Epidemic spreading in community networks

Liu, Zonghua; Hu, Bambi

doi:10.1209/epl/i2004-10550-5

Cited by 221 publications

(158 citation statements)

References 30 publications

(29 reference statements)

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“…This research provides vital insight in terms of the efficiency of vaccination under different circumstances, yet empirical networks usually have particular topology properties that require special care. This includes taking into account community structure [170,188,[329][330][331][332], changes in the network structure over time [52,218,[333][334][335][336][337], as well as multilayer properties that are typical for a large plethora of real-world networks [203,231,240,241,[338][339][340][341][342][343][344][345][346][347]. In what follows, we will review vaccination programs that take into account the particular aspects of these properties on various types of networks.…”

Section: Vaccination On Other Types Of Networkmentioning

confidence: 99%

Statistical physics of vaccination

et al. 2016

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Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination-one of the most important preventive measures of modern times-is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

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Section: Vaccination On Other Types Of Networkmentioning

confidence: 99%

Statistical physics of vaccination

et al. 2016

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“…Finally, some details are ignored. For example, a recent study [79] indicates the existence of large fertility differentials between HIV-infected and uninfected women, and some empirical studies show that the social networks have community structure [80,81], which will affect the epidemic dynamics [82,83]. …”

Section: Conclusion and Discussionmentioning

confidence: 99%

Interplay Between Hiv/Aids Epidemics and Demographic Structures Based on Sexual Contact Networks

Bai

Zhou

Wang

2007

Int. J. Mod. Phys. C

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In this article, we propose a network spread model for HIV epidemics, wherein each individual is represented by a node of the transmission network and the edges are the connections between individuals along which the infection may spread. The sexual activity of each individual, measured by its degree, is not homogeneous but obeys a power-law distribution. Due to the heterogeneity of activity, the infection can persistently exist at a very low prevalence, which has been observed in real data but can not be illuminated by previous models with homogeneous mixing hypothesis. Furthermore, the model displays a clear picture of hierarchical spread: In the early stage the infection is adhered to these high-risk persons, and then, diffuses toward low-risk population. The prediction results show that the development of epidemics can be roughly categorized into three patterns for different countries, and the pattern of a given country is mainly determined by the average sex-activity and transmission probability per sexual partner. In most cases, the effect of HIV epidemics on demographic structure is very small. However, for some extremely countries, like Botswana, the number of sex-active people can be depressed to nearly a half by AIDS.

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“…A significant amount of research had been directed towards the epidemic propagation of information in social networks [14,11,12]. In these papers, the information spread is modeled as virus infection in computer networks.…”

Section: Related Workmentioning

confidence: 99%

Modeling the Propagation of Public Perception across Repeated Social Interactions

Bhatia

Khan

Bölöni

2013

Lecture Notes in Computer Science

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Abstract. In this paper we develop an operational, quantitative method for the propagation of public perception. The model is presented as an extension of the culture-sanctioned social metric framework. We use the technique to model an extended version of the Spanish Steps flower selling scam, where a seller manipulates the belief of the clients and the public perception to pressure the clients to buy overpriced flowers.

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Epidemic spreading in community networks

Cited by 221 publications

References 30 publications

Statistical physics of vaccination

Statistical physics of vaccination

Interplay Between Hiv/Aids Epidemics and Demographic Structures Based on Sexual Contact Networks

Modeling the Propagation of Public Perception across Repeated Social Interactions

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