Contact Network Transmission Modeling of Healthcare Associated Infections

项目概要/摘要 卫生保健相关感染（HAI）是死亡率和发病率的主要来源，影响约200万人 患者每年在医院内，病原体如艰难梭菌和耐甲氧西林葡萄球菌， 金黄色葡萄球菌（MRSA）通常传播给住院患者和在住院患者之间传播： 多药耐药微生物（MDRO），因为由这些病原体引起的HAI越来越难以 请客这些感染可以在医院扩大艾德，传播到其他医院，长期或熟练的护理设施， 然后，最终，整个社会。制定有效的干预措施，防止 HAI仍然是一个重要的公共卫生目标，并要求采取一些措施，以确保拟议的有效性。 干预措施（或其组合）可以有效和廉价地进行比较。在经验丰富的领域， 虽然不可能实现，但数学模型和模拟可以深入了解系统如何响应 研究中的干预措施。 该项目的首要主题是克服现有的障碍，模拟HAI的传播。我们 假设从复杂的细粒度数据中导出的高精度模型可以用来理解 在医疗机构内和医疗机构之间采集和传输HAI。基于我们模型的模拟 可用于比较替代干预措施，并为如何减少 MDRO和其他能够引起HAI的病原体的传播。

Project Summary/Abstract Healthcare-associated infections (HAIs) are a major source of mortality and morbidity and affect about two million patients each year. Within hospitals, pathogens like Clostridioides difficile and methicillin-resistant Staphylococ- cus aureus (MRSA) are routinely transmitted to and among hospitalized patients: also of particular concern are multidrug resistant organisms (MDROs), because HAIs caused by these pathogens are increasingly difficult to treat. These infections can be amplified in hospitals, transmitted to other hospitals, long-term or skilled-care facil- ities, and then, eventually, to the community at large. Developing effective interventions to prevent the spread of HAIs remains an important public health goal, and demands some means by which the effectiveness of proposed interventions (or combinations thereof) can be efficiently and inexpensively compared. In fields where experi- ments are not possible, mathematical models and simulations can yield insight into how a system responds to the intervention under study. The overarching theme of this project is to overcome existing barriers for modeling the spread of HAIs. We hypothesize that high-fidelity models derived from complex, fine-grained data can be used to understand the acquisition and transmission of HAIs within and across healthcare facilities. Simulations based on our models can be used to compare alternative interventions and provide effective and practical guidance for how to reduce the transmission of MDROs and other pathogens capable of causing HAIs.