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Inferring the origin of an epidemic with a dynamic message-passing algorithm
Open accessAbstract
We study the problem of estimating the origin of an epidemic outbreak: given a contact network and a snapshot of epidemic spread at a certain time, determine the infection source. This problem is important in different contexts of computer or social networks. Assuming that the epidemic spread follows the usual susceptible-infected-recovered model, we introduce an inference algorithm based on dynamic message-passing equations and we show that it leads to significant improvement of performance compared to existing approaches. Importantly, this algorithm remains efficient in the case where the snapshot sees only a part of the network.
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Cited by
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
The Hidden Geometry of Complex, Network-Driven Contagion Phenomena
Brockmann, D., & Helbing, D. (2013) · Science · doi:10.1126/science.1245200 · Cited by 1,253
Dynamics of information diffusion and its applications on complex networks
Zhang, Z.-K., Liu, C., Zhan, X.-X., Lu, X., Zhang, C.-X., & Zhang, Y.-C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.07.002 · Cited by 484
Metadata
- Authors
- Lokhov, A. Y., Mézard, M., Ohta, H., & Zdeborová, L.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2014-07-01
- Volume
- 90
- Issue
- 1
- Pages
- 012801-012801
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2011014734
- Cited by
- 322
- References
- 0
- FWCI
- 19.12
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Inferring the origin of an epidemic with a dynamic message-passing algorithm. https://app.cochat.ai/papers/10.1103/physreve.90.012801
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- Lokhov, A. Y., Mézard, M., Ohta, H., & Zdeborová, L. (2014). Inferring the origin of an epidemic with a dynamic message-passing algorithm. Physical Review E. https://doi.org/10.1103/physreve.90.012801
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