Data Analysis and Modeling Unit, Department of Veterinary Sciences, University of Torino, Grugliasco, Italy.
Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Teramo, Italy.
PLoS One. 2024 Nov 13;19(11):e0313657. doi: 10.1371/journal.pone.0313657. eCollection 2024.
Animal movements are a key factor in the spread of pathogens. Consequently, network analysis of animal movements is a well-developed and well-studied field. The relationships between animals facilitate the diffusion of infectious agents and, in particular, shared environments and close interactions can facilitate cross-species transmission. Cattle are often the focus of these studies since they are among the most widely distributed and traded species globally. This remains true for Italy as well, but with an important additional consideration. Indeed, another important productive reality in the peninsula is buffalo farming. These farms have an interesting characteristic: approximately two-thirds of them also rear cattle. This coexistence between cattle and buffalo could have an impact on the diffusion of pathogens. Given that buffalo farms are often overlooked in the literature, the primary goal of this work is to investigate the potential consequences of omitting buffalo from cattle network analyses. To investigate this impact, we will focus on Q fever, a disease that can infect both species and is present on the Italian territory and for which the impact of the buffalo population has not been thoroughly studied, and simulate its spread to the farms of both species through compartmental models. Our analysis reveals that despite the significant difference in network sizes, the unique characteristic of Italian buffalo farms makes the buffalo network essential for a comprehensive understanding of bovine disease dynamics in Italy.
动物的运动是病原体传播的关键因素。因此,动物运动的网络分析是一个高度发达和研究充分的领域。动物之间的关系促进了传染病的传播,特别是共同的环境和密切的相互作用可以促进跨物种传播。牛通常是这些研究的焦点,因为它们是全球分布最广和交易量最大的物种之一。意大利也是如此,但有一个重要的额外考虑因素。事实上,半岛上另一个重要的生产现实是水牛养殖。这些农场有一个有趣的特点:大约三分之二的农场也饲养牛。牛和水牛的共存可能会对病原体的传播产生影响。鉴于水牛农场在文献中经常被忽视,这项工作的主要目标是研究从牛网络分析中忽略水牛可能产生的后果。为了研究这种影响,我们将集中研究 Q 热,这是一种可以感染两种物种的疾病,存在于意大利境内,其水牛种群的影响尚未得到彻底研究,并通过隔间模型模拟其在两种物种农场的传播。我们的分析表明,尽管网络规模存在显著差异,但意大利水牛农场的独特特征使得水牛网络对于全面了解意大利牛病动态至关重要。