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Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission

Authors :
Anna M. Gamża
Thomas J. Hagenaars
Miriam G. J. Koene
Mart C. M. de Jong
Source :
Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Although most infections are transmitted through the environment, the processes underlying the environmental stage of transmission are still poorly understood for most systems. Improved understanding of the environmental transmission dynamics is important for effective non-pharmaceutical intervention strategies. To study the mechanisms underlying environmental transmission we formulated a parsimonious modelling framework including hypothesised mechanisms of pathogen dispersion and decay. To calibrate and validate the model, we conducted a series of experiments studying distance-dependent transmission of Campylobacter jejuni in broilers. We obtained informative simultaneous estimates for all three model parameters: the parameter of C. jejuni inactivation, the diffusion coefficient describing pathogen dispersion, and the transmission rate parameter. The time and distance dependence of transmission in the fitted model is quantitatively consistent with marked spatiotemporal patterns in the experimental observations. These results, for C. jejuni in broilers, show that the application of our modelling framework to suitable transmission data can provide mechanistic insight in environmental pathogen transmission.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.bcab60ab95d9426f8ba7621e441c1a5f
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-38817-z