Modeling and control of environmentally transmitted pathogens

性状（由申请人提供）：许多病原体能够通过环境感染宿主，宿主之间不直接接触。迫切需要在用于疾病控制的数学和计算模型中更好地描述环境传播的特征。我们的长期研究目标是开发一个定量框架，以推进疾病传播理论和控制病原体与环境途径和水库。我们的中心假设是，不同的模型配方的环境传播的适用性取决于病原体的生活史，环境水库的表征，以及与病原体暴露相关的过程。将艰难梭菌在医疗机构中的传播作为案例研究，将实现以下具体目标：1）开发和分析机械地解决环境传播的模型。明确的功能形式，代表暴露途径将开发使用heterogeneing理论，并将与宿主外的病原体动力学，并在疾病动力学的影响将进行调查。2)开发和分析空间上明确的模型，以解决空间异质性在环境传播中的作用。将开发基于主体的模型，以包括环境传播的空间特征。他们的聚集行为将近似和比较偏微分方程模型。3)使用最佳控制理论评估环境传播对疾病控制和监测的影响。最佳控制将应用于ABM，以确定首选的环境策略。该项目将全面了解环境传播的规模扩大，以及环境水库，传播和减少环境暴露的控制策略的不同模型表示的适用性。从数学的角度来看，该项目将解决与ABM分析相关的重大数学挑战，ABM用于从分子生物学到生态学的所有生物学科，即如何将空间显式ABM减少到平均场动态，以及如何将最佳控制策略从平均场模型转移到ABM。

DESCRIPTION (provided by applicant): Many pathogens are able to infect hosts via the environment without direct contact between hosts. There is a critical need to better characterize environmental transmission in mathematical and computational models used for disease control. Our long term research goal is to develop a quantitative framework to advance disease transmission theory and control of pathogens with environmental pathways and reservoirs. Our central hypothesis is that the suitability of different model formulations for environmental transmission depends on the pathogen life history, the characterization of the environmental reservoir, and the processes associated with pathogen exposure. Using as a case study the transmission of Clostridium difficile in health-care settings, the following specific aims will be carried out: 1) Develop and analyze models that mechanistically address environmental transmission. Explicit functional forms that represent exposure pathways will be developed using queueing theory, and will be linked to the pathogen dynamics outside the host, and implications in disease dynamics will be investigated. 2) Develop and analyze spatially explicit models to address the role of spatial heterogeneity in environmental transmission. Agent-based models (ABM) will be developed to include spatial features of environmental transmission. Their aggregated behavior will be approximated and compared with partial differential equations models. 3) Assess the implications of environmental transmission in disease control and surveillance using optimal control theory. Optimal control will be applied to ABMs to identify the preferred environmental strategies. The project will deliver a comprehensive understanding of the scaling up of environmental transmission, and the suitability of different model representations of environmental reservoirs, transmission, and control strategies that reduce environmental exposure. From a mathematical perspective, the project will address significant mathematical challenges associated to the analysis of ABMs, which are used across all biological disciplines, from molecular biology to ecology, namely how to reduce spatially explicit ABMs to mean-field dynamics, and how to transfer optimal control strategies from the mean-field models to the ABMs.