Mathematical and statistical methods for modelling invivo pathogen dynamics

体内病原体动力学建模的数学和统计方法

• 批准号: DP170103076
• 负责人: Prof James McCaw
• 金额: $ 23.43万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-01-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP170103076
• 关键词: Mathematical; statistical; methods; modelling; invivo

This project aims to develop mathematical models and Bayesian statistical methods that better capture how natural defence responses and drugs help control infection. When viruses (e.g. influenza) or parasites (e.g. malaria) invade the human body, they begin to replicate. To date, only simple mathematical models have been developed to capture these processes, and these models are not well formulated. This project will improve biomathematics and biostatistical algorithms for pathogen dynamics and is ultimately expected to benefit public health and clinical research aimed at alleviating the effect of infectious diseases on human health.

该项目旨在开发数学模型和贝叶斯统计方法，以更好地捕捉自然防御反应和药物如何帮助控制感染。当病毒（如流感）或寄生虫（如疟疾）侵入人体时，它们开始复制。到目前为止，只有简单的数学模型已经开发，以捕捉这些过程，这些模型没有很好地制定。该项目将改进病原体动力学的生物数学和生物统计算法，最终有望有利于公共卫生和临床研究，以减轻传染病对人类健康的影响。