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.

由于世界面临着大量埃博拉病毒的流行爆发，目前正在进行临床试验中的几种疫苗，有合理的机会在2015年初在该领域可用。由于疫苗的初始量将受到限制，因此对埃博拉流行性动态的理解对于通过对目标进行了实现的实现，对实时的实现，对埃博拉流行动态的有效性最大化至关重要。当前全球埃博拉病毒流行病的可处理和统计学上的预测动态模型。 将人口划分为三组的建模方法（所谓的SIR模型）及其各种概括在历史上被用作决定流行病是否生长还是消散的重要工具。 研究人员在具有给定程度分布的图表上扩展了爵士随机流行病的传统模型，以说明特定于埃博拉病毒的特征。 这些包括包括感染高风险（例如卫生工作者）的一类人，并结合了动态的网络结构，反映了与人口不同细分的接触方式在主机内感染过程中发生变化。新的数学模型描述了埃博拉通过人类和世界各地的群体范围内的埃博拉群体传播的方式，以及各个国家的群体，以及各个国家的范围内，以及范围内的各个国家的范围内，以及各个国家的范围内，遍及整个国家的群体，以及范围内的跨越。非洲和美国。预计该模型将允许公共卫生和政府官员快速分析许多不同的干预措施，以加快当前流行病的耗散，并选择最有效的预防或至少最小化未来爆发的方式。