ATD Collaborative Research: A computational analysis of multi-strain structure in genetically diverse bacterial populations in a natural host environment

新检测到的病原体变异(基因类型)与一些已知病原体的遗传相似，其生物威胁的程度可以根据研究中的两种变种之间的交叉免疫来评估。两个变种之间完美的(缺乏)交叉免疫表明，新检测到的病原体和已知的变种在流行病学上是相同的(不同的)。将开发新的流行病学模型，以评估双菌株系统中的交叉免疫，该系统可能考虑自然宿主的不同出生率、垂直传播的可能性和单位时间内每个受试者有限的接触次数。与许多流行的流行病学模型类似，所提出的流行病学模型假定状态向量的动态服从某种非线性偏微分方程。提出了一种新的计算高效的估计PDE模型的方法。研究小组由来自两个学术机构的两名统计学家和一名来自疾控中心的流行病学家组成，他们在一起工作多年，对巴尔通氏变种(基因类型)在自然鼠类(棉鼠)中流行的真实监测纵向数据的分析将指导拟议方法的发展。拟议的工作将提供量化新检测到的病原体变异与已知细菌物种之间的流行病学相似性的通用工具，这有助于评估与新检测到的变异相关的生物威胁。所提出的估计方法可普遍适用于流行病学研究中使用的PDE模型的估计，也可用于其他领域，如金融领域。实施拟议方法的计算机程序包将向公众免费提供。研究团队将继续保持培养博士生进行跨学科研究的强劲记录。

The degree of bio-threat associated with newly detected pathogen variants (genotypes) that are genetically similar to some known pathogens may be assessed in terms of the cross-immunity between the two variants under study. Perfect (lack of) cross-immunity between the two variants suggests that the newly detected pathogen and the known variant are identical (distinct) epidemiologically. New epidemiological models will be developed for estimating cross-immunity in a two-strain system that may allow for variable birth rate of the natural hosts, possibility of vertical transmission and finite number of contacts per subject per unit time. Similar to many popular epidemiological models, the proposed epidemiological models stipulate that the dynamics of the state vector follow some nonlinear partial differential equation (PDE). New computationally efficient estimation methods are proposed for estimating a PDE model. The development of the proposed methodologies will be guided by analysis of a real monitoring longitudinal data on prevalence of various Bartonella variants (genotypes) in a natural population of rodents (cotton rats).The research team consists of two statisticians from two academic institutions and one epidemiologist from the CDC, who have worked closely together for a number of years. The proposed works will provide general tools for quantifying an epidemiological similarity between newly detected pathogen variant and known bacterial species, which contribute to the general problem on the assessment of bio-threat associated with newly detected variants. The proposed estimation methods can be generally applicable for estimating PDE models used in epidemiological studies, as well as in other fields, e.g. finance. A computer package implementing the proposed methods will be freely available to the public. The research team will continue to maintain the strong record of training PhD students in cross-disciplinary research.