Effects of two channels on explosive information spreading

Wu, Jiao; Zheng, Muhua; Xu, Ke; Gu, Changgui

doi:10.1007/s11071-019-05427-2

Cited by 20 publications

(11 citation statements)

References 42 publications

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“…First it predicts a broad range of conditions -the mutated phase -in which a sub-pandemic pathogen can gain prevalence. On top of that, it also predicts that this phase exhibits a discontinuous transition, characterized by hysteresis, a phenomenon unobserved in the classic SIS dynamics, yet congruent with other models 38,41,[45][46][47][48][49] that incorporate feedback between a pathogen's prevalence (ρ(t)) and its potency (R i (t)). These two observations have direct implications on mitigation:…”

Section: The Mutated Phasesupporting

confidence: 76%

Epidemic spreading under pathogen evolution

Zhang¹,

Ruan²,

Zheng³

et al. 2021

Preprint

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Battling a widespread pandemic is an arms race between our mitigation efforts, e.g., social distancing or vaccination, and the pathogen's evolving persistence. This is being observed firsthand during the current COVID-19 crisis, as novel mutations are constantly challenging our global vaccination race. To address this, we introduce here a general framework for epidemic spreading under pathogen evolution, which shows that mutations can fundamentally alter the projection of the spread. Specifically, we detect a new pandemic phase - the mutated phase - in which, despite the fact that the pathogen is initially non-pandemic (R0 < 1), it may still spread due to the emergence of a critical mutation. The boundaries of this phase portray a balance between the epidemic and the evolutionary time-scales. If the mutation rate is too low, the pathogen prevalence decays prior to the appearance of a critical mutation. On the other hand, if mutations are too rapid, the pathogen evolution becomes volatile and, once again, it fails to spread. Between these two extremes, however, a broad range of conditions exists in which an initially sub-pandemic pathogen will eventually gain prevalence. This is especially relevant during vaccination, which creates, as it progresses, increasing selection pressure towards vaccine-resistance. To overcome this, we show that vaccination campaigns must be accompanied by fierce mitigation efforts, to suppress the potential rise of a resistant mutant strain.

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Section: The Mutated Phasesupporting

confidence: 76%

Epidemic spreading under pathogen evolution

Zhang¹,

Ruan²,

Zheng³

et al. 2021

Preprint

Self Cite

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“…To quantify the impact of college students' mental health on their social relationships in school, we collected data from 4955 freshmen in a college, including the SCL-90 Assessment Scale (hereafter referred to as the SCL-90 form) of 20188 swipe-card data in October [21][22][23][24][25][26][27][28][29][30][31]2018. e data used in the article, which could only be used for statistical analysis to obtain certain macrostatistical characteristics, were all processed through anonymization; hence, it is impossible to identify specific students.…”

Section: Data Descriptionsmentioning

confidence: 99%

“…It was found that the smaller the average, the higher the difference in the spread of information on regular and random networks. Because of the limited risk of redundant information to eliminate the propagation [28], Wu et al [29][30][31] further analyzed information propagation on multilayered social networks based on the theory of edge division [32]. During the dissemination process, it was found that the multilayer network structure is comparatively more conducive to information dissemination.…”

Section: Introductionmentioning

confidence: 99%

Influence of Student Depression on the Spread of Public Opinion in University

Nie

Yang

Wei-min

et al. 2020

Discrete Dynamics in Nature and Society

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In this study, we examined the impact of college students’ mental health on their social behavior. A social network was identified based on the behavior of college students sharing a meal. We analyzed the impact of depression on the structure of this network and found that students without obvious depressive symptoms, based on the test data of the SCL-90 Assessment Scale, were better at socializing than students with obvious depressive symptoms. We proposed a public opinion spreading model on social networks and formulated a heterogeneous mean-field theory to describe it. Further, using computer simulation experiments, we studied the impact of students’ mental health on the process of information propagation in college. The results of the experiments showed that students without obvious depressive symptoms were more likely to receive information than students with obvious depressive symptoms. Based on the results of our study, college psychological consultants can actively identify students who may be at risk of mental illness and give them attention and guidance.

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“…erefore, understanding the dynamics of epidemic spreading and determining an efficient strategy to contain a pandemic have attracted considerable attention in complex networks [1]. Various factors and effects have been discussed, from the network topology and competition between viruses to human behavior and robustness of the health system [2][3][4][5][6][7][8][9][10][11][12]. With the rapid development of modern techniques, the pattern of epidemic spreading has also changed.…”

Section: Introductionmentioning

confidence: 99%

Coevolving Dynamics between Epidemic and Information Spreading considering the Dependence between Vigilance and Awareness Prevalence

Zhang

Lü

et al. 2021

Complexity

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It has been demonstrated that the propagation of information and awareness regarding a disease can assist in containing the outbreak of epidemics. Previous models for this coevolving usually introduced the dependence between these two processes by setting a lower but time-independent infection rate for individuals with awareness. However, a realistic scenario can be more complicated, as individual vigilance and the adopted protective measures may depend on the extent of the discussion on the disease, whereas individuals may be irrational or lack relevant knowledge, leading to improper measures being taken. These can introduce a time-varying dependence between epidemic dynamics and awareness prevalence and may weaken the effect of spreading awareness in containing a pandemic. To better understand this effect, we introduce a nonlinear dependence of the epidemic infection rate on awareness prevalence, focusing on the effect of different forms of dependence on the coevolving dynamics. We demonstrate that a positive correlation between vigilance and awareness prevalence can enhance the effect of information spreading in suppressing epidemics. However, this enhancement can be weakened if some individuals are irrational. Our results demonstrate the importance of rational behavior in the strategy of containing epidemics by propagation of disease information.

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Effects of two channels on explosive information spreading

Cited by 20 publications

References 42 publications

Epidemic spreading under pathogen evolution

Epidemic spreading under pathogen evolution

Influence of Student Depression on the Spread of Public Opinion in University

Coevolving Dynamics between Epidemic and Information Spreading considering the Dependence between Vigilance and Awareness Prevalence

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