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Related Experiment Video

Updated: Jul 16, 2026

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling

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Published on: July 22, 2017

Modelling disease spread and control in networks: implications for plant sciences.

Mike J Jeger¹, Marco Pautasso¹, Ottmar Holdenrieder²

¹Division of Biology, Imperial College London, Wye Campus, Kent TN25 5AH, UK.

The New Phytologist

|March 29, 2007

Summary

Network analysis reveals that pathogen spread is faster in scale-free networks. Targeting highly connected individuals is more effective for disease control than mass immunization.

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Published on: July 4, 2007

Area of Science:

Epidemiology
Network Science
Disease Ecology

Background:

Infectious diseases spread through interconnected systems (natural, technological, social).
Understanding disease dynamics in complex networks is crucial for control.
Network theory is increasingly applied in human and animal health.

Purpose of the Study:

To analyze pathogen spread in complex networks.
To evaluate disease control strategies in different network structures.
To explore the application of network thinking in plant and forest pathology.

Main Methods:

Modeling disease development in scale-free and random networks.
Investigating the impact of network features (clustering, finite size, household structure) on epidemic thresholds.
Analyzing asymmetrical interactions in disease transmission.

Main Results:

Pathogen spread is faster in scale-free networks than random ones, unless high clustering is present.
Scale-free networks theoretically lack an epidemic threshold, but realistic features introduce one.
Asymmetrical interactions influence epidemic dynamics.

Conclusions:

Disease control in scale-free networks should target highly connected individuals.
Network thinking can enhance the study and management of plant and tree diseases, especially in commercial transport systems.