A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks

Sartori, Fabio; Turchetto, Massimiliano; Bellingeri, Michele; Scotognella, Francesco; Alfieri, Roberto; Nguyen, Ngoc-Kim-Khanh; Trang, Le Thi Ngoc; Nguyen, Quan; Cassi, Davide

doi:10.1038/s41598-022-24652-1

Cited by 16 publications

(10 citation statements)

References 62 publications

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“…Alvarez-Zuzek et al studied disease transmission in multiplex networks by opinion exchanges on vaccination, which concludes that the exchange of views among individuals had an impact on the vaccination rate [17]. Sartori et al explored the effectiveness of vaccination by comparing the vaccination strategies of seven nodes in twelve real-world complex networks [18]. Cremonini et al proposed a new agent group dynamic model of network transmission to study the dynamics of disease transmission [19].…”

Section: Introductionmentioning

confidence: 99%

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

Xie¹,

Huo²,

Zhao³

et al. 2023

Commun. Theor. Phys.

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Disease is a serious threat to human society. Understanding the characteristics of disease transmission is helpful for people to effectively control the disease. In the real life, it is natural to take various measures when people are aware of the disease. In this paper, a novel coupled model considering asymmetric activity is proposed to describe the interactions between information diffusion and disease transmission in multiplex networks. Then, the critical threshold for disease transmission is derived by using the Micro-Markov chain method. Finally, the theoretical results are verified by numerical simulations. The results show that reducing the activity level of individuals in the physical contact layer will have a continuous impact on reducing disease outbreak threshold and suppressing the disease. In addition, the activity level of individuals in the virtual network has little impact on the transmit of the disease. Meanwhile, when individuals are aware of more disease-related information, the higher their awareness of prevention will be, which can effectively inhibit the transmission of disease. Our research results can provide useful reference for the control of disease transmission.

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Section: Introductionmentioning

confidence: 99%

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

Xie¹,

Huo²,

Zhao³

et al. 2023

Commun. Theor. Phys.

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“…Centrality-targeting is one of the spatial strategies used for strategic implementation of disease control interventions and has shown to be superior to risk-targeting when seeking to reduce epidemic contagion, especially in resource-constrained areas affected by epidemics caused by highly transmissible pathogens 61 , 62 , as is the case of FMD and other TADs affecting livestock 63 . For instance, spatial vaccination strategies informed by centrality-based prioritisation have shown to be effective at halting epidemic spread by reducing the size of the largest connected component, total number of individuals infected and the maximum number of simultaneous infections during an outbreak 64 .…”

Section: Discussionmentioning

confidence: 99%

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda

González-Gordon,

Porphyre,

Muwonge

et al. 2023

Sci Rep

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Animal movements are a major driver for the spread of Transboundary Animal Diseases (TADs). These movements link populations that would otherwise be isolated and hence create opportunities for susceptible and infected individuals to meet. We used social network analysis to describe the seasonal network structure of cattle movements in Uganda and unravel critical network features that identify districts or sub-regions for targeted risk-based surveillance and intervention. We constructed weighted, directed networks based on 2019 between-district cattle movements using official livestock mobility data; the purpose of the movement (‘slaughter’ vs. ‘live trade’) was used to subset the network and capture the risks more reliably. Our results show that cattle trade can result in local and long-distance disease spread in Uganda. Seasonal variability appears to impact the structure of the network, with high heterogeneity of node and edge activity identified throughout the seasons. These observations mean that the structure of the live trade network can be exploited to target influential district hubs within the cattle corridor and peripheral areas in the south and west, which would result in rapid network fragmentation, reducing the contact structure-related trade risks. Similar exploitable features were observed for the slaughter network, where cattle traffic serves mainly slaughter hubs close to urban centres along the cattle corridor. Critically, analyses that target the complex livestock supply value chain offer a unique framework for understanding and quantifying risks for TADs such as Foot-and-Mouth disease in a land-locked country like Uganda. These findings can be used to inform the development of risk-based surveillance strategies and decision making on resource allocation. For instance, vaccine deployment, biosecurity enforcement and capacity building for stakeholders at the local community and across animal health services with the potential to limit the socio-economic impact of outbreaks, or indeed reduce their frequency.

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“…Node centrality measures were first developed in social network analysis to identify influential persons in social networks [1,67,68]. Ranking network nodes according to their network structural embedding helps address a Frontiers in Physics frontiersin.org variety of problems in social networks, such as identifying the most influential persons in a friendship network [5], selecting the influential spreaders of news and information [69], and finding the most important nodes for vaccination to halt epidemic spreading, [17,18,70], etc [66]. Many node centrality measures conceived for binary networks were then adapted to rank nodes in WSNs.…”

Section: Measures Of Node Centralitymentioning

confidence: 99%

“…In criminal networks, NR may describe how arresting criminals affects the structure of interpersonal relationships in crime with the aim of developing policies to halt criminal activities [134]. Finally, in social contact networks within which a disease can spread, NR may simulate the effect of node vaccination [18] and quarantine [128] on the spread of the disease.…”

Section: Node Removalmentioning

confidence: 99%

“…Social networks are composed of nodes (individual actors, people, or social organizations within the network) and the links (relationships or interactions) that connect them. Social networks have been used to describe patterns in friendship [5], science collaborations [6], criminal organizations [7,8], and to model spreading dynamics involving, e.g., several real problems of interest, such as information diffusion [9,10], social influence models [11][12][13][14], epidemic spreading [15,16], and vaccination policies [17,18].…”

Section: Introductionmentioning

confidence: 99%

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Considering weights in real social networks: A review

et al. 2023

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Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences.

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A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks

Cited by 16 publications

References 62 publications

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda

Considering weights in real social networks: A review

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