Methodological Approaches to Planning and Analysis of N*

描述（由申请方提供）：防范和应对新的和重新出现的传染病需要一系列数学模型，以：（a）了解和预防导致新疾病出现的最初步骤，从纯粹的人畜共患病风险到人际传播;（B）在疾病爆发的早期阶段评估疾病的关键参数，包括其繁殖数量、连续间隔、传染性的时间进程等;以及（c）预先规划控制措施，利用模型比较不同政策下的流行病进程（及其分布）。在这笔拨款中，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内传播的第一个周期（可能是在建立完全的人际传播之前）的传播;（B）开发工具用于在真实的时间内根据疫情爆发早期可用的有限数据来估计生殖数量、控制措施的有效性以及传染性的时间;以及（c）开发数学建模工具，以中等复杂性的模型捕捉现实疾病传播网络的关键特征-比完整的、基于个人的模拟模型复杂，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工具，这将有助于理解和推广计算复杂的疾病传播模型的输出。

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.