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sispread: A software to simulate infectious diseases spreading on contact networks.
F P Alvarez1, P Crépey, M Barthélemy
1INSERM, U707, ESIM, Paris, France. fabian.alvarez@u707.jussieu.fr
Methods of Information in Medicine
|January 17, 2007
Summary
This software simulates infectious disease dynamics on networks, helping to understand outbreak spread and control strategies. It models stochastic factors crucial for realistic epidemic analysis.
Area of Science:
- Epidemiology
- Computational Biology
- Network Science
Background:
- Understanding infectious disease dynamics is crucial for public health.
- Stochastic factors significantly influence epidemic spread in populations.
- Previous models often simplified network structures and disease transmission.
Purpose of the Study:
- To introduce a simulation software for studying infectious disease dynamics on networks.
- To facilitate the analysis of stochastic factors in epidemic evolution.
- To provide tools for network and epidemiological parameter customization.
Main Methods:
- Utilizes three common infectious disease models: SI, SIS, and SIR.
- Supports algorithm-generated networks (scale-free, small-world, random) and external network data.
- Enables simulation of single or multiple outbreaks across networks.
Main Results:
- Standard outputs include disease prevalence evolution (single or averaged outbreaks).
- Allows customized outputs for detailed epidemiological questions.
- Facilitates analysis of disease spread across various network structures.
Conclusions:
- The software models stochasticity in epidemics by simulating outbreaks on contact networks.
- This approach aids in understanding outbreak pathways within communities.
- It supports the design of novel disease prevention and control strategies.
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