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

各种各样的陆地动植物病原体已经进化出传播周期，需要媒介，通常是节肢动物，在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、动物和植物的健康构成了严重威胁，并对全球经济福利产生了负面影响。例如，大约三分之一的人口面临仅由蚊子传播感染的风险，而媒介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%，造成数十亿美元的农作物和牲畜损失。为了更好地预防和预测VBDS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信息和数据。然而，由于在载体上收集的数据被隔离、难以获取并以不同的格式保存，这一努力受到了阻碍。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。它将包含有关媒介特征和种群丰度的标准化数据。这将使疾病生态社区和其他感兴趣的社区更容易共享和使用数据。此外，将结合教育材料，包括关于使用数据库和数据分析工具的教程，开发可免费使用的工具来分析和模拟这些数据。培训早期职业科学家将通过该项目中的博士后研究人员、研究生和本科生的研讨会和指导来完成。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，介绍适用于这些数据的数据库和统计方法的使用。这一结合的受众将使应用领域对最佳用户实践的反馈成为可能，并将促进在学术界开发的工具与现实世界决策之间架起桥梁的合作机会。该平台和培训将反过来支持研究和数学建模工作，这将有助于更好地了解疫情在何时何地发生，并使之能够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，病媒的特征随时间、环境条件以及种群内和种群之间的不同而不同。这种变异对媒介种群的动态产生了连锁效应，因此也影响了媒介传播感染的传播和控制策略的有效性。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，要做到这一点，需要详细的数据，从实验室对病媒个体水平特征的测量到观察到的病媒种群动态，所有这些数据通常都很难获得或使用。此外，VBD系统的数据通常以不一致的格式和位置进行归档。VectorByte项目将开发一个用户友好的信息学平台，在全球范围内存储、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、可访问、可互操作和可重复使用的(公平)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，目前使用现有的开放数据是不可能的。该项目将使VBD研究人员能够通过标准化格式化和集中定位来增加其数据的影响，增加数据的可持续性，同时增加重复使用的潜力。这些数据标准还将促进VBD系统的比较和VBD动态的开放和可测试模型的构建。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.