ArticleProceedings of the National Academy of Sciences of the United States of America2017
Optimal deployment of resources for maximizing impact in spreading processes.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The coupling process of awareness and disease under the influence of synergistic-hedging effect of information resources.Infectious Disease Modelling · 2026Article
- Observer-Based Source Localization in Tree Infection Networks via Laplace Transforms.Bulletin of mathematical biology · 2026Article
- Detecting bias in algorithms used to disseminate information in social networks and mitigating it using multiobjective optimization.PNAS nexus · 2025Article
- A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks.Scientific reports · 2022Article
- Effects of official information and rumor on resource-epidemic coevolution dynamics.Journal of King Saud University. Computer and information sciences · 2022Article
- Best influential spreaders identification using network global structural properties.Scientific reports · 2021Article
- Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently.Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2021Article
- Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics.Applied mathematics and computation · 2020Article
- TSSCM: A synergism-based three-step cascade model for influence maximization on large-scale social networks.PloS one · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of "influential spreaders" for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. We show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.
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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.