Methodological Approaches to Planning and Analysis of N*

N* 规划和分析的方法论

• 批准号: 7028724
• 负责人: MARC LIPSITCH
• 金额: $ 47.63万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-02-01 至 2011-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7028724
• 关键词: Africa; bacteria infection mechanism; bioterrorism /chemical warfare; clinical research; communicable disease control; communicable disease transmission; computational biology; computer simulation; cooperative study; emerging infectious disease; human data; malaria; mathematical model; model design /development; virus infection mechanism

DESCRIPTION (provided by applicant): Preparing for and responding to novel and re-emerging infectious diseases requires a range of mathematical models to: (a) understand and prevent the initial steps leading to emergence of a new disease from a purely zoonotic risk to human-to-human spread; (b) evaluate key parameters of the disease, including its reproduction number, serial interval, time course of infectiousness, etc. in the early phases of an outbreak; and (c) plan in advance for control measures, using models to compare the course of the epidemic (and its distribution) across various policies. In this grant, we will (a) develop models of control policies to minimize the spread of an infectious disease during the first cycles of transmission within humans, possibly before full human-to-human transmission is established; (b) develop tools for use in real time to estimate the reproductive number, effectiveness of control measures, and timing of infectiousness from the limited data available early in an outbreak; and (c) develop mathematical modeling tools that capture the key features of realistic disease transmission networks in models of intermediate complexity - less complex than full, individual-based simulation models but more complex than the simple differential equation models that fail to capture population structure. The goal of this work is to design tools that will aid in understanding and generalizing the output of computationally complex models of disease transmission.

描述（由申请人提供）：准备并应对新颖和重新出现的传染病需要一系列数学模型，以：（a）理解并防止最初的步骤导致新疾病从纯粹的人畜共患病风险到人类到人类传播的新疾病； （b）评估疾病的关键参数，包括其繁殖数，串行间隔，传染性时间等等。在爆发的早期阶段； （c）提前计划进行控制措施，使用模型比较各种策略的流行病（及其分布）的过程。在这笔赠款中，我们将（a）制定控制政策模型，以最大程度地减少在人类内部第一个传播周期中传染病的传播，甚至可能是在建立完全人类到人类传播之前； （b）开发用于实时使用的工具，以估计从爆发早期可用的有限数据中获得的生殖数量，控制措施的有效性以及传染性的时机； （c）开发数学建模工具，这些工具在中间复杂性模型中捕获现实疾病传播网络的关键特征 - 比完全基于个体的模拟模型复杂，但比未能捕获人口结构的简单微分方程模型更为复杂。这项工作的目的是设计工具，以帮助理解和推广疾病传播的计算复杂模型的输出。