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Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions
Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we de...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862288/ https://www.ncbi.nlm.nih.gov/pubmed/35193675 http://dx.doi.org/10.1186/s13567-022-01031-2 |
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author | Cardenas, Nicolas C. Sykes, Abagael L. Lopes, Francisco P. N. Machado, Gustavo |
author_facet | Cardenas, Nicolas C. Sykes, Abagael L. Lopes, Francisco P. N. Machado, Gustavo |
author_sort | Cardenas, Nicolas C. |
collection | PubMed |
description | Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we describe multi-host contact networks and elucidate the potential of disease spread through farms with multiple hosts. Four years of between-farm animal movement among all farms of a Brazilian state were described through a static and monthly snapshot of network representations. We developed a stochastic multilevel model to simulate scenarios in which infection was seeded into single host and multi-host farms to quantify disease spread potential, and simulate network-based control actions used to evaluate the reduction of secondarily infected farms. We showed that the swine network was more connected than cattle and small ruminants in both the static and monthly snapshots. The small ruminant network was highly fragmented, however, contributed to interconnecting farms, with other hosts acting as intermediaries throughout the networks. When a single host was initially infected, secondary infections were observed across farms with all other species. Our stochastic multi-host model demonstrated that targeting the top 3.25% of the farms ranked by degree reduced the number of secondarily infected farms. The results of the simulation highlight the importance of considering multi-host dynamics and contact networks while designing surveillance and preparedness control strategies against pathogens known to infect multiple species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13567-022-01031-2. |
format | Online Article Text |
id | pubmed-8862288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88622882022-02-23 Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions Cardenas, Nicolas C. Sykes, Abagael L. Lopes, Francisco P. N. Machado, Gustavo Vet Res Research Article Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we describe multi-host contact networks and elucidate the potential of disease spread through farms with multiple hosts. Four years of between-farm animal movement among all farms of a Brazilian state were described through a static and monthly snapshot of network representations. We developed a stochastic multilevel model to simulate scenarios in which infection was seeded into single host and multi-host farms to quantify disease spread potential, and simulate network-based control actions used to evaluate the reduction of secondarily infected farms. We showed that the swine network was more connected than cattle and small ruminants in both the static and monthly snapshots. The small ruminant network was highly fragmented, however, contributed to interconnecting farms, with other hosts acting as intermediaries throughout the networks. When a single host was initially infected, secondary infections were observed across farms with all other species. Our stochastic multi-host model demonstrated that targeting the top 3.25% of the farms ranked by degree reduced the number of secondarily infected farms. The results of the simulation highlight the importance of considering multi-host dynamics and contact networks while designing surveillance and preparedness control strategies against pathogens known to infect multiple species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13567-022-01031-2. BioMed Central 2022-02-22 2022 /pmc/articles/PMC8862288/ /pubmed/35193675 http://dx.doi.org/10.1186/s13567-022-01031-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Cardenas, Nicolas C. Sykes, Abagael L. Lopes, Francisco P. N. Machado, Gustavo Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title | Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title_full | Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title_fullStr | Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title_full_unstemmed | Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title_short | Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
title_sort | multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862288/ https://www.ncbi.nlm.nih.gov/pubmed/35193675 http://dx.doi.org/10.1186/s13567-022-01031-2 |
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