Centre for Planetary Health and Food Security, Griffith University, Brisbane, Qld, Australia.
School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, Australia.
J Anim Ecol. 2022 May;91(5):916-932. doi: 10.1111/1365-2656.13634. Epub 2021 Nov 28.
Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogeneous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated. We collected a 13-month dataset of tree-roosting Pteropus spp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree-level measures of abundance and density-the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost level, subplot level, tree level) are predictive of these local density dynamics. Roost-level features were not representative of tree-level abundance (bats per tree) or tree-level density (bats per m or m ), with roost-level models explaining minimal variation in tree-level measures. Total roost abundance itself was either not a significant predictor (tree-level 3D density) or only weakly predictive (tree-level abundance). This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree. Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.
宿主-病原体相互作用模型有助于解释野生动物种群中的感染动态，并预测和减轻人畜共患病溢出的风险。模型的见解本质上取决于宿主之间接触的建模方式，以及至关重要的是，传播与动物密度的关系。蝙蝠是重要的人畜共患病宿主，也是所有哺乳动物中最具群居性的物种之一。它们的种群结构可能高度异质，由不同尺度的生态过程支撑，这使得关于接触和传播性质的假设变得复杂。尽管模型通常使用总丰度的指标来参数化传播，但这是否是宿主-病原体相互作用的生态代表性近似值通常未进行评估。我们收集了来自 8 个栖息地的 2522 个空间参考树木中 13 个月的树栖 Pteropus spp. 数据，以实证评估总栖息地丰度与树木水平丰度和密度的关系 - 最有可能与病毒传播相关的尺度。我们还评估了不同尺度（栖息地水平、子区水平、树木水平）的栖息地特征是否可预测这些局部密度动态。栖息地水平的特征不能代表树木水平的丰度（每棵树上的蝙蝠数量）或树木水平的密度（每米或每立方米的蝙蝠数量），栖息地水平的模型只能解释树木水平测量值的最小变化。总栖息地丰度本身要么不是重要的预测因子（树木水平的 3D 密度），要么只是弱预测因子（树木水平的丰度）。这表明，基本措施，例如栖息地中蝙蝠的总丰度，可能无法为与传播相关的规模的种群动态提供充分的近似值，并且需要替代措施来比较栖息地之间的传播潜力。在最佳候选模型中，对局部种群结构最强的预测因子是栖息地内的树木密度，其中树木密度低的栖息地每棵树上的蝙蝠数量较多，但密度较低（蝙蝠之间的间距更大）。总的来说，这些数据突出了总丰度与局部密度之间不可预测且违反直觉的关系。更细致的蝙蝠传播、传播和溢出建模可能需要替代方法来整合宿主-病原体模型中的接触结构，而不仅仅是修改传播函数。
