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A fast algorithm for calculating an expected outbreak size on dynamic contagion networks.

Jessica Enright¹, Rowland R Kao²

¹Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, United Kingdom.

|July 6, 2016

Summary

This summary is machine-generated.

We developed an efficient method to calculate expected outbreak size on dynamic contact networks. This approach models disease spread forward in time, offering a faster alternative to traditional simulations.

Keywords:

Contagion on networks Network modelling

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Area of Science:

Epidemiology
Network Science
Computational Biology

Background:

Calculating expected outbreak size is crucial for epidemiological studies.
Traditional simulation methods are computationally intensive.
Modeling dynamically changing networks presents challenges.

Purpose of the Study:

To develop an efficient exact method for calculating expected outbreak size.
To model contagion spread on outbreak-invariant, directed, and acyclic networks.
To provide a computationally feasible alternative to intensive simulations.

Main Methods:

Developed an efficient exact algorithm for expected outbreak size calculation.
Applied the method to outbreak-invariant networks (directed and acyclic).
Algorithm described using pseudocode for clarity.

Main Results:

The proposed method efficiently calculates expected outbreak size.
Demonstrated the algorithm's utility on disease-relevant, data-derived networks.
The method allows modeling of dynamically changing networks.

Conclusions:

The new algorithm provides an efficient and exact method for epidemiological modeling.
This approach is suitable for networks where contagion travels forward in time.
The method offers a valuable tool for understanding disease dynamics in complex contact structures.