Astorga Francisca, Groom Quentin, Shimabukuro Paloma Helena Fernandes, Manguin Sylvie, Noesgaard Daniel, Orrell Thomas, Sinka Marianne, Hirsch Tim, Schigel Dmitry
Facultad de Ciencias, Universidad Mayor, Chile.
Biodiversity Informatics, Meise Botanic Garden, Belgium Nieuwelaan 38, 1860, Meise, Belgium.
One Health. 2023 Jan 18;16:100484. doi: 10.1016/j.onehlt.2023.100484. eCollection 2023 Jun.
The unprecedented generation of large volumes of biodiversity data is consistently contributing to a wide range of disciplines, including disease ecology. Emerging infectious diseases are usually zoonoses caused by multi-host pathogens. Therefore, their understanding may require the access to biodiversity data related to the ecology and the occurrence of the species involved. Nevertheless, despite several data-mobilization initiatives, the usage of biodiversity data for research into disease dynamics has not yet been fully leveraged. To explore current contribution, trends, and to identify limitations, we characterized biodiversity data usage in scientific publications related to human health, contrasting patterns of studies citing the Global Biodiversity Information Facility (GBIF) with those obtaining data from other sources. We found that the studies mainly obtained data from scientific literature and other not aggregated or standardized sources. Most of the studies explored pathogen species and, particularly those with GBIF-mediated data, tended to explore and reuse data of multiple species (>2). Data sources varied according to the taxa and epidemiological roles of the species involved. Biodiversity data repositories were mainly used for species related to hosts, reservoirs, and vectors, and barely used as a source of pathogens data, which was usually obtained from human and animal-health related institutions. While both GBIF- and not GBIF-mediated data studies explored similar diseases and topics, they presented discipline biases and different analytical approaches. Research on emerging infectious diseases may require the access to geographical and ecological data of multiple species. The One Health challenge requires interdisciplinary collaboration and data sharing, which is facilitated by aggregated repositories and platforms. The contribution of biodiversity data to understand infectious disease dynamics should be acknowledged, strengthened, and promoted.
大量生物多样性数据的前所未有的产生一直在为包括疾病生态学在内的广泛学科做出贡献。新发传染病通常是由多宿主病原体引起的人畜共患病。因此,对它们的理解可能需要获取与相关物种的生态学和分布有关的生物多样性数据。然而,尽管有多项数据调动倡议,但生物多样性数据在疾病动态研究中的应用尚未得到充分利用。为了探索当前的贡献、趋势并确定局限性,我们对与人类健康相关的科学出版物中生物多样性数据的使用进行了特征描述,对比了引用全球生物多样性信息设施(GBIF)的研究模式与从其他来源获取数据的研究模式。我们发现,这些研究主要从科学文献和其他未汇总或未标准化的来源获取数据。大多数研究探索病原体物种,特别是那些使用GBIF介导数据的研究,倾向于探索和重用多个物种(>2)的数据。数据源因所涉物种的分类群和流行病学作用而异。生物多样性数据存储库主要用于与宿主、宿主动物和病媒相关的物种,很少用作病原体数据的来源,病原体数据通常从与人类和动物健康相关的机构获取。虽然GBIF介导和非GBIF介导的数据研究都探索了相似的疾病和主题,但它们存在学科偏见和不同的分析方法。对新发传染病的研究可能需要获取多个物种的地理和生态数据。“同一健康”挑战需要跨学科合作和数据共享,而汇总的存储库和平台有助于实现这一点。应认识到、加强并促进生物多样性数据对理解传染病动态的贡献。