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Common features in spatial livestock disease transmission parameters
Gert Jan Boender1, Thomas J Hagenaars2
1Wageningen Bioveterinary Research, P.O. Box 65, 8200 AB, Lelystad, The Netherlands. gertjan.boender@wur.nl.
Scientific Reports
|March 2, 2023
Summary
Disease spread in livestock threatens animal and human health. This study reveals universal patterns in livestock disease transmission, aiding control measure optimization even with limited outbreak data.
Area of Science:
- Epidemiology
- Veterinary Science
- Mathematical Modeling
Background:
- Epidemic spread of livestock diseases poses significant risks to animal and human health.
- Statistical modeling of between-farm transmission is crucial for assessing control measure effectiveness.
- Quantifying the between-farm transmission kernel is vital for various livestock diseases.
Purpose of the Study:
- To compare different transmission kernels and identify common, universal features across various pathogen-host combinations.
- To explore the potential for generic insights into livestock disease spread.
- To understand how interventions impact transmission patterns.
Main Methods:
- Comparative analysis of different transmission kernels.
- Statistical modeling to quantify between-farm transmission.
- Exploration of spatial transmission kernel shapes and their relation to animal movement patterns.
Main Results:
- Common features connecting different pathogen-host transmission kernels were identified.
- The spatial transmission kernel's distance dependence, without movement bans, shows a universal shape similar to Lévy-walk models.
- Interventions like movement bans and zoning universally alter the transmission kernel's shape.
Conclusions:
- Identified universal features in livestock disease transmission kernels offer generic insights.
- The shape of the spatial transmission kernel is analogous to human movement patterns (Lévy-walks) in the absence of movement restrictions.
- Understanding these universal patterns can aid in risk assessment and optimizing control strategies, especially when outbreak data is scarce.
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