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Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission
Enteric microparasites like Escherichia coli use multiple transmission pathways to propagate within and between host populations. Characterizing the relative transmission risk attributable to host social relationships and direct physical contact between individuals is paramount for understanding how...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493196/ https://www.ncbi.nlm.nih.gov/pubmed/34754493 http://dx.doi.org/10.1098/rsos.210328 |
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author | Farthing, Trevor S. Dawson, Daniel E. Sanderson, Mike W. Seger, Hannah Lanzas, Cristina |
author_facet | Farthing, Trevor S. Dawson, Daniel E. Sanderson, Mike W. Seger, Hannah Lanzas, Cristina |
author_sort | Farthing, Trevor S. |
collection | PubMed |
description | Enteric microparasites like Escherichia coli use multiple transmission pathways to propagate within and between host populations. Characterizing the relative transmission risk attributable to host social relationships and direct physical contact between individuals is paramount for understanding how microparasites like E. coli spread within affected communities and estimating colonization rates. To measure these effects, we carried out commensal E. coli transmission experiments in two cattle (Bos taurus) herds, wherein all individuals were equipped with real-time location tracking devices. Following transmission experiments in this model system, we derived temporally dynamic social and contact networks from location data. Estimated social affiliations and dyadic contact frequencies during transmission experiments informed pairwise accelerated failure time models that we used to quantify effects of these sociobehavioural variables on weekly E. coli colonization risk in these populations. We found that sociobehavioural variables alone were ultimately poor predictors of E. coli colonization in feedlot cattle, but can have significant effects on colonization hazard rates (p ≤ 0.05). We show, however, that observed effects were not consistent between similar populations. This work demonstrates that transmission experiments can be combined with real-time location data collection and processing procedures to create an effective framework for quantifying sociobehavioural effects on microparasite transmission. |
format | Online Article Text |
id | pubmed-8493196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-84931962021-11-08 Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission Farthing, Trevor S. Dawson, Daniel E. Sanderson, Mike W. Seger, Hannah Lanzas, Cristina R Soc Open Sci Ecology, Conservation and Global Change Biology Enteric microparasites like Escherichia coli use multiple transmission pathways to propagate within and between host populations. Characterizing the relative transmission risk attributable to host social relationships and direct physical contact between individuals is paramount for understanding how microparasites like E. coli spread within affected communities and estimating colonization rates. To measure these effects, we carried out commensal E. coli transmission experiments in two cattle (Bos taurus) herds, wherein all individuals were equipped with real-time location tracking devices. Following transmission experiments in this model system, we derived temporally dynamic social and contact networks from location data. Estimated social affiliations and dyadic contact frequencies during transmission experiments informed pairwise accelerated failure time models that we used to quantify effects of these sociobehavioural variables on weekly E. coli colonization risk in these populations. We found that sociobehavioural variables alone were ultimately poor predictors of E. coli colonization in feedlot cattle, but can have significant effects on colonization hazard rates (p ≤ 0.05). We show, however, that observed effects were not consistent between similar populations. This work demonstrates that transmission experiments can be combined with real-time location data collection and processing procedures to create an effective framework for quantifying sociobehavioural effects on microparasite transmission. The Royal Society 2021-10-06 /pmc/articles/PMC8493196/ /pubmed/34754493 http://dx.doi.org/10.1098/rsos.210328 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Ecology, Conservation and Global Change Biology Farthing, Trevor S. Dawson, Daniel E. Sanderson, Mike W. Seger, Hannah Lanzas, Cristina Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title | Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title_full | Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title_fullStr | Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title_full_unstemmed | Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title_short | Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission |
title_sort | combining epidemiological and ecological methods to quantify social effects on escherichia coli transmission |
topic | Ecology, Conservation and Global Change Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493196/ https://www.ncbi.nlm.nih.gov/pubmed/34754493 http://dx.doi.org/10.1098/rsos.210328 |
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