymptomatic. Methods: Using a generic network model where every potential contact exists with the same common probability, we conduct a simulation study in which we vary four key model parameters (transmission rate, probability of remaining asymptomatic, and the mean lengths of time spent in the exposed and infectious disease states) and examine the resulting impacts on various metrics of epidemic severity, including the effective reproduction number. We then consider the effects of a more complex network model. Results: We find that the mean length of time spent in the infectious state and the transmission rate are the most important model parameters, while the mean length of time spent in the exposed state and the probability of remaining asymptomatic are less important. We also find that the network structure has a significant impact on the dynamics of the disease spread. Conclusions: In this article, we present a modification to the network-based stochastic SEIR epidemic model which allows for modifications to the underlying contact network to account for the effects of quarantine. We also discuss the changes needed to the model to incorporate situations where some proportion of the individuals who are infected remain asymptomatic throughout the course of the disease.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gerardo Chowell ◽  
Sushma Dahal ◽  
Raquel Bono ◽  
Kenji Mizumoto

AbstractTo ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.


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