Anticipating and rapidly responding to respiratory virus outbreaks with continuous air sampling in K-12 schools

项目摘要/摘要 新冠肺炎暴露出在呼吸道病原体监测方面的弱点。检测SARS-CoV-2的工具有 最初是有限的。现在SARS-CoV-2流行，学校和其他集会场所努力 执行系统监控。随着流感病毒和其他呼吸道病原体回归共存 与SARS-CoV-2病毒一样，大流行疲劳破坏了依赖行为的风险缓解战略 修改，在学校造成了前所未有的因病旷课的风险。 我们假设，在K-12学校进行频繁的空气采样是一种简单、廉价和准确的方法。 用于确定学校及其所在社区何时处于兴奋状态的监控策略 SARS-CoV-2和流感病毒传播的风险。 在这项研究中，我们将在16所K-12学校每所学校内放置一个空气采样器，并收集持续的空气样本。 在整个学年里，PLES每周两次。我们将化验空气样本中的SARS-CoV-2和流感病毒VI- RUS，呼吸道病毒旷工的两大原因。一个关键的问题是，是否检测到这些 空气样本中的病毒不逊于对流感样患者的全面个体检测 疾病。我们正在与俄勒冈(威斯康星州)学区合作，该学区已经在- 学校对有症状的个人进行快速诊断测试。在这个独特的环境中，我们可以确定 如果空气监测和诊断的SARS-CoV-2和流感的检测率相似 对个人的测试。如果它们相似，这将表明简单、廉价和匿名 空气采样计划可能是以学校为基础的哨兵病毒监测计划的基础。 我们还将确定在空气样本中检测和排序SARS-CoV-2是否具有更广泛的预测能力 社区疾病蔓延。使用SARS-CoV-2诊断测试、废水、环境和管理 除了学校空气采样器检测和测序数据外，我们还将开发和迭代 使用空气采样器数据预测社区传播的模型。我们将把这个模型扩展到预测 目前没有系统监测的流感病毒的风险。 成功研制成功SARS-CoV-2和流感病毒的高精度空气采样器监测 公立学校的设置将为全国范围内的监测项目提供一个样板。这样的一个节目 将导致更安全的教室，提高对威胁特定通信的呼吸道病毒的认识- 提高对未来威胁学校的呼吸道病原体的复原力。

Project summary/abstract COVID-19 revealed weaknesses in respiratory pathogen surveillance. Tools to detect SARS-CoV-2 were initially limited. Now that SARS-CoV-2 is prevalent, schools and other congregate settings struggle to perform systematic surveillance. As influenza virus and other respiratory pathogens return to co-exist alongside SARS-CoV-2, pandemic fatigue undermines risk mitigation strategies that rely on behavior modification, creating an unprecedented risk of illness-caused absenteeism in schools. We hypothesize that frequent air sampling in K-12 schools is a simple, inexpensive, and accurate sur- veillance strategy for identifying when schools and the communities where they are located are at high risk for SARS-CoV-2 and influenza virus transmission. In this study, we will place an air sampler inside each of 16 K-12 schools and collect continuous air sam- ples twice weekly throughout the school year. We will test air samples for SARS-CoV-2 and influenza vi- rus, the two leading causes of respiratory virus absenteeism. A key question is whether detecting these viruses in air samples is non-inferior to comprehensive individual testing of people with influenza-like illnesses. We are partnering with the Oregon (Wisconsin) School District which already performs in- school rapid diagnostic testing of symptomatic individuals. Within this unique setting, we can determine if the detection rates of SARS-CoV-2 and influenza are similar between air surveillance and diagnostic testing of individuals. If they are similar, this would suggest that simple, inexpensive, and anonymous air sampling programs could be the foundation of school-based sentinel virus surveillance programs. We will also determine whether detecting and sequencing SARS-CoV-2 in air samples forecasts broader community disease spread. Using SARS-CoV-2 diagnostic testing, wastewater, environmental, and mo- bility data alongside in-school air sampler detection and sequencing data, we will develop and iterate a model using air sampler data to forecast community transmission. We will extend this model to forecast the risk for influenza viruses that are not currently surveilled systematically. Successfully developing precision air sampler surveillance for SARS-CoV-2 and influenza virus in a large public school setting would provide a model for a nationwide surveillance program. Such a program would lead to safer classrooms, improve awareness of respiratory viruses that threaten specific commu- nities, and increase resilience to respiratory pathogens that threaten schools in the future.