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This is a Quantitative Study study.

Dynamic propagation and control of a West Nile virus model based on higher-order temporal network structure

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Epidemic model predicts virus spread in birds and humans, suggesting control methods to mitigate outbreaks.

The model shows that higher-order interactions enhance the understanding of disease dynamics within populations and communities.
Results indicate that the conditions for disease equilibrium and Turing instability are influenced by the network's topology.
Analysis utilized numerical simulations to verify the theoretical underpinnings of virus propagation and control strategies.
Findings emphasize the potential of higher-order temporal networks for improving epidemic modeling and guiding public health interventions.

Zhu et al. (2025) studied this question.

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View Full Paper

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Authors

Epidemic model predicts virus spread in birds and humans, suggesting control methods to mitigate outbreaks.

The model shows that higher-order interactions enhance the understanding of disease dynamics within populations and communities.
Results indicate that the conditions for disease equilibrium and Turing instability are influenced by the network's topology.
Analysis utilized numerical simulations to verify the theoretical underpinnings of virus propagation and control strategies.
Findings emphasize the potential of higher-order temporal networks for improving epidemic modeling and guiding public health interventions.

Zhu et al. (2025) studied this question.

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