RAPID: Modeling Ebola Spread and Developing Decision Support System Using Big Data Analytics

该项目旨在通过推动计算机科学、大数据分析、数据可视化技术和决策支持系统的最新发展，帮助解决具有国家和全球意义的紧急公共卫生问题（特别是埃博拉病毒的传播）。具体来说，这项工作是开发计算模型来预测埃博拉病毒的传播，利用从一个给定病人开始的“正向模拟”和感染在社区中的传播，以及向后的模拟，旨在追踪一些已证实的感染，直到病人“零”。这项工作利用了大数据分析技术、有关潜在个人关系、卫生中心位置和埃博拉病毒传播已知机制的数据。该项目直接连接佛罗里达国际大学（FIU）？TerraFly系统，这是一个基于网络的系统，旨在帮助空间和遥感数据的可视化。该系统允许用户“飞行”。以精细的分辨率在地球表面上探索各种数据（例如，当地信息，街道地图，航空摄影，卫星图像等）。然后将埃博拉病毒传播模式输入决策支持系统（DDS）。这些输入还包括有关社会群体或个人的信息。根据传播模式，DSS将计算一个社会群体或一个特定的人感染埃博拉病毒的概率。该系统将能够向接听热线电话的操作员和遇到病人并决定分诊的现场工作人员提供数据混搭。这些数据还将以报告的形式提交给负责的政府机构。这一具有时效性的项目需要及时收集和分析埃博拉病毒的传播情况，以便能够建立正确的模型。

This project aims to help address urgent public health problems (specifically the spread of the Ebola virus) of national and global significance by advancing the state of the art in computer science, big data analytics, data visualization techniques, and decision support systems. Specifically, the effort, developing computational models to predict the spread of Ebola utilizing both 'forward simulation' from a given patient and the propagation of the infection into the community and backwards, aims to trace a number of the verified infections to patient 'zero.' The work utilizes big data analytic techniques, data about underlying personal relationships, health center locations, and the known mechanisms for the spread of the Ebola virus.The project connects directly to the Florida International University (FIU)?s TerraFly system, a web-enabled system designed to aid in the visualization of spatial and remotely sensed data. The system allows users to ?fly? with fine resolution over the surface of the earth to explore various kinds of data (e.g., local information, street maps, aerial photography, satellite imagery, etc.). The Ebola spread patterns are then fed into a Decision Support System (DDS). These inputs also consist of information about social groups or individual persons. Based on spread patterns, the DSS will then calculate probabilities for a social group or a given person to get infected with Ebola. The system will be able to present data mashups to operators responding to hotline calls and field workers encountering patients and deciding about triage. The data will also be presented in report form to responsible government agencies. This time-sensitive project necessitates prompt collection and analysis of the spread of the Ebola virus in order to enable the development of the correct models.