RFA-CK-22-008, TRANSMIT: Training Research Acumen in Students Modeling Infectious Threats

项目总结/摘要 持续的COVID-19大流行使医疗保健和公共卫生系统不堪重负， 强调有必要预测疾病的爆发，并准备好医院等资源， 床和工作人员。一个具有成本效益和及时的方式来准备资源，以应对这些挑战， 爆发是通过使用数学建模。模型可以作为虚拟实验室， 及时探索各种方案、干预措施或应用，为政策提供信息 干预措施。虽然COVID-19大流行凸显了模型可以填补的空白，但它也 强调了建模的一个相当大的差距：缺乏建模专业人员的培训， 开发并将传播模型应用于医疗机构。在本提案中，我们详细介绍了 三个项目旨在培养三名博士前研究员在不同方面的数学 医疗保健相关病原体的建模。这些项目针对不同的病原体， 在医疗环境中疾病传播的组成部分;而且，虽然每个项目都是不同的， 它们吻合得很好，形成了一个有凝聚力的研究计划。 项目1解决了医疗环境中疾病传播的一个关键组成部分：COVID-19 长期护理设施（LTCF）。在整个大流行期间，LTCF的发病率与 死亡率的负担。然而，尽管LTCF对疾病结局很重要， 它们是否对SARS-CoV-2施加了选择性的力量，这种力量塑造了全球的 病原体的进化尚不清楚。在这里，我们将开发模型来量化系统发育 社区和长期护理机构谱系之间的关系，以了解病毒 多样化归因于医疗保健环境。项目2探讨患者的风险因素 因感染SARS-CoV-2而住院治疗，以获得多药耐药微生物（MDRO）。快速 SARS-CoV-2的传播已经转变为医院感染控制和抗菌药物管理 施政纲要而其中一个变化是广泛使用可能不必要的抗生素， 住院病人。在这里，我们将识别子人群的特征 严重急性呼吸道综合征住院患者中， 二型冠状病毒项目3与项目1和项目2相结合，探索抗生素的进化 在医疗机构中，由于可变剂量和脱靶抗生素的使用而产生的耐药性。患者 LTCF的医院和居民暴露于广泛的病原体和治疗， 许多这些生物本身就暴露在广泛的环境中， 抗生素在这里，我们将开发进化模型，以调查导致 最难治的感染

PROJECT SUMMARY/ABSTRACT The ongoing COVID-19 pandemic has overwhelmed healthcare and public health systems, underscoring the need to anticipate disease outbreaks and prepare resources such as hospital beds and staff. One cost-effective and timely way to prepare resources to respond to these outbreaks is through the use of mathematical modeling. Models can act as a virtual laboratory to explore a variety of scenarios, interventions, or applications in a timely manner to inform policy interventions. While the COVID-19 pandemic highlighted the gaps that models can fill, it also highlighted a considerable gap in modeling: there is a lack of modeling professionals trained in developing and applying transmission models to healthcare settings. In this proposal, we detail three projects aimed to train three predoctoral fellows in different aspects of mathematical modeling of healthcare associated pathogens. These projects tackle different pathogens and components of disease transmission in a healthcare setting; and, while each project is distinct, they dovetail nicely, resulting in a cohesive research program. Project 1 tackles a critical component of disease transmission in healthcare settings: COVID-19 in long-term care facilities (LTCFs). Throughout the pandemic, LTCFs bore a disproportionate burden of mortality. Yet, while it is clear that LTCFs important with regards to disease outcomes, whether or not they exert selective forces on SARS-CoV-2 that have shaped global patterns of pathogen evolution is not yet known. Here, we will develop models to quantify the phylogenetic relationships between community and long-term care facility lineages to understand the viral diversification attributable to healthcare settings. Project 2 explores the risk factors of patients hospitalized with SARS-CoV-2 for acquiring multi-drug resistant organisms (MDROs). The rapid spread of SARS-CoV-2 has changed to hospital infection control and antimicrobial stewardship policies. One such change has been widespread potentially unnecessary antibiotic use among hospitalized patients. Here, we will identify the characteristics of the sub-population disproportionately impacted by co-infections with MDROs for patients hospitalized with SARS- CoV-2. Project 3 integrates with both Project 1 and 2, to explore the evolution of antibiotic resistance due to variable dose and off-target antibiotic use in healthcare settings. Patients in hospitals and residents of LTCFs are exposed to a wide range of pathogens and treatments, and many of these organisms have themselves been exposed to a wide range of environmental antibiotics. Here, we will develop models of evolution to investigate the conditions that lead to the most intractable infections.