RAPID: Big Geospatial Data for Decision Support in Ebola Triage

RAPID：用于埃博拉分诊决策支持的大地理空间数据

• 批准号: 1507611
• 负责人: Naphtali Rishe
• 金额: $ 10万
• 依托单位: Florida International University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1507611&HistoricalAwards=false
• 关键词: RAPID; Big; Geospatial; Data; Decision

Proposal #: 15-07611PI(s): Rishe, NaphtaliInstitution: Florida International University Title: RAPID: Big Geospatial Data for Decision Support in Ebola Triage Project Proposed:This project, developing a methodology for utilization of geospatial data for decision support in triage and hotline operations related to identification of suspected cases of Ebola aims to further, develop a prototype module, on the base of the TerraFly instrument (presently funded by NSF). The prototype, a decision support application, presents data mashup to operators responding to hotline calls and patient encounter triage. Additionally, the effort leverages work on Fuzzy Logic for epidemics prediction. Furthermore, in collaboration with UMBC, FIU researchers will:- Identify locations of Ebola by geolocating references in Twitter Posts, utilizing the FIU?s patent-pending technology of geolocating social media,- Generate near real time Crisis maps demonstrating the spread of Ebola available data and assess their utility to stakeholders presently involved in mitigation,- Compare maps derived from social media data streams to CDC maps. Broader Impacts:This work, coordinated with and submitted in parallel with respective RAPID proposals, with coalition members at FAU, UMBC, and UMN, aims to jointly address public health problems of national and global significance. In particular the proposers will work with FAU on modeling Ebola spread through use of innovative big data analytics techniques and with UMBC on integrating quantifiable social media data from Twitter into our data mashups. Beyond the present issue of Ebola, the proposed methodology and the coalition-building effort aims to support solutions in a wide range of public health issues.

提案号：15-07611PI(s): Rishe， NaphtaliInstitution: Florida International University标题：RAPID：用于埃博拉分诊决策支持的大地理空间数据项目建议：该项目旨在开发一种利用地理空间数据进行与埃博拉疑似病例识别相关的分诊和热线业务决策支持的方法，旨在进一步开发基于TerraFly仪器的原型模块（目前由NSF资助）。该原型是一个决策支持应用程序，向响应热线电话和患者遭遇分类的运营商提供数据混搭。此外，这项工作还利用模糊逻辑进行流行病预测。此外，通过与UMBC的合作，FIU的研究人员将：-利用FIU？-生成近乎实时的危机地图，显示埃博拉病毒的可用数据传播情况，并评估其对目前参与缓解工作的利益相关者的效用；-将来自社交媒体数据流的地图与CDC地图进行比较。更广泛的影响：这项工作与FAU、UMBC和UMN的联盟成员协调并与各自的RAPID提案并行提交，旨在共同解决具有国家和全球意义的公共卫生问题。特别是，提案人将与FAU合作，通过使用创新的大数据分析技术来模拟埃博拉病毒的传播，并与UMBC合作，将来自Twitter的可量化社交媒体数据整合到我们的数据mashup中。除了目前的埃博拉问题之外，拟议的方法和建立联盟的努力旨在支持解决广泛的公共卫生问题。