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

通过 K-12 学校的连续空气采样来预测和快速应对呼吸道病毒爆发

• 批准号: 10658581
• 负责人: David H. O'Connor
• 金额: $ 78.87万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-18 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10658581
• 关键词: 2019-nCoV; Absenteeism; Age; Air; Air Movements; Awareness; Behavior Therapy; COVID-19; COVID-19 detection; COVID-19 diagnostic; COVID-19 pandemic; COVID-19 surveillance; COVID-19 testing; Censuses; Child; Collection; Communities; Consumption; County; Data; Detection; Diagnostic tests; Disease; Disease Outbreaks; Fatigue; Foundations; Future; Household; Illness impact; Individual; Infection; Influenza; Laboratories; Learning; Location; Masks; Measures; Modeling; Oregon; Pattern; Persons; Proxy; Rapid diagnostics; Research Personnel; Respiratory Disease; Risk; SARS-CoV-2 infection; Schools; Seasons; Sentinel; Sentinel Surveillance; Site; Students; Surveillance Program; Testing; Time; United States; Variant; Viral; Virus; Wisconsin; air sampler; air sampling; commune; community transmission; high risk; improved; infection risk; influenza infection; influenzavirus; innovation; programs; promote resilience; respiratory; respiratory pathogen; respiratory virus; risk mitigation; risk prediction; school district; surveillance strategy; teacher; tool; transmission process; viral detection; viral transmission; wastewater samples

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.

项目概要/摘要 COVID-19暴露了呼吸道病原体监测的弱点。检测SARS-CoV-2的工具包括 最初有限。现在SARS-CoV-2流行，学校和其他聚集场所正在努力 进行系统的监视。随着流感病毒和其他呼吸道病原体恢复共存 与SARS-CoV-2一样，大流行疲劳破坏了依赖于行为的风险缓解策略 修改后，造成了前所未有的因病缺课的风险。 我们假设，在K-12学校频繁的空气采样是一个简单的，廉价的，准确的表面， 确定学校及其所在社区何时处于高水平的战略 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学校内放置一个空气采样器，连续收集空气样本， 在整个学年中每周两次。我们将检测空气样本中的SARS-CoV-2和流感vi- 罗斯是呼吸道病毒缺席的两个主要原因。一个关键的问题是， 空气样本中的病毒不劣于对流感样病毒感染者进行全面的个体检测。 疾病。我们正在与俄勒冈州（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SARS-CoV-2和流感的检出率在空气监测和诊断之间相似， 测试个人。如果它们是相似的，这将表明，简单，廉价，匿名 空气采样方案可以作为学校监测病毒方案的基础。 我们还将确定在空气样本中检测和测序SARS-CoV-2是否能预测更广泛的情况。 社区疾病传播。使用SARS-CoV-2诊断测试，废水，环境和mo- 能力数据以及校内空气采样器检测和测序数据，我们将开发和验证 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 流感病毒的风险，目前没有系统地监测。 成功地在一个大的国家开发了监测SARS-CoV-2和流感病毒的精密空气采样器 公立学校的设置将为全国范围的监测计划提供一个模型。这样的程序 将导致更安全的教室，提高对威胁特定社区的呼吸道病毒的认识， 学校，并提高抵御未来威胁学校的呼吸道病原体的能力。