On The Epidemic Spread Using Spline Tie-Decay Network Model
Keywords:
Temporal networks, Spline tie-decay networks, SIR dynamicsAbstract
Standard epidemic compartmental models often overlook the evolving nature of inter-personal contact by assuming static interactions. To address this, we propose a deterministic SIR model driven by a spline tie-decay network, in which nodes represent individuals whose interactions (edge weights) gradually increase upon the arrivals of contact events under a cubic spline polynomial, followed by an exponential decay. This mechanism allows a flexible and realistic delay in how tie strength develops and fades over time. Here, the infection rate is dynamically computed as the sum of edge weights over the number of individuals squared, reflecting the state of the system without aggregating events into large time windows. In particular, this work highlights the importance of fine-grained temporal modeling in understanding and predicting disease spread dynamics.References
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