RCN Proposal: Macroecology of Infectious Disease

RCN 提案：传染病宏观生态学

• 批准号: 1316223
• 负责人: Patrick Stephens
• 金额: $ 49.95万
• 依托单位: University of Georgia Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1316223&HistoricalAwards=false
• 关键词: RCN; Proposal; Macroecology; Infectious; Disease

Scientists from multiple disciplines, including wildlife biology, public health, veterinary parasitology and biomedical sciences, have compiled a wealth of data on the distribution and impacts of infectious diseases, with most studies focused on particular locations or single host-pathogen interactions. This wealth of data creates the opportunity to address a pressing need, namely to explore the patterns and drivers of infectious disease emergence in humans and natural ecosystems at global scales. This project will create a Research Coordination Network to bring together internationally recognized experts from ecology, conservation medicine, parasitology and computational sciences to quantify and explore the drivers of global scale patterns of pathogen biodiversity. Participants will work together to assemble data sets of unprecedented size, including information about disease occurrence in host species ranging from insects to humans. With help from experts in machine learning (artificial intelligence) and geographic information systems (GIS), they will work to build predictive models that can be used to understand the changing distributions of infectious diseases and identify future hotspots of novel disease emergence in humans and wildlife.Emerging infectious diseases, especially those that jump from wildlife to livestock and humans, threaten public health around the world. Using state of the art computational methods, the RCN will be able to answer critical questions such as: How and why do certain pathogens successfully move from one host species to another? Are hotspots of pathogen biodiversity in wildlife the same areas as hotspots of disease emergence in humans and livestock? To share its findings, the RCN will develop educational products such as webcasts and workshops aimed at educational levels from high school to post graduate, and will train students from under-represented groups through a summer research program. The RCN will also develop and maintain databases of global infectious disease biodiversity and make these data freely available to the academic community and the general public.

来自野生动物生物学、公共卫生、兽医寄生虫学和生物医学等多个学科的科学家收集了有关传染病分布和影响的大量数据，其中大多数研究集中在特定地点或单一宿主与病原体的相互作用。这些丰富的数据创造了解决紧迫需求的机会，即探索全球范围内人类和自然生态系统中传染病出现的模式和驱动因素。该项目将创建一个研究协调网络，汇集来自生态学、保护医学、寄生虫学和计算科学的国际公认专家，以量化和探索病原体生物多样性全球规模模式的驱动因素。参与者将共同努力收集规模空前的数据集，包括从昆虫到人类等宿主物种中疾病发生的信息。在机器学习（人工智能）和地理信息系统（GIS）专家的帮助下，他们将致力于建立预测模型，可用于了解传染病的分布变化并确定人类和野生动物中未来新型疾病出现的热点新出现的传染病，特别是那些从野生动物传染给牲畜和人类的传染病，威胁着世界各地的公共健康。使用最先进的计算方法，RCN 将能够回答关键问题，例如：某些病原体如何以及为何成功地从一种宿主物种转移到另一种宿主物种？野生动物中病原体生物多样性的热点地区是否与人类和牲畜疾病出现的热点地区相同？为了分享其研究结果，RCN 将开发教育产品，例如针对高中到研究生教育水平的网络广播和研讨会，并将通过夏季研究计划培训来自代表性不足群体的学生。 RCN还将开发和维护全球传染病生物多样性数据库，并将这些数据免费提供给学术界和公众。