Common features in spatial livestock disease transmission parameters

The risk of epidemic spread of diseases in livestock poses a threat to animal and often also human health. Important for the assessment of the effect of control measures is a statistical model quantification of between-farm transmission during epidemics. In particular, quantification of the between-...

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Bibliographic Details
Published in:Scientific reports 2023-03, Vol.13 (1), p.3550-3550, Article 3550
Main Authors: Boender, Gert Jan, Hagenaars, Thomas J.
Format: Article
Language:English
Subjects:
631/114/2397
631/114/2409
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Animal diseases
Animals
City Planning
Disease Outbreaks - veterinary
Disease transmission
Drugs, Generic
Epidemics
Humanities and Social Sciences
Humans
Livestock
Mathematical models
multidisciplinary
Risk assessment
Science
Science (multidisciplinary)
Statistical models
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Summary:The risk of epidemic spread of diseases in livestock poses a threat to animal and often also human health. Important for the assessment of the effect of control measures is a statistical model quantification of between-farm transmission during epidemics. In particular, quantification of the between-farm transmission kernel has proven its importance for a range of different diseases in livestock. In this paper we explore if a comparison of the different transmission kernels yields further insight. Our comparison identifies common features that connect across the different pathogen-host combinations analyzed. We conjecture that these features are universal and thereby provide generic insights. Comparison of the shape of the spatial transmission kernel suggests that, in absence of animal movement bans, the distance dependence of transmission has a universal shape analogous to Lévy-walk model descriptions of human movement patterns. Also, our analysis suggests that interventions such as movement bans and zoning, through their impact on these movement patterns, change the shape of the kernel in a universal fashion. We discuss how the generic insights suggested can be of practical use for assessing risks of spread and optimizing control measures, in particular when outbreak data is scarce.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-30230-w