Influence of vaccination strategies and topology on the herd immunity of complex networks

Thedchanamoorthy, Gnana; Piraveenan, Mahendra; Uddin, Shahadat; Senanayake, Upul

doi:10.1007/s13278-014-0213-5

Cited by 13 publications

(7 citation statements)

References 29 publications

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“…As clear from the exponential dependence on the k min and β , targeted vaccination strategy based on degree centrality provides a very efficient way to control epidemic spreading. Similar conclusions can be drawn by applying other centrality measures, such as betweenness and k-core centrality, or memberships, for the selection of immunized nodes [9,57,58,59,60,61].…”

Section: Introductionsupporting

confidence: 64%

Control Strategies of Contagion Processes in Time-Varying Networks

Karsai

Perra

2017

Theoretical Biology

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The vast majority of strategies aimed at controlling contagion processes on networks consider a timescale separation between the evolution of the system and the unfolding of the process. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently to the contagion phenomena. Here, we review the most commonly used immunization strategies on networks. In the first part of the chapter, we focus on controlling strategies in the limit of timescale separation. In the second part instead, we introduce results and methods that relax this approximation. In doing so, we summarize the main findings considering both numerical and analytically approaches in real as well as synthetic time-varying networks.

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Section: Introductionsupporting

confidence: 64%

Control Strategies of Contagion Processes in Time-Varying Networks

Karsai

Perra

2017

Theoretical Biology

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“…Some of these approaches to vaccine deployment have previously been tested against one-another (Salathé and Jones, 2010; Thedchanamoorthy et al, 2014; Ventresca and Aleman, 2013). However, there is limited systematic evidence comparing a range of different intervention approaches requiring different levels of resource input, particularly using real-world or real-world-like (i.e.…”

Section: Introductionmentioning

confidence: 99%

Efficient vaccination strategies for epidemic control using network information

et al. 2019

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Background: Network-based interventions against epidemic spread are most powerful when the full network structure is known. However, in practice, resource constraints require decisions to be made based on partial network information. We investigated how the accuracy of network data available at individual and village levels affected network-based vaccination effectiveness. Methods: We simulated a Susceptible-Infected-Recovered process on static empirical social networks from 75 rural Indian villages. First, we used regression analysis to predict the percentage of individuals ever infected (cumulative incidence) based on village-level network properties for simulated datasets from 10 representative villages. Second, we simulated vaccinating 10% of each of the 75 empirical village networks at baseline, selecting vaccinees through one of five network-based approaches: random individuals (Random); random contacts of random individuals (Nomination); random high-degree individuals (High Degree); highest degree individuals (Highest Degree); or most central individuals (Central). The first three approaches require only sample data; the latter two require full network data. We also simulated imposing a limit on how many contacts an individual can nominate (Fixed Choice Design, FCD), which reduces the data collection burden but generates only partially observed networks. Results: In regression analysis, we found mean and standard deviation of the degree distribution to strongly predict cumulative incidence. In simulations, the Nomination method reduced cumulative incidence by one-sixth compared to Random vaccination; full network methods reduced infection by two-thirds. The High Degree approach had intermediate effectiveness. Somewhat surprisingly, FCD truncating individuals’ degrees at three was as effective as using complete networks. Conclusions: Using even partial network information to prioritize vaccines at either the village or individual level, i.e. determine the optimal order of communities or individuals within each village, substantially improved epidemic outcomes. Such approaches may be feasible and effective in outbreak settings, and full ascertainment of network structure may not be required.

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“…a lattice) as is sometimes the case in the literature 15 16 17 . Some real world examples of such networks could be social networks, both online and offline 16 17 18 , contact networks in epidemiological studies where any individual can come into contact with any other individual 19 20 21 22 , or the World Wide Web (WWW) where any website could link to any other website 6 16 , to name a few. In fact, most real world social, biological, and technical networks studied in the literature will fall into this category, where link formation is not constrained by node type 6 16 .…”

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confidence: 99%

Network growth models: A behavioural basis for attachment proportional to fitness

Bell

Perera

Piraveenan

et al. 2017

Sci Rep

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Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example.

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Influence of vaccination strategies and topology on the herd immunity of complex networks

Cited by 13 publications

References 29 publications

Control Strategies of Contagion Processes in Time-Varying Networks

Control Strategies of Contagion Processes in Time-Varying Networks

Efficient vaccination strategies for epidemic control using network information

Network growth models: A behavioural basis for attachment proportional to fitness

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