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

与新检测到的病原体变异体（基因型）相关的生物威胁程度，这些变异体与一些已知病原体在遗传上相似，可以根据研究中的两种变异体之间的交叉免疫力进行评估。两种变异体之间完全（缺乏）交叉免疫表明新检测到的病原体和已知变异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，用于估计双菌株系统中的交叉免疫力，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单位时间内每个受试者的接触次数有限。与许多流行病模型类似，所提出的流行病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）。提出了新的计算效率高的估计方法来估计偏微分方程模型。建议的方法的发展将通过分析一个真实的监测纵向数据的流行率的各种巴尔通体变种（基因型）在自然种群的啮齿动物（棉鼠）。研究小组由两个统计学家从两个学术机构和一个流行病学家从疾病预防控制中心，谁已经密切合作了数年。拟议的工作将提供通用工具，用于量化新检测到的病原体变体和已知细菌物种之间的流行病学相似性，这有助于解决与新检测到的变体相关的生物威胁评估的一般问题。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PDE模型，以及在其他领域，如金融。将向公众免费提供实施拟议方法的计算机包。研究团队将继续保持培养跨学科研究博士生的良好记录。

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.