Monitoring for biological agents in the environment is a longstanding method for predicting and investigating the incidence and spread of infectious diseases among human populations. Exposure to a pathogen is the initial step of acquiring an infectious disease. Therefore, controlling infectious disease outbreaks often relies on pinpointing the source of infection. In cases of influenza virus outbreaks, children are often the first to get sick, and therefore schools are considered a source of infection. Monitoring influenza-like illness (ILI) in schoolchildren is a common method for predicting and measuring influenza outbreaks. Noninvasive methods that indirectly monitor ILI in children are favored, but only provide minimal information regarding influenza virus activity, leaving many questions unanswered regarding influenza virus transmission among children and the greater community. Given the magnitude of the school-aged population, direct investigations of influenza virus in the school environment are needed to better elucidate influenza virus activity in schools. A significant barrier to this knowledge is the invasive nature of gold standard methods for detecting influenza virus in humans and the environment. Nasopharyngeal swabbing is abrasive, and surface swabbing is disruptive to students and teachers. Therefore, the overall goal of this dissertation research was to noninvasively study influenza virus activity in schools to characterize the relationship between influenza virus and student illness. For this purpose, two separate studies were devised to (i) design and evaluate a bioaerosol sampling method to noninvasively detect influenza virus in the school environment, (ii) employ this noninvasive method to quantify airborne influenza virus densities to identify respiratory virus “hotspots” in a public elementary school, and (ii) align airborne influenza virus densities with student and community data to characterize the relationship between influenza virus densities and student and community illness.
In our first study, we combined peer-reviewed bioaerosol sampling methods using state-of-the-art CDC NIOSH bioaerosol samplers, with molecular diagnostics, to noninvasively monitor influenza virus activity in a public elementary school. This approach enabled us to be the first researchers to detect airborne influenza virus RNA in a school. Our ability to detect airborne influenza virus in the school environment provides the first line of evidence of airborne influenza virus transmission in the school environment. We then used the bioaerosol methodology to quantify airborne influenza virus densities to identify respiratory virus “hotspots” in a public elementary school. Air samples were collected four times per week in four different locations in and around Ottawa Hills Elementary School throughout an eight-week sampling period during the 2013-14 influenza season. To test for correlations between environmental data and proportions of respirable particles in our samples, airborne virus-laden particles were also analyzed. The highest densities of airborne influenza virus RNA were retrieved from samples collected in the school hallway. We hypothesize the corridor to be a respiratory virus hotspot not only because of its high density of airborne influenza virus, but also because of its narrow size and high volume of student traffic. In conclusion, this study provides a method for individual school districts to use to identify respiratory virus hotspots in their school facilities, and also shows that during influenza season, airborne influenza virus has the potential to circulate in schools in large enough doses known to initiate infection.
In our final study, we used sampling, detection, and quantification methods from our first study to characterize the relationship between airborne influenza virus densities and student and community illness. Environmental parameters such as temperature and RH were also analyzed as well as virus-laden particle size. Particles <4 µm in diameter were strongly correlated with RH levels of 20 – 30%. Additionally, daily counts of respiratory symptoms reported to the school nurse were positively correlated with the number of influenza-associated hospitalizations in the community for the corresponding week, which supports current methods of monitoring ILI in children to predict and monitor communal influenza outbreaks. More importantly, our efforts reveal two lines of evidence linking the presence of airborne influenza virus with student illness and absenteeism. First, airborne influenza virus detection was followed by an increase in student absences due to illness. On the days following the first airborne virus detection, student absences rose 30% above the average number of absences per day during our sampling period. Second, a lag period of one to four days occurred between airborne IAV detection and increased student absence, which we hypothesize is linked to the incubation period for influenza (known to be one to four days). Each line of evidence suggests that the timely detection of airborne influenza virus might serve as a predictive indicator of
absence in schoolchildren, which could act as an early warning for communities that an outbreak is nearing. More specifically, our results show that an airborne influenza virus density at or above 11,470 copies m-3 air in a school is indicative of an increase in student absences above the daily average. Therefore, our study provides evidence of an airborne influenza virus density threshold for influenza infection in schools, which could potentially be monitored for and used by school officials when making decisions regarding school closure.
Finally, the utilization of bioaerosol sampling and molecular diagnostics to monitor influenza virus activity in schools to predict student and community illness is a novel concept in the fields of environmental microbiology and infectious disease epidemiology. Our efforts have allowed us to envision respiratory virus activity in the school environment, providing a more comprehensive picture of respiratory virus transmission among schoolchildren. The observed persistence of airborne influenza virus densities in our study suggests that current environmental health programs should be augmented to reduce airborne virus densities in schools. Additionally, our results suggest that routine monitoring of airborne influenza virus in schools, in addition to virus-laden particle size, RH, and student reported symptoms, is a noninvasive way to potentially predict ILI in students and the greater community. Lastly, our discovery of airborne influenza virus in the school environment suggests that airborne transmission is an important mode of influenza transmission during influenza season, and that new ideas for controlling the spread of influenza virus are needed.