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通过案例研究探索人畜共患相互作用的一种One Health 框架。

A One Health framework for exploring zoonotic interactions demonstrated through a case study.

机构信息

Centre for Food Science and Veterinary Public Health, Clinical Department for Farm Animals and Food System Science, University of Veterinary Medicine Vienna, Vienna, Austria.

Complexity Science Hub, Vienna, Austria.

出版信息

Nat Commun. 2024 Jul 15;15(1):5650. doi: 10.1038/s41467-024-49967-7.

Abstract

The eco-epidemiology of zoonoses is often oversimplified to host-pathogen interactions while findings derived from global datasets are rarely directly transferable to smaller-scale contexts. Through a systematic literature search, we compiled a dataset of naturally occurring zoonotic interactions in Austria, spanning 1975-2022. We introduce the concept of zoonotic web to describe the complex relationships between zoonotic agents, their hosts, vectors, food, and environmental sources. The zoonotic web was explored through network analysis. After controlling for research effort, we demonstrate that, within the projected unipartite source-source network of zoonotic agent sharing, the most influential zoonotic sources are human, cattle, chicken, and some meat products. Analysis of the One Health 3-cliques (triangular sets of nodes representing human, animal, and environment) confirms the increased probability of zoonotic spillover at human-cattle and human-food interfaces. We characterise six communities of zoonotic agent sharing, which assembly patterns are likely driven by highly connected infectious agents in the zoonotic web, proximity to human, and anthropogenic activities. Additionally, we report a frequency of emerging zoonotic diseases in Austria of one every six years. Here, we present a flexible network-based approach that offers insights into zoonotic transmission chains, facilitating the development of locally-relevant One Health strategies against zoonoses.

摘要

人畜共患病的生态流行病学通常被简化为主机-病原体相互作用,而从全球数据集得出的发现很少能够直接转化为较小规模的情况。通过系统的文献搜索,我们编制了一个奥地利自然发生的人畜共患病相互作用数据集,涵盖了 1975 年至 2022 年的数据。我们引入了人畜共患病网络的概念,以描述人畜共患病病原体、其宿主、媒介、食物和环境来源之间的复杂关系。通过网络分析探索了人畜共患病网络。在控制研究力度后,我们证明,在预测的人畜共患病病原体共享的非二分有向源-源网络中,最具影响力的人畜共患病源是人、牛、鸡和一些肉类产品。对“One Health 3- clique”(代表人类、动物和环境的三角形节点集合)的分析证实了在人与牛和人与食物界面上发生人畜共患病溢出的概率增加。我们描述了六种人畜共患病病原体共享的群落,这些群落的组装模式可能是由人畜共患病网络中高度连接的传染性病原体、与人类的接近程度和人为活动驱动的。此外,我们报告了在奥地利新出现的人畜共患病的频率为每六年一次。在这里,我们提出了一种灵活的基于网络的方法,可以深入了解人畜共患病的传播链,有助于制定针对人畜共患病的具有本地相关性的“One Health”策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3846/11250852/af2bf8de886f/41467_2024_49967_Fig1_HTML.jpg

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