MOdeling Nursing homes to Affect Response to COVID-19 (MONARC)

项目摘要 疗养院受到严重急性呼吸系统综合征冠状病毒2的打击尤为严重 （SARS-CoV-2）大流行。NH可能作为传播的中心，可以继续帮助推动 因为它们是一个复杂的、相互关联的卫生设施网络的关键部分， 地区然而，确定如何最好地预防/控制SARS-CoV-2在养老院的传播， 会很有挑战性NH本身是一个复杂的系统，由NH居民/工作人员/游客组成， 在一天中以不同的方式。由于自然生态系统及其所在的生态系统是复杂的， 系统，计算建模，综合经济，业务和流行病学方面的SARS- CoV-2可以为决策者提供关于如何最好地预防SARS-CoV-2传播的重要见解 在NHS内和整个周边地区。这个项目的总体目标是， Nursing Homes to Affect Response to COVID-19（MONARC）是开发基于代理的模型（ABM） 并使用这些模型来帮助设计和评估各种SARS-CoV 2政策 和干预（例如，为NH居民、NH工作人员和 参观者）。此外，该项目将开发一种新的计算工具， 其他地区的公共卫生官员和政策制定者可以使用它来建立他们的NHS模型， 用于制定有关COVID-19预防和应对的决策。该项目将由两名经验丰富的 研究人员和他们的团队已经合作了十多年，开发了ABM， 预防/控制传染病在医疗机构的传播。自2007年以来，这包括帮助 决策者解决了几乎所有对美国的主要传染病威胁，包括嵌入到 2009年H1N1疫情期间的卫生与公众服务部（HHS）。该项目将是一个自然的延伸， 我们过去的项目和我们目前的COVID-19冠状病毒建模工作。具体目标1将制定 OC的70个国家卫生局评估不同SARS-CoV-2症状筛查和COVID-19检测的影响 策略，如时间，频率和测试类型。具体目标2将探讨各种价值 将COVID-19阳性的NH居民和照顾他们的工作人员在内部和跨部门进行分组的策略 不同的NH。具体目标3将开发一种计算工具，可以同时评估症状 筛查、检测和聚集策略，以应对NHS中的COVID-19，考虑到当地的患病率， 设施规模和遵守感染预防标准。MONARC项目将带来多个 创新包括：1）解决紧迫但目前尚未解决的问题，即国家卫生机构可以做些什么， 预防/控制SARS-CoV-2的传播，2）确定SARS-CoV-2预防和控制策略 应根据不同的国家卫生机构和国家卫生机构居民和工作人员的特点进行调整，3）制定一个 这是一个计算工具，NHS可以使用它来帮助确定应对SARS-CoV-2的最佳策略。

PROJECT SUMMARY ABSTRACT Nursing homes have been hit particularly hard by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. NHs may serve as epicenters of transmission that could continue to help fuel the overall pandemic because they are critical parts of complex, interconnected networks of health facilities in a region. However, determining how best to prevent/control the transmission of SARS-CoV-2 in nursing homes can be challenging. A NH itself is a complex system, consisting of NH residents/staff/visitors that mix with each other in different ways throughout a given day. Since NHs and the ecosystems that they sit within are complex systems, computational modeling that integrates economic, operational, and epidemiologic aspects of SARS- CoV-2 can provide decision makers with important insights on how best to prevent the spread of SARS-CoV-2 within NHs and throughout the surrounding region. The overall goal of this proposed project, MOdeling Nursing homes to Affect Response to COVID-19 (MONARC), is to develop agent-based models (ABMs) of the 70 NHs in OC and use these models to help design and evaluate various SARS-CoV2 policies and interventions (e.g., screening, testing, and cohorting strategies for NH residents, NH staff and visitors). Furthermore, the project will develop a new computational tool that NH administrators and public health officials and policymakers in other regions can then use to build models of their NHs to use to make decisions about COVID-19 prevention and response. This project will be led by two seasoned investigators and their teams who have worked together for over a decade on developing ABMs to prevent/control the spread of infectious diseases in healthcare facilities. Since 2007, this has included helping decision makers address nearly every major infectious disease threat to the U.S., including being embedded in Health and Human Services (HHS) during the 2009 H1N1 epidemic. This project will be a natural extension of our past projects and our current COVID-19 coronavirus modeling work. Specific Aim 1 will develop ABMs of the 70 NHs in OC to evaluate the impact of different SARS-CoV-2 symptom screening and COVID-19 testing strategies such as the timing, frequency, and test types. Specific Aim 2 will explore the value of various strategies to cohort COVID-19-positive NH residents and the staff who care for them, within and across different NHs. Specific Aim 3 will develop a computational tool that can simultaneously evaluate symptom screening, testing, and cohorting strategies to address COVID-19 in NHs, accounting for local prevalence, facility size, and adherence to infection prevention standards. The MONARC project will bring multiple innovations including: 1) addressing urgent but currently unaddressed questions about what NHs can do to prevent/control the spread of SARS-CoV-2, 2) determining how SARS-CoV-2 prevention and control strategies should be tailored by different NHs and NH resident and staff characteristics and 3) developing a computational tool that NHs can use to help determine the best strategies in response to SARS-CoV-2.