Statistical Methods for Studying Infectious disease

描述(由申请人提供)：我们的长期目标是开发一个 对流行病和病原体重现的预测科学(理解) 研究引起人类感染的病原微生物的进化 包括流行病在内的疾病。具体目标包括(1)发展人口 处理纵向样本的遗传学理论。我们将学习统计学 各种汇总统计数据的属性并开发模拟方法 总体样本和计算隔离模式的概率 网站。(2)开发和评估估计重要程度的统计方法 总体参数。我们将开发统计方法来估计 种群参数，如突变率、有效种群规模、增长 突变的频率、世代时间和年龄。(三)发展统计 检验假设的方法。我们将开发统计方法来测试 对理解进化机制至关重要的假说， 包括中性突变、恒定有效种群的假设 大小，两个种群之间没有遗传分化。(4)分析 A组链球菌流行的分子数据。我们将分析， 使用现有和新开发的统计方法，多态 关于一种名为补体链球菌抑制物(SIC)的基因的数据，它是 高度多态和SIC变异与GAS流行有关。(5)至 开发一个用户友好的纵向样品分析计算机程序包 纳入了新开发的统计方法。

DESCRIPTION (provided by applicant): Our long-term goal is to develop a predictive science (understandings) of epidemics and pathogen re-emergence and to study the evolution of pathogenic microbes which cause human infectious disease including epidemics. Specific aims include (1) To develop population genetics theory for treatinglongitudinal samples.We will study the statistical properties of various summary statistics and develop methods to simulate population samples and to compute the probability of a pattern of segregating sites. (2) To develop and evaluate statistical methods for estimating important population parameters. We will develop statistical methods to estimate population parameters such as mutation rate, effective population size, growth rate, generation time and the age of a mutation. (3) To develop statistical methods fortesting hypotheses. We will develop statistical methods to test hypotheses that are essential for understanding the mechanism of evolution, including the hypotheses of neutral mutations, constant effective population size, and no genetic differentiation between two populations. (4) To analyze molecular data from the epidemics of Group A streptococcus. We will analyze, using both existing and newly developed statistical methods, the polymorphism data on a gene called Streptococcal inhibitor of complement (sic), which is highly polymorphic and sic variants are associated with GAS epidemics. (5) To develop a user-friendly computer package for analyzing longitudinal samples incorporating newly developed statistical methods.