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）：准备和应对新型和重新出现的传染病需要一系列数学模型，以： (a) 理解和防止导致新疾病出现的最初步骤，从纯粹的人畜共患风险到人际传播； (b) 评估疾病暴发早期阶段的关键参数，包括其繁殖数量、序列间隔、传染性时间进程等； (c) 提前规划控制措施，使用模型比较不同政策下的流行病进程（及其分布）。在这笔赠款中，我们将 (a) 开发控制政策模型，以最大限度地减少传染病在人类传播的第一个周期中的传播，可能是在建立全面的人际传播之前； (b) 开发实时使用的工具，根据疫情爆发初期可获得的有限数据，估计繁殖数量、控制措施的有效性和传染时间； (c) 开发数学建模工具，以中等复杂度的模型捕捉现实疾病传播网络的关键特征——比完整的、基于个体的模拟模型复杂，但比无法捕捉人口结构的简单微分方程模型复杂。这项工作的目标是设计有助于理解和概括疾病传播计算复杂模型输出的工具。