Spatio-temporal dynamics of water and faecal borne pathogens in livestock and wildlife populations in Laikipia, Kenya.

新出现的传染病对人类和动物健康构成了全球性挑战。大多数新出现的疾病是由病原体从野生动物传播给牲畜引起的。然而，传播是双向的，既有的疾病回到野生动物中，导致保护危机，然后回到不同地点的牲畜中。包括COVID 19在内的新型病原体从野生动物直接传播（即无媒介）到牲畜和人类是大流行病的主要来源。该项目将评估日益短暂的地表水供应和高密度的动物聚集在稀缺期间对动物健康和疾病传播的影响。通过提出以下问题：在整个研究区域的野生和家养有蹄类动物中，某些确定的未充分研究的病原体的患病率是多少？目标疾病的患病率在不同的属性和季节之间在空间和时间上有何不同？研究疾病传播的潜在空间和时间热点是什么？疾病如何在不同物种和空间之间遗传差异？这些未充分研究的病原体如何影响野生动物和牲畜？过去水资源的变化与全球人类疾病暴发有何关系，以及这如何预测不同气候情景下未来的疾病暴发？该项目采用“一个健康”的方法，将涉及使用许多学科，包括但不限于建模、流行病学、分子生物学、免疫学、寄生虫学和生态学。实地工作将在肯尼亚的莱基皮亚进行，以收集不同季节不同财产的水和粪便样本。这些将通过聚合酶链反应（PCR）进行分子筛选，以确定目标病原体的存在。贝叶斯建模将用于确定病原体丰度在不同属性中的变化，这些属性在可用水源的数量和类型以及野生动物和牲畜之间的不同相互作用以及跨季节之间的不同相互作用方面存在差异，以确定雨季和旱季之间水和资源可用性的变化如何影响病原体存在。预测模型将使我们能够根据这些空间和时间数据预测病原体的潜在存在，从而识别潜在的传播热点（例如，在有限的水源周围）和潜在的关注时间段（例如，干旱时期，动物聚集在剩余的有限资源周围）。然后对PCR产物进行测序，以识别不同的种属和亚种。然后将创建网络，以识别不同的病原体物种和单倍型，以及它们在哪种动物物种，地点和一年中的时间被发现。这些信息将有助于增加对传播动态的了解，以及了解哪些病原体存在于某些地区和物种，为跨物种传播提供证据。虽然对疾病和病原体如何影响人类健康进行了广泛的研究，但动物健康的影响往往被忽视。特别是在野生动物中，许多疾病被认为是无症状的，尽管支持这一点的证据很少。因此，我们可以开始了解动物健康是如何潜在的负面影响，这些病原体通过使用酶联免疫吸附试验（ELISA），旨在确定粪便中的炎症生物标志物的水平。这可以识别对野生动物造成潜在健康影响的病原体，从而影响宿主适应性。最后，该项目将进行一项荟萃分析，研究全球水供应的历史变化和全球人类腹泻疫情。建模将使水的可用性和霍乱暴发之间的模式得以确定，并将能够根据未来的流行病学预测未来人类社区霍乱暴发的预测。

Emerging infectious diseases present a global challenge to human and animal health. Most emerging diseases arise from transmission of disease agents from wildlife to livestock. However, transmission moves both ways, with established diseases moving back into wildlife leading to conservation crises and then back to livestock transformed and in different locations. Direct transmission (i.e. without vectors) of novel pathogens, including COVID19, from wildlife into livestock and humans is the primary source of pandemics. This project will evaluate how increasingly ephemeral surface water availability and high-density animal aggregations during periods of scarcity impacts on animal health and disease transmission. By asking the following questions:What is the prevalence of certain identified understudied pathogens in both wild and domestic ungulates across the study area?How does the prevalence of the target diseases differ across spatially and temporally across properties and seasons?What are potential spatial and temporal hotspots for transmission of the studied diseases?How to diseases differ genetically across species and space? How do these understudied pathogens affect wildlife and livestock?How past changes in water availability relates to human disease outbreaks globally and how this can predict future outbreaks under different climate scenarios?This project employs a One Health approach will involve the use of many disciplines included but not limited to modelling, epidemiology, molecular biology, immunology, parasitology, and ecology. Fieldwork will be undertaken in Laikipia Kenya to collect water and faecal samples from different properties across different seasons. These will be molecularly screened via polymerase chain reaction (PCR) to identify the presence of target pathogens. Bayesian modelling will be used to identify changes in pathogen abundance across properties that differ in the amount and types of water sources available as well as differing interactions between wildlife and livestock as well as across seasons to identify how changing water and resource availability between the wet and dry seasons influence pathogen presence. Predictive models will allow for us to predict the potential presence of pathogens based on this spatial and temporal data allowing for the identification of potential hotspots of transmission (e.g around limited sources of water) and potential time periods of concern (e.g periods of drought where animals aggregate around remaining limited resources). PCR products will then be sequenced allowing for different species and subspecies to be identified. Networks will then be created that identify different species and haplotypes of pathogens and which animal species, locations, and times of year they are found in. This information will help increase understanding of transmission dynamics and which pathogens are present in certain areas and species providing evidence for or against cross species transmissions. Whilst there is often extensive research on how diseases and pathogens affect human health, animal health impacts are often neglected. Especially in wildlife many diseases are considered to be asymptomatic despite evidence supporting this being low. Therefore, we can begin to understand how animal health is potentially negatively affected by these pathogens by using enzyme-linked immunosorbent assays (ELISAs) aimed at identifying levels of inflammatory biomarkers in faeces. This could identify pathogens that are causing underlying health impacts in wild animals and as a result having impacts on host fitness. Finally, this project will undertake a meta-analysis looking at global historical changes in water availability and global human diarrhoeal outbreaks. Modelling will allow patterns between water availability and diarrhoeal outbreaks to be identified and future predictions of diarrhoeal outbreaks in human communities will be able to be predicted based on future rainfal