Immunizations of Interacting Diseases

Zhou, Shicheng; Shi, Shuyang; Wang, Lin

doi:10.23919/chicc.2018.8482798

Cited by 3 publications

(5 citation statements)

References 15 publications

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“…As we mentioned in the previous section, other epidemics have a certain impact on the current research epidemic [123]. Zhou et al [140] investigated the impact of one disease's immunization on the spread of another disease and found that, under some interaction parameters, an increase in the percentage of one disease's Complexity immunization would lead to the mutual damage of another disease. is phenomenon indicates that the control of one disease may lead to the outbreak of other pathogen.…”

Section: Other Strategiesmentioning

confidence: 99%

A Literature Review of Social Network Analysis in Epidemic Prevention and Control

Wang

Zhang

et al. 2021

Complexity

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Studying the structure and evolution characteristics of social networks is of great significance in assessing and controlling the outbreak of infectious diseases. Therefore, it is necessary to find research trends in this field. In this study, 1,752 documents (2001–2020) related to the relationship between the social network and epidemic published from Scopus, WOS (Web of Science), and CNKI (China National Knowledge Infrastructure) databases were studied to provide a more comprehensive overview of the frontiers of research in this field, including epidemics in social networks, spread of disease, influence of different factors on the spread of the epidemic, prevention and control strategies of the epidemic, and comparison of various strategies. Besides, several new research directions in this field worthy of attention of researchers are discussed.

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Section: Other Strategiesmentioning

confidence: 99%

A Literature Review of Social Network Analysis in Epidemic Prevention and Control

Wang

Zhang

et al. 2021

Complexity

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“…Similar scenario to 'disease supporting spread of awareness and awareness suppressing disease' was also explored in the case of disease and immunization where spread of diseases is modelled over multilayer structure and immunization strategies can enhance them or impair [79] [108]. Immunization can compete with epidemics but, at the same time, epidemics can enhance the dynamics of immunization [59].…”

Section: ) Interaction Between Processesmentioning

confidence: 99%

“…Having said that, some researchers [80] [86] [79] [103] [113] [98] enrich their models by taking into account such external factors as the influence of the media or global immunizations strategies. For example, in [80] and [98] authors simulate the influence of media by creating, in the information layer, an artificial node which is connected to every other node in that layer.…”

Section: ) External Influencementioning

confidence: 99%

“…Zhou [79] simulates the external influence in the form of immunization of important nodes in the network. Another research shows that combined self-protection with external information is an effective strategy to decrease epidemic spreading [103].…”

Section: ) External Influencementioning

confidence: 99%

“…Very interesting effect can be observed in the case of disease and awareness spreading where in some cases, information/awareness spreading is suppressing disease spread-ing, but at the same time disease spread promotes (infected node becomes aware and is able to spread information about the contagion) information/awareness spread [ [105]. Interaction between awareness and epidemics spreading can be observed and modelled with the use of activity driven model [83], risk perceptions [79], or approach that also takes into account individual behaviour where a node can decide whether to communicate with nodes that are sources of information or disease [82].…”

Section: ) Interaction Between Processesmentioning

confidence: 99%

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Interacting Spreading Processes in Multilayer Networks: A Systematic Review

2020

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The world of network science is fascinating and filled with complex phenomena that we aspire to understand. One of them is the dynamics of spreading processes over complex networked structures. Building the knowledge-base in the field where we can face more than one spreading process propagating over a network that has more than one layer is a challenging task, as the complexity comes both from the environment in which the spread happens and from characteristics and interplay of spreads' propagation. As this cross-disciplinary field bringing together computer science, network science, biology and physics has rapidly grown over the last decade, there is a need to comprehensively review the current state-of-the-art and offer to the research community a roadmap that helps to organise the future research in this area. Thus, this survey is a first attempt to present the current landscape of the multi-processes spread over multilayer networks and to suggest the potential ways forward.INDEX TERMS complex networks, information diffusion, multilayer networks, spreading processes

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