Cost-efficient vaccination protocols for network epidemiology

Abstract

We investigate methods to vaccinate contact networks -- i.e. removing nodes in such a way that disease spreading is hindered as much as possible -- with respect to their cost-efficiency. Any real implementation of such protocols would come with costs related both to the vaccination itself, and gathering of information about the network. Disregarding this, we argue, would lead to erroneous evaluation of vaccination protocols. We use the susceptible-infected-recovered model -- the generic model for diseases making patients immune upon recovery -- as our disease-spreading scenario, and analyze outbreaks on both empirical and model networks. For different relative costs, different protocols dominate. For high vaccination costs and low costs of gathering information, the so-called acquaintance vaccination is the most cost efficient. For other parameter values, protocols designed for query-efficient identification of the network's largest degrees are most efficient.

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• The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: a mean-field model perspective
• Hyperbolic Mapping of Human Proximity Networks
• Geometric Programming for Optimal Positive Linear Systems
• Group centrality in optimal and suboptimal vaccination for epidemic models in contact networks
• Diffusion on dynamic contact networks with indirect transmission links