RAPID: Collaborative Research: Metapopulation Modeling to Develop Strategies to Reduce COVID-19 Transmission in Public Spaces

2019冠状病毒病大流行对公共和私人机构安全重新开放公共场所（包括公共场所和学校）提出了前所未有的挑战。然而，我们几乎没有指导如何管理共享空间的使用，因为它具有高度传播性，但不可见的病原体。该项目的基本目标是更好地了解SARS-CoV-2如何在建筑环境中传播。通过数学建模产生的预测将使用替代非致病性病毒进行实验测试。该项目提出了一个新的范例，其中受感染的个人存在的可能性，病毒脱落的数量和方式，随着时间的推移病毒的位置，以及位置的使用需求提供了公共空间占用和使用评估的重大进展。最终目标是制定能够限制病毒传播和应对当前全球公共卫生挑战的做法。建议将类似于既定的建筑和消防法规，这些法规根据设计和使用要求规定如何分配每个居住者的空间;我们的分析将产生一个“COVID代码”，可以在未来爆发时推广使用。这项研究还将为学生和博士后学者提供培训机会。 最近开发的计算模型（短暂岛集合种群模型（EIMM）），应用集合种群理论来解释病原体如何在医院环境中持续存在，将被修改，以解决SARS-CoV-2在建筑环境中的空间传播。EIMM将建筑环境的各个方面定义为不同的可居住居住区（“demes”），其方式与考虑人类宿主的方式大致相同，但这些demes具有与SARS-CoV-2的生存和传播相关的生物参数。生物和非生物群落的数量和大小，而不是人类宿主，被用来模拟病原体种群的大小和位置，使用生态相关的参数，如增长率，人口规模和承载能力。一个包膜噬菌体phi 6将被用来验证模型的期望，以及在真实的环境，如教室的测试控制策略。目标是测试EIMM建议的哪些干预措施最大限度地减少了噬菌体phi 6在共享空间中传播的机会，这些信息可以用于评估各种干预措施如何影响SARS-CoV-2的持久性和传播。该RAPID奖由环境生物学部门的传染病生态学和进化计划颁发，使用冠状病毒援助，救济，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The COVID-19 pandemic presents an unprecedented challenge to public and private institutions to safely reopen public spaces, including workspaces and schools. However, we have little guidance on how to manage the use of shared spaces in light of a highly transmissible, but invisible, pathogen. The fundamental aim of this project is to better understand how SARS-CoV-2 spreads in built environments. Predictions generated by mathematical modeling will be experimentally tested using a surrogate non-pathogenic virus. This project presents a new paradigm where the likelihood of infected individuals being present, the amount and manner of viral shedding, the locations of viruses over time, and the usage-needs of a location provide for a major advancement in the assessment of public space occupancy and usage. The ultimate goal is to develop practices capable of limiting virus transmission and meeting the current worldwide challenge to public health. Recommendations will resemble established building and fire codes, which regulate how space is allotted per occupant based upon design and usage requirements; our analyses will generate a “COVID Code” that can be generalized for use during future outbreaks. This research will also provide training opportunities for students and postdoctoral scholars. A recently developed computational model (the Ephemeral Island Metapopulation Model (EIMM)) that applies metapopulation theory to explain how pathogens persist in hospital environments will be revised to address the spatial spread of SARS-CoV-2 within built environments. The EIMM defines aspects of the built environment as distinct habitable zones of occupancy (“demes”) in much the same manner as human hosts are considered, but these demes have their own biological parameters relevant to the survival and transmission of SARS-CoV-2. The number and size of both living and non-living demes, instead of human hosts alone, are used to model size and location of pathogen populations using ecologically relevant parameters, such as growth rate, population size, and carrying capacity. An enveloped bacteriophage phi6 will be used to validate model expectations as well as test control strategies in real environments such as classrooms. The goal is to test which interventions suggested by the EIMM minimize opportunities for phage phi6 spread in shared spaces, and this information can be adapted to provide estimates of how various interventions would affect SARS-CoV-2 persistence and transmission.This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.