4.6 Article

Using integrated wildlife monitoring to prevent future pandemics through one health approach

期刊

ONE HEALTH
卷 16, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.onehlt.2022.100479

关键词

Anthropogenic imbalances; Disease risk; Host community; Integrated wildlife monitoring; One health; Wildlife health monitoring

向作者/读者索取更多资源

In the context of One Health, Integrated Wildlife Monitoring (IWM) combines wildlife health monitoring (WHM) and host community monitoring to detect emerging infections, examine disease dynamics, and evaluate interventions in complex multi-host and multi-pathogen networks. A nationwide IWM pilot test was conducted in eleven sites representing the habitat diversity of mainland Spain. The results identified differences in biodiversity and host community characteristics among the study sites, with the Eurasian wild boar being the most central species. The study also found a negative relationship between biodiversity and disease risk, although this trend was influenced by specific host community and environmental factors.
In the One Health context, Integrated Wildlife Monitoring (IWM) merges wildlife health monitoring (WHM) and host community monitoring to early detect emerging infections, record changes in disease dynamics, and assess the impact of interventions in complex multi-host and multi-pathogen networks. This study reports the deployment and results obtained from a nationwide IWM pilot test in eleven sites representing the habitat diversity of mainland Spain. In each study site, camera-trap networks and sampling of indicator species for antibody and biomarker analysis were used to generate information. The results allowed identifying differences in biodiversity and host community characteristics among the study sites, with a range of 8 to 19 relevant host species per point. The Eurasian wild boar (Sus scrofa) was the most connected and central species of the host communities, becoming a key target indicator species for IWM. A negative relationship between biodiversity and disease risk was detected, with a lower number and prevalence of circulating pathogens in the sites with more species in the community and larger network size. However, this overall trend was modified by specific hostcommunity and environmental factors, such as the relative index of wild boar - red deer interactions or the proximity to urban habitats, suggesting that human-driven imbalances may favour pathogen circulation. The effort of incorporating wildlife population monitoring into the currently applied WHM programs to achieve effective IWM was also evaluated, allowing to identify population monitoring as the most time-consuming component, which should be improved in the future. This first nationwide application of IWM allowed to detect drivers and hotspots for disease transmission risk among wildlife, domestic animals, and humans, as well as identifying key target indicator species for monitoring. Moreover, anthropogenic effects such as artificially high wildlife densities and urbanisation were identified as risk factors for disease prevalence and interspecific transmission.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据