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Collaborative Research: CIBR: VectorByte: A Global Informatics Platform for studying the Ecology of Vector-Borne Diseases

合作研究：CIBR：VectorByte：研究媒介传播疾病生态学的全球信息学平台

基本信息

批准号：
2016265
负责人：
Sadie Ryan
金额：
$ 43.65万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016265&HistoricalAwards=false
关键词：
Collaborative Research CIBR VectorByte Global

项目摘要

A wide variety of terrestrial plant and animal pathogens have evolved transmission cycles that require vectors, typically arthropods, that transmit the pathogen when it feeds on a host. These vector-borne diseases (VBDs) represent a serious threat to human, animal, and plant health as well as negatively impacting economic welfare worldwide. For example, approximately a third of the human population is at risk for infections transmitted by mosquitoes alone, and vectors transmit many important diseases of plants and livestock. Yearly, VBDs account for 17% of human infectious diseases and billions of dollars in crop and livestock losses. In order to better prevent and predict outbreaks of VBDs, many types of information and data on interactions of vectors with their environments over space and time need to be combined. However, efforts to do this have been hindered by data collected on vectors being isolated, difficult to access, and kept in disparate formats. The main goal of this project is to build a centralized open access data platform called VectorByte. It will contain standardized data on vector traits and population abundance. This will allow data to be more easily shared and used by the disease ecology community and by other interested communities. Further, freely available tools to analyze and model these data will be developed, combined with educational materials, including tutorials on using the databases and data analysis tools. Training early career scientists will be accomplished through workshops and mentoring of postdoctoral researchers, graduate students, and undergraduates within the project. Training workshops covering use of the databases and statistical methods appropriate for the data will target early career scientists from underrepresented groups and regions, as well as practitioners from the broader public health and vector control community. This combined audience will enable feedback from the applied realm about best user practice and will promote collaborative opportunities to bridge between tools developed within the academic community and real world decisions. The platform and training will in turn support research and mathematical modelling efforts that will lead to a better understanding of why outbreaks occur when and where they do and will allow for development and assessment of potential control strategies for these diseases. There is mounting empirical evidence that the traits of vectors vary across time, environmental conditions, and within and between populations. This variation has knock-on effects for the dynamics of vector populations, and therefore also for transmission of vector-borne infections and the efficacy of control strategies. Mathematical and statistical models can be used to better understand the links between traits, populations, and transmission. However, doing this well requires detailed data ranging from laboratory measurements of individual-level traits of vectors to observed population dynamics of the vectors, all of which are often difficult to obtain or use. Further, data for VBD systems are often archived in inconsistent formats and locations. The VectorByte project will develop a user-friendly informatics platform with a global scope for depositing, accessing, and visualizing data in order to fill these gaps for the VBD community. The VectorByte platform has the potential to transform VBD disease research by providing Findable, Accessible, Interoperable, and Reusable (FAIR) data, necessary to build, test, and validate models of VBDs not currently possible with available open data. This project will enable VBD researchers to increase the impact of their data through standardized formatting and centralized location, increasing the sustainability of data while simultaneously increasing the potential for reuse. These data standards will also facilitate comparison of VBD systems and the construction of open and testable models of VBD dynamics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

各种各样的陆生植物和动物病原体已经进化出传播周期，需要载体，通常是节肢动物，当病原体以宿主为食时传播病原体。这些病媒传播的疾病（VBD）对人类，动物和植物健康构成严重威胁，并对全球经济福利产生负面影响。例如，大约三分之一的人口面临仅由蚊子传播的感染风险，而病媒传播许多重要的植物和牲畜疾病。每年，VBDs占人类传染病的17%，并造成数十亿美元的作物和牲畜损失。为了更好地预防和预测VBD的爆发，需要结合关于病媒与其环境在空间和时间上相互作用的多种类型的信息和数据。然而，由于收集的病媒数据孤立、难以获取，而且格式各异，这方面的努力受到阻碍。该项目的主要目标是建立一个名为VectorByte的集中式开放访问数据平台。它将载有关于病媒特征和种群数量的标准化数据。这将使数据更容易被疾病生态学界和其他感兴趣的群体分享和使用。此外，还将开发免费提供的分析这些数据和模拟这些数据的工具，并结合教育材料，包括使用数据库和数据分析工具的教程。培训早期职业科学家将通过研讨会和项目内博士后研究人员，研究生和本科生的指导来完成。培训讲习班将针对来自代表性不足的群体和区域的早期职业科学家以及来自更广泛的公共卫生和病媒控制界的从业人员，内容涉及数据库的使用和适用于数据的统计方法。这一合并后的受众将能够从应用领域获得关于最佳用户实践的反馈，并将促进协作机会，以在学术界开发的工具与真实的世界决策之间架起桥梁。该平台和培训将反过来支持研究和数学建模工作，从而更好地了解为什么会在何时何地爆发，并将允许制定和评估这些疾病的潜在控制战略。越来越多的经验证据表明，病媒的特征因时间、环境条件以及种群内部和种群之间的不同而不同。这种变异对病媒种群的动态产生连锁效应，因此也对病媒传染病的传播和控制战略的效力产生连锁效应。数学和统计模型可以用来更好地理解性状、种群和传播之间的联系。然而，要做好这一工作，就需要从实验室测量病媒个体特征到观察到的病媒种群动态的详细数据，而所有这些数据往往都难以获得或使用。此外，VBD系统的数据通常以不一致的格式和位置存档。VectorByte项目将开发一个用户友好的信息学平台，用于存储，访问和可视化数据，以填补VBD社区的这些空白。VectorByte平台有可能通过提供可查找、可扩展、可互操作和可重用（FAIR）数据来改变VBD疾病研究，这些数据是构建、测试和验证VBD模型所必需的，目前无法使用可用的开放数据。该项目将使VBD研究人员能够通过标准化格式和集中位置来增加其数据的影响力，提高数据的可持续性，同时增加重用的潜力。这些数据标准也将促进VBD系统的比较和VBD动力学的开放和可测试模型的构建。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。