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Viral Tracing of Genetically Defined Neural Circuitry

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Distinguishing Simple and Complex Contagion Processes on Networks.

Giulia Cencetti¹, Diego Andrés Contreras², Marco Mancastroppa²

¹Fondazione Bruno Kessler, Trento, Italy.

Physical Review Letters

|June 30, 2023

Summary

We developed a new method to distinguish between simple and complex contagion processes by analyzing the order of infection spread on networks. This approach helps identify disease spreading and information diffusion mechanisms with limited data.

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Area of Science:

Network Science
Epidemiology
Sociology

Background:

Contagion processes, such as disease spread or information diffusion, can be simple (one interaction) or complex (multiple interactions).
Distinguishing between these contagion mechanisms using empirical data is challenging.

Purpose of the Study:

To propose a novel strategy for discriminating between simple and complex contagion mechanisms.
To enable identification of contagion types from a single observed spreading event.

Main Methods:

Analyzing the order of node infection in a spreading process.
Correlating infection order with local network topology.
Comparing observed correlations with those predicted for simple contagion, threshold mechanisms, and group interactions.

Main Results:

Different contagion mechanisms exhibit distinct correlations between infection order and local network topology.
The proposed strategy effectively differentiates between simple contagion, threshold-based, and higher-order (group) contagion processes.

Conclusions:

The developed method allows for the identification of contagion mechanisms using limited observational data.
This improves the understanding of various spreading phenomena on networks.