Mathematical understanding of the multi-species biological networks underpinning rabies transmission

“零到30”是一项全球战略计划，旨在到2030年防止人类死于狗传播的狂犬病。我们离实现这一目标还有很长的路要走，因为最近的估计表明，全球每年约有59,000人因狂犬病死亡[95%置信区间（CI）： 25,000-159,200]。除了对人类健康和经济造成影响外，狂犬病疫情还可能对野生动物物种造成毁灭性影响。坦桑尼亚先前的研究表明，尽管野生食肉动物是狂犬病感染的宿主，但家养狗是维持感染所必需的唯一种群。然而，最近来自坦桑尼亚南部地区的结果表明，该地区家养狗的狂犬病疫苗接种水平很高，这可能表明该地区存在另一种维持宿主。本研究的目的是利用数学和统计方法来提高我们对狂犬病病毒多物种传播的生物接触网络的理解。为了实现这一目标，将开发新的多物种确定性和随机模型来表示物种内部和物种之间的狂犬病传播。最初将使用从坦桑尼亚南部8个地区收集的新数据进行参数化，这些数据包括2007-2017年家养动物和野生动物狂犬病病例的详细情况。（数据由格拉斯哥大学生物多样性、动物健康和比较医学研究所Katie Hampson博士和Sarah Cleaveland教授提供）。最大似然方法和贝叶斯马尔可夫链蒙特卡罗（MCMC）方法将用于利用模型结构内数据集的信息进行参数估计。最佳拟合模型将用于确定哪些物种或物种组合在一个区域内充当维持宿主，以及哪些特征允许它们充当维持宿主。此外，该模型将用于探索一个区域内狂犬病灭绝的可能性以及相关的时间尺度和再次出现的可能性。最初将开发模型以反映坦桑尼亚南部的情况，然后将其应用于狂犬病流行的非洲其他地区。

"Zero by 30" is a global strategic plan to prevent human deaths from dog-transmitted rabies by 2030. We are a long way from achieving this goal as recent estimates suggest that approximately 59,000 [95% Confidence Interval (CI): 25,000-159,200] human rabies deaths occur annually globally. As well as their impact on human health and economics, rabies outbreaks can also be devastating for wild animal species. Previous studies from Tanzania suggest that although wild carnivores contribute to the reservoir of rabies infection, domestic dogs are the only population necessary for maintenance of infection. However, recent results from areas of southern Tanzania where levels of rabies vaccination amongst domestic dogs are high, may suggest the presence of an alternative maintenance host in this region. The aim of this study is to use mathematical and statistical methods to improve our understanding of the biological contact networks underpinning the multi-species transmission of rabies virus. To achieve this, novel, multi-species deterministic and stochastic models will be developed to represent rabies transmission both within and between species. These will initially be parameterised using new data collected from 8 regions of southern Tanzania which incorporate details of rabies cases in domestic and wild animals from 2007-2017. (Data provided by Dr Katie Hampson and Professor Sarah Cleaveland, Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow). Maximum likelihood methods and Bayesian Markov Chain Monte Carlo (MCMC) methods will be used for parameter estimation using the information from the data set within the model structure. The best fit model will be used to identify which species or combinations of species are acting as maintenance hosts within a region and which features allow them to act as maintenance hosts. In addition, the model will be used to explore the likelihood of rabies extinction within a region and the associated timescale and potential for re-emergence. Models will initially be developed to reflect a southern Tanzanian setting but then applied to other areas of Africa where rabies is endemic.