On the importance of structural equivalence in temporal networks for epidemic forecasting
Abstract Understanding how a disease spreads in a population is a first step to preparing for future epidemics, and machine learning models are a useful tool to analyze the spreading process of infectious diseases. For effective predictions of these spreading processes, node embeddings are used to e...
Main Authors: | Pauline Kister, Leonardo Tonetto |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-01-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-28126-w |
Similar Items
-
Network structure indexes to forecast epidemic spreading in real-world complex networks
by: Michele Bellingeri, et al.
Published: (2022-11-01) -
Epidemic Dynamics in Temporal Clustered Networks with Local-World Structure
by: Wenjun Jing, et al.
Published: (2023-01-01) -
Evaluating structural edge importance in temporal networks
by: Isobel E. Seabrook, et al.
Published: (2021-05-01) -
Temporal prediction of epidemic patterns in community networks
by: Xiao-Long Peng, et al.
Published: (2013-01-01) -
Temporal percolation of the susceptible network in an epidemic spreading.
by: Lucas Daniel Valdez, et al.
Published: (2012-01-01)