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Linking parasitism to network centrality and the impact of sampling bias in its interpretation
Group living is beneficial for individuals, but also comes with costs. One such cost is the increased possibility of pathogen transmission because increased numbers or frequencies of social contacts are often associated with increased parasite abundance or diversity. The social structure of a group...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677876/ https://www.ncbi.nlm.nih.gov/pubmed/36420133 http://dx.doi.org/10.7717/peerj.14305 |
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author | Xu, Zhihong MacIntosh, Andrew J.J. Castellano-Navarro, Alba Macanás-Martínez, Emilio Suzumura, Takafumi Duboscq, Julie |
author_facet | Xu, Zhihong MacIntosh, Andrew J.J. Castellano-Navarro, Alba Macanás-Martínez, Emilio Suzumura, Takafumi Duboscq, Julie |
author_sort | Xu, Zhihong |
collection | PubMed |
description | Group living is beneficial for individuals, but also comes with costs. One such cost is the increased possibility of pathogen transmission because increased numbers or frequencies of social contacts are often associated with increased parasite abundance or diversity. The social structure of a group or population is paramount to patterns of infection and transmission. Yet, for various reasons, studies investigating the links between sociality and parasitism in animals, especially in primates, have only accounted for parts of the group (e.g., only adults), which is likely to impact the interpretation of results. Here, we investigated the relationship between social network centrality and an estimate of gastrointestinal helminth infection intensity in a whole group of Japanese macaques (Macaca fuscata). We then tested the impact of omitting parts of the group on this relationship. We aimed to test: (1) whether social network centrality –in terms of the number of partners (degree), frequency of interactions (strength), and level of social integration (eigenvector) –was linked to parasite infection intensity (estimated by eggs per gram of faeces, EPG); and, (2) to what extent excluding portions of individuals within the group might influence the observed relationship. We conducted social network analysis on data collected from one group of Japanese macaques over three months on Koshima Island, Japan. We then ran a series of knock-out simulations. General linear mixed models showed that, at the whole-group level, network centrality was positively associated with geohelminth infection intensity. However, in partial networks with only adult females, only juveniles, or random subsets of the group, the strength of this relationship - albeit still generally positive - lost statistical significance. Furthermore, knock-out simulations where individuals were removed but network metrics were retained from the original whole-group network showed that these changes are partly a power issue and partly an effect of sampling the incomplete network. Our study indicates that sampling bias can thus hamper our ability to detect real network effects involving social interaction and parasitism. In addition to supporting earlier results linking geohelminth infection to Japanese macaque social networks, this work introduces important methodological considerations for research into the dynamics of social transmission, with implications for infectious disease epidemiology, population management, and health interventions. |
format | Online Article Text |
id | pubmed-9677876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96778762022-11-22 Linking parasitism to network centrality and the impact of sampling bias in its interpretation Xu, Zhihong MacIntosh, Andrew J.J. Castellano-Navarro, Alba Macanás-Martínez, Emilio Suzumura, Takafumi Duboscq, Julie PeerJ Animal Behavior Group living is beneficial for individuals, but also comes with costs. One such cost is the increased possibility of pathogen transmission because increased numbers or frequencies of social contacts are often associated with increased parasite abundance or diversity. The social structure of a group or population is paramount to patterns of infection and transmission. Yet, for various reasons, studies investigating the links between sociality and parasitism in animals, especially in primates, have only accounted for parts of the group (e.g., only adults), which is likely to impact the interpretation of results. Here, we investigated the relationship between social network centrality and an estimate of gastrointestinal helminth infection intensity in a whole group of Japanese macaques (Macaca fuscata). We then tested the impact of omitting parts of the group on this relationship. We aimed to test: (1) whether social network centrality –in terms of the number of partners (degree), frequency of interactions (strength), and level of social integration (eigenvector) –was linked to parasite infection intensity (estimated by eggs per gram of faeces, EPG); and, (2) to what extent excluding portions of individuals within the group might influence the observed relationship. We conducted social network analysis on data collected from one group of Japanese macaques over three months on Koshima Island, Japan. We then ran a series of knock-out simulations. General linear mixed models showed that, at the whole-group level, network centrality was positively associated with geohelminth infection intensity. However, in partial networks with only adult females, only juveniles, or random subsets of the group, the strength of this relationship - albeit still generally positive - lost statistical significance. Furthermore, knock-out simulations where individuals were removed but network metrics were retained from the original whole-group network showed that these changes are partly a power issue and partly an effect of sampling the incomplete network. Our study indicates that sampling bias can thus hamper our ability to detect real network effects involving social interaction and parasitism. In addition to supporting earlier results linking geohelminth infection to Japanese macaque social networks, this work introduces important methodological considerations for research into the dynamics of social transmission, with implications for infectious disease epidemiology, population management, and health interventions. PeerJ Inc. 2022-11-18 /pmc/articles/PMC9677876/ /pubmed/36420133 http://dx.doi.org/10.7717/peerj.14305 Text en ©2022 Xu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Animal Behavior Xu, Zhihong MacIntosh, Andrew J.J. Castellano-Navarro, Alba Macanás-Martínez, Emilio Suzumura, Takafumi Duboscq, Julie Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title | Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title_full | Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title_fullStr | Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title_full_unstemmed | Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title_short | Linking parasitism to network centrality and the impact of sampling bias in its interpretation |
title_sort | linking parasitism to network centrality and the impact of sampling bias in its interpretation |
topic | Animal Behavior |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677876/ https://www.ncbi.nlm.nih.gov/pubmed/36420133 http://dx.doi.org/10.7717/peerj.14305 |
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