ArticleJournal of theoretical biology2016
A biologically inspired immunization strategy for network epidemiology.
Article in Journal of theoretical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 19 citations in OpenAlex.
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- Alternating lysis and lysogeny is a winning strategy in bacteriophages due to Parrondo's paradox.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Optimizing targeted vaccination across cyber-physical networks: an empirically based mathematical simulation study.Journal of the Royal Society, Interface · 2018Article
- The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.BMC bioinformatics · 2017Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Well-known immunization strategies, based on degree centrality, betweenness centrality, or closeness centrality, either neglect the structural significance of a node or require global information about the network. We propose a biologically inspired immunization strategy that circumvents both of these problems by considering the number of links of a focal node and the way the neighbors are connected among themselves. The strategy thus measures the dependence of the neighbors on the focal node, identifying the ability of this node to spread the disease. Nodes with the highest ability in the network are the first to be immunized. To test the performance of our method, we conduct numerical simulations on several computer-generated and empirical networks, using the susceptible-infected-recovered (SIR) model. The results show that the proposed strategy largely outperforms the existing well-known strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.