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Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission
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 interventio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415373/ https://www.ncbi.nlm.nih.gov/pubmed/37563156 http://dx.doi.org/10.1038/s41598-023-38817-z |
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author | Gamża, Anna M. Hagenaars, Thomas J. Koene, Miriam G. J. de Jong, Mart C. M. |
author_facet | Gamża, Anna M. Hagenaars, Thomas J. Koene, Miriam G. J. de Jong, Mart C. M. |
author_sort | Gamża, Anna M. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10415373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104153732023-08-12 Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission Gamża, Anna M. Hagenaars, Thomas J. Koene, Miriam G. J. de Jong, Mart C. M. Sci Rep Article 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. Nature Publishing Group UK 2023-08-10 /pmc/articles/PMC10415373/ /pubmed/37563156 http://dx.doi.org/10.1038/s41598-023-38817-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Gamża, Anna M. Hagenaars, Thomas J. Koene, Miriam G. J. de Jong, Mart C. M. Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title | Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title_full | Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title_fullStr | Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title_full_unstemmed | Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title_short | Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
title_sort | combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415373/ https://www.ncbi.nlm.nih.gov/pubmed/37563156 http://dx.doi.org/10.1038/s41598-023-38817-z |
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