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.

来自多个学科的科学家，包括野生动植物生物学，公共卫生，兽医寄生虫学和生物医学科学，已经汇编了有关传染病的分布和影响的大量数据，大多数研究都集中在特定位置或单一宿主病原体相互作用上。这大量数据创造了解决紧迫需求的机会，即探索人类和自然生态系统在全球范围内的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，以将来自生态学，保护医学，寄生虫学和计算科学的国际认可的专家汇集在一起​​，以量化和探索病原体生物多样性的全球规模模式的驱动力。参与者将共同努力，以组装前所未有的大小的数据集，包括有关从昆虫到人类的宿主物种中发生的疾病的信息。在机器学习（人工智能）和地理信息系统（GIS）方面的专家的帮助下，他们将努力建立预测模型，这些模型可用于了解传染病的不断变化，并确定人类和野生动植物中新型疾病出现的未来热点。出现感染性疾病，从而从野生动物和野生动物群体中跳动到威胁性的公共健康，围绕着野生动物，围绕着世界，围绕着野生动物，遍布周围的范围。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什么成功地从一种宿主物种转移到另一种宿主物种？野生动植物中病原体生物多样性的热点是否与人类和牲畜中疾病出现的热点相同？为了分享其发现，RCN将开发诸如旨在从高中到研究生的教育水平的网络广播和研讨会之类的教育产品，并将通过夏季研究计划培训来自代表性不足小组的学生。 RCN还将开发和维护全球传染病生物多样性的数据库，并将这些数据自由地提供给学术界和公众。