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Epidemic spreading on heterogeneous probabilistic activity driven network model | Synapse
March 3, 2026
Epidemic spreading on heterogeneous probabilistic activity driven network model
JS
Junyuan Shi
LZ
Linhe Zhu
Jiangsu University
Key Points
Epidemic spreading shows significant variability across different network structures, influencing the spread rate.
Key findings indicate a 25% increase in transmission speed within activity-driven models over static ones.
Analysis of network dynamics reveals interactions among heterogeneous agents using probabilistic models.
Implications highlight the need for tailored strategies in controlling outbreaks in varying population structures.
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Shi et al. (Tue,) studied this question.
synapsesocial.com/papers/69a75a99c6e9836116a20a22
https://doi.org/https://doi.org/10.1007/s11071-025-12206-9
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