Developing mathematical models and statistical methods to understand the dynamics of infectious diseases: stochasticity, structure and inference

开发数学模型和统计方法来了解传染病的动态：随机性、结构和推理

• 批准号: FT130100254
• 负责人: Prof Joshua Ross
• 金额: $ 43.09万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-06-30 至 2018-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT130100254
• 关键词: Developing; mathematical; models; statistical; methods

Infectious diseases remain a major contributor to mortality and illness worldwide. The potential for future severe pandemics also continues to present a substantial threat to our health and well-being. Mathematics and statistics are increasingly becoming part of the arsenal used by governments to combat the invasion and spread of infectious diseases. In such work, three themes have emerged as having the potential to revolutionise the modelling of infectious diseases: stochasticity, structure (both age and spatial), and inference. This project will develop state-of-the-art techniques, at the interface of these themes, of critical importance to understanding the dynamics of infectious diseases.

传染病仍然是全世界死亡和疾病的主要原因。未来可能发生的严重流行病也继续对我们的健康和福祉构成重大威胁。数学和统计学正日益成为政府用来对抗传染病入侵和传播的武器库的一部分。在这样的工作中，出现了三个主题，有可能彻底改变传染病的建模：随机性，结构（年龄和空间）和推理。该项目将在这些主题的界面上开发最先进的技术，对了解传染病的动态至关重要。