Collaborative Research: Modeling Infectious Diseases: How Much Ecological Complexity Must We Address?

合作研究：传染病建模：我们必须解决多少生态复杂性？

• 批准号: 1115965
• 负责人: Armand Kuris
• 金额: $ 214.94万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1115965&HistoricalAwards=false
• 关键词: Collaborative; Research; Modeling; Infectious; Diseases

Ecology of Infectious Disease Special Competition - Spring 2011Ecological systems are undeniably complex. Evaluating the appropriate level of complexity needed to fully understand their dynamics is essential to more efficiently increase the predictive accuracy of models. With funding through this Grant, this theoretical and empirical research will analyze the benefits of added complexity in host-parasite models and the extent to which including complexity increases the predictive accuracy of dynamical models. The team from the University of California-Santa Barbara and Princeton University will examine the role played by parasites in food webs for 16 estuarine systems along a latitudinal gradient of the Pacific coast of North America. They will model four focal parasites found in these webs and perform laboratory and field studies to parameterize the model. Versions of these models will vary in aspects of ecological complexity, including alternative hosts, other parasites, varying detail about life stages, direct and indirect effects of non-hosts and temperature.The study is innovative and certainly worth of funding. The research will advance understanding of how model performance changes with added complexity and investigate the level of detail needed to address life-stage complexity, alternative host diversity and food web complexity. Examining how model performance improves with complexity and the cost of including that complexity will provide insight on the most appropriate level of complexity needed for infectious disease models to be most suitably predictive. The broader impacts of this project are very strong. The research from this study will provide a framework for how to most effectively model infectious diseases in complex systems and will address how parasites impact ecological networks and surrounding biodiversity. This project will make excellent provision for the training and support of a post-doctoral researcher, graduate students and undergraduates, including individuals from under-represented groups. This study will also feature excellent and very appropriate outreach to K-12 teachers and students and will enhance international scientific collaboration through interaction with scientists and students from Mexico, Czech Republic, Argentina and Australia.

传染病生态学特别比赛-2011年春季生态系统是非常复杂的。为了更有效地提高模型的预测准确性，评估充分理解其动态所需的适当复杂程度至关重要。通过这笔赠款的资助，这项理论和实证研究将分析宿主-寄生虫模型中增加复杂性的好处，以及包括复杂性增加动态模型预测准确性的程度。来自加州大学圣巴巴拉分校和普林斯顿大学的研究小组将研究寄生虫在北美太平洋沿岸纬度梯度沿着16个河口系统的食物网中所起的作用。他们将模拟在这些网络中发现的四种焦点寄生虫，并进行实验室和实地研究以参数化模型。这些模型的版本将在生态复杂性方面有所不同，包括替代宿主，其他寄生虫，生命阶段的不同细节，非宿主和温度的直接和间接影响。该研究将进一步了解模型性能如何随着复杂性的增加而变化，并调查解决生命阶段复杂性，替代宿主多样性和食物网复杂性所需的细节水平。研究模型性能如何随着复杂性的提高而提高，以及包括这种复杂性的成本将提供关于传染病模型最适合预测所需的最合适的复杂性水平的见解。该项目的广泛影响非常强大。这项研究将为如何在复杂系统中最有效地模拟传染病提供一个框架，并将解决寄生虫如何影响生态网络和周围生物多样性的问题。该项目将为培训和支持一名博士后研究员、研究生和本科生，包括代表性不足群体的个人，提供极好的条件。这项研究还将对K-12教师和学生进行出色和非常适当的宣传，并将通过与墨西哥，捷克共和国，阿根廷和澳大利亚的科学家和学生的互动加强国际科学合作。