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

新发现的与某些已知病原体在遗传上相似的病原体变异（基因型）的生物威胁程度可以根据所研究的两种变异之间的交叉免疫来评估。两种变体之间完全（缺乏）交叉免疫表明，新发现的病原体和已知变体在流行病学上是相同的（不同的）。将开发新的流行病学模型，以估计两种菌株系统中的交叉免疫，该系统可能考虑到自然宿主的可变出生率、垂直传播的可能性和每个受试者在单位时间内的有限接触次数。与许多流行的流行病学模型类似，本文提出的流行病学模型规定状态向量的动力学遵循一些非线性偏微分方程（PDE）。提出了一种新的计算效率高的估计方法来估计PDE模型。提出的方法的发展将以对啮齿动物（棉鼠）自然种群中各种巴尔通体变异（基因型）流行率的实际监测纵向数据的分析为指导。研究小组由来自两个学术机构的两名统计学家和来自疾病预防控制中心的一名流行病学家组成，他们多年来一直密切合作。所提出的工作将为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提供通用工具，这有助于评估与新检测到的变异相关的生物威胁的一般问题。所提出的估计方法可以普遍适用于估计流行病学研究中使用的偏微分方程模型，以及其他领域，如金融。实施建议方法的电脑套件将免费提供给公众。研究团队将继续保持培养博士研究生进行跨学科研究的良好记录。

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.