Methodological Approaches to Planning and Analysis of N*

预防和应对新的和重新出现的传染病需要一系列的数学 （a）了解和预防导致新疾病出现的最初步骤， 人畜共患疾病在人与人之间传播的风险;（B）评估疾病的关键参数，包括其 在暴发的早期阶段，繁殖数量、连续间隔、传染性的时间进程等; 和（c）提前计划控制措施，使用模型比较流行病的进程（及其 分布在不同的政策。在这项拨款中，我们将（a）开发控制政策模型，以尽量减少 传染病在人类内部传播的第一个周期期间的传播，可能在完全传播之前， （B）开发用于真实的时间的工具，以估计 生殖数量、控制措施的有效性和有限数据中的传染性时间 （c）开发数学建模工具，以捕捉 中等复杂性模型中的现实疾病传播网络-比完整模型复杂性低， 基于个人的模拟模型，但比简单的微分方程模型更复杂， 捕捉人口结构。这项工作的目标是设计工具，将有助于理解和 推广计算复杂的疾病传播模型的输出。

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 .inadvance 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.