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Updated: May 3, 2026
08:12
Use of the EpiAirway Model for Characterizing Long-term Host-pathogen Interactions
Published on: September 2, 2011
11.2K
Pathogen population dynamics in agricultural landscapes: the Ddal modelling framework.
Julien Papaïx1, Katarzyna Adamczyk-Chauvat2, Annie Bouvier2
1INRA, UR 1290 BIOGER-CPP, 78850 Thiverval Grignon, France; INRA, UR 341 Mathématiques et Informatique Appliquées, 78350 Jouy-en-Josas, France.
Summary
This study introduces a new metapopulation-based model for landscape epidemiology. It helps assess how agricultural landscape patterns influence disease spread, aiding managers in preventing epidemics.
Area of Science:
- Ecological modeling
- Landscape epidemiology
- Theoretical ecology
Background:
- Current landscape-scale process models often lack practical applicability for managers or a strong theoretical foundation.
- Metapopulation theory offers a robust framework for understanding spatial population dynamics.
Purpose of the Study:
- To develop and present a novel modeling approach for landscape epidemiology grounded in metapopulation concepts.
- To create a tool that integrates realistic landscape structures and pathogen dynamics for practical application.
Main Methods:
- Utilized a landscape simulator to represent field patterns and crop distribution.
- Employed a stage- and space-structured matrix population model for pathogen dynamics.
- Incorporated invasion analysis, stochastic simulation, and sensitivity analysis, treating landscape as an input.
Main Results:
- Demonstrated the model's ability to evaluate the impact of agricultural landscape composition and structure on epidemic development.
- Showcased the integration of theoretical metapopulation dynamics with realistic landscape features.
- Provided a flexible framework adaptable to various organisms beyond the example fungal foliar disease.
Conclusions:
- The proposed metapopulation-based modeling approach effectively bridges theoretical ecology and practical agricultural management.
- Landscape structure and composition can be leveraged to prevent and mitigate disease epidemics.
- The adaptable framework supports diverse applications in landscape epidemiology.
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