RAPID: Stochastic Ebola Modeling on Dynamic Contact Networks

RAPID：动态接触网络的随机埃博拉建模

• 批准号: 1513489
• 负责人: Grzegorz Rempala
• 金额: $ 17.66万
• 依托单位: Ohio State 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: 2015-01-15 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513489&HistoricalAwards=false
• 关键词: RAPID; Stochastic; Ebola; Modeling; Dynamic

As the world faces a large outbreak of Ebola epidemic, several vaccines are currently in clinical trials with a reasonable chance of being available in the field in early 2015. Since the initial amount of vaccine will be limited, the understanding of Ebola epidemic dynamics is essential for maximizing the effectiveness of public health intervention through a combination of targeted vaccination, monitoring and quarantine.This project is concerned with developing a realistic but at the same time mathematically tractable and statistically predictive dynamic model of the current world-wide Ebola epidemics. The modeling approach that divides the population into three groups (susceptibles, infected, and removed--the so-called SIR model) and its various generalizations has been used historically as an important tool in deciding whether epidemics grow or dissipate. The investigators expand the traditional model of an SIR stochastic epidemic on a graph with a given degree distribution, in order to account for the Ebola-specific features. These include, among others, incorporating a class of individuals at high risk of infection (e.g., health workers), and incorporating a dynamic network structure that reflects how contacts with different segments of the population change over the course of infection within host.The new mathematical model describing the way in which Ebola spreads through a network of human contacts, both in rural and urban areas as well as across countries and continents, will be informed by the actual field data from various parts of the world including Africa and the United States. It is expected that the model will allow public health and government officials to quickly analyze a host of different intervention scenarios in order to speed up the current epidemic's dissipation and to select the most effective way of preventing, or at least minimizing, the future outbreaks.

随着世界面临埃博拉疫情的大规模爆发，几种疫苗目前正在进行临床试验，很有可能在2015年初投入使用。由于最初的疫苗数量将是有限的，了解埃博拉疫情动态对于通过有针对性的疫苗接种、监测和隔离相结合最大限度地发挥公共卫生干预的有效性至关重要。该项目致力于开发一个现实但同时在数学上易于处理的、统计上可预测的当前全球埃博拉疫情的动态模型。将人口分成三组(易感人群、感染人群和被移除人群--所谓的SIR模型)及其各种概括的建模方法，历史上一直被用作确定流行病是增长还是消散的重要工具。研究人员在给定度分布的图上扩展了SIR随机流行病的传统模型，以解释埃博拉特有的特征。其中包括纳入一类高感染风险的个人(例如卫生工作者)，并纳入一个动态的网络结构，反映与不同人群的接触在宿主内感染过程中的变化。描述埃博拉病毒在农村和城市以及跨国家和大陆的人际接触网络传播方式的新数学模型将由包括非洲和美国在内的世界不同地区的实际现场数据提供信息。预计该模型将允许公共卫生和政府官员快速分析一系列不同的干预情景，以加快当前疫情的消散，并选择最有效的预防方法，或者至少将未来的疫情降至最低。