A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
09 12 2022
09 12 2022
Historique:
received:
18
07
2022
accepted:
18
11
2022
entrez:
9
12
2022
pubmed:
10
12
2022
medline:
15
12
2022
Statut:
epublish
Résumé
We compared seven node vaccination strategies in twelve real-world complex networks. The node vaccination strategies are modeled as node removal on networks. We performed node vaccination strategies both removing nodes according to the initial network structure, i.e., non-adaptive approach, and performing partial node rank recalculation after node removal, i.e., semi-adaptive approach. To quantify the efficacy of each vaccination strategy, we used three epidemic spread indicators: the size of the largest connected component, the total number of infected at the end of the epidemic, and the maximum number of simultaneously infected individuals. We show that the best vaccination strategies in the non-adaptive and semi-adaptive approaches are different and that the best strategy also depends on the number of available vaccines. Furthermore, a partial recalculation of the node centrality increases the efficacy of the vaccination strategies by up to 80%.
Identifiants
pubmed: 36494427
doi: 10.1038/s41598-022-24652-1
pii: 10.1038/s41598-022-24652-1
pmc: PMC9734664
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
21355Informations de copyright
© 2022. The Author(s).
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