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

2019冠状病毒病大流行给公共和私营机构带来了前所未有的挑战，要求它们安全地重新开放公共场所，包括工作场所和学校。然而，鉴于一种高度传染性但看不见的病原体，我们几乎没有关于如何管理共享空间使用的指导。该项目的根本目的是更好地了解SARS-CoV-2如何在建筑环境中传播。由数学模型产生的预测将使用替代的非致病性病毒进行实验检验。该项目提出了一种新的范例，其中受感染个体存在的可能性、病毒脱落的数量和方式、病毒随时间的位置以及地点的使用需求为评估公共空间的占用和使用提供了重大进展。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。建议将类似于现有的建筑和消防规范，规定如何根据设计和使用要求分配每位住户的空间；我们的分析将生成一个“COVID代码”，可以在未来的疫情期间推广使用。本研究还将为学生和博士后提供培训机会。最近开发的计算模型（临时岛屿元种群模型（EIMM））应用元种群理论解释病原体如何在医院环境中持续存在，将进行修订，以解决SARS-CoV-2在建筑环境中的空间传播问题。EIMM将建筑环境的各个方面定义为不同的可居住区域（“demes”），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自己的生物学参数。利用生态学相关参数，如生长率、种群规模和承载能力，利用活的和非活的茧的数量和大小，而不是单独的人类宿主，来模拟病原体种群的大小和位置。包膜噬菌体phi6将用于验证模型预期以及在教室等真实环境中测试控制策略。目的是测试EIMM建议的哪些干预措施可以最大限度地减少噬菌体phi6在共享空间传播的机会，并且可以利用这些信息来估计各种干预措施将如何影响SARS-CoV-2的持久性和传播。该RAPID奖由环境生物学部传染病生态和进化项目颁发，资金来自《冠状病毒援助、救济和经济安全法案》。该奖项反映了美国国家科学基金会的法定使命，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.