Indoor air surveillance and factors associated with respiratory pathogen detection

COVID-19 has re-emphasised the need for scalable, non-invasive surveillance of community transmission of respiratory pathogens, and the importance of indoor air quality in mitigation efforts. Ambient air sampling provides such a surveillance method, and is a tool to study indoor transmission risk.
Indoor air surveillance and factors associated with respiratory pathogen detection
Like

In our recent study, now published in Nature Communications, we collected hundreds of air samples from all types of community settings, ranging from kindergarten to elderly care homes, over a 7 Month period, in the town of Leuven, Belgium. We tested them for the presence of 29 respiratory pathogens using multiplex qPCR. For each sample, we also collected transmission risk factors, such as occupancy, mask wearing, voice use, the amount of natural ventilation, CO2 concentration, and the presence of air filtration.

On average, 3.9 pathogens were positive per sample and 85.3% of samples tested positive for at least one. We saw clear trends in the detection rates throughout the sampling period, and across age groups, which shows that they correspond to disease patterns in the population. When we investigated the factors that were associated with pathogen detection and concentration, the importance of air quality was very clear. Both natural ventilation (the opening of windows and doors) and the indoor CO2 concentration were significantly and independently associated with the number of pathogens detected. Both CO2 concentration and air filtration were independently associated with the concentration of detected pathogens. When we looked more closely at a kindergarten, where we placed different air filters in different groups of children, we saw that strong air filters were better at removing pathogens than lighter filters. When we compared the pathogens in the air of community settings to the pathogens found in patients with severe respiratory infections in the same region, we saw a clear association for COVID-19, and a less clear association for Influenza A virus and Enterovirus D68. This suggests that, for some pathogens which tend to cause severe infections, ambient air samples may say something about the disease burden in the population. 

This study helps to interpret ambient air sample results for disease surveillance. It also demonstrates that even a small research team with a bike and a PCR machine can surveil the respiratory pathogens in a community at an affordable cost. Can you imagine what a public health program could achieve with a larger program? In addition, our results support the paramount importance of air quality to reduce the risk of transmission in the community. 

As always, our study has many limitations. The main one is that we used PCR instead of culture, which means we may have detected non-infectious pathogens. Also, we did not take respiratory samples from the attendants of our sampling sites, nor did we collect symptom or disease outcome data. These factors limit our ability to make firm conclusions on whether or not we are measuring transmission risk, or make it difficult to compare our methodology to other surveillance methods such as symptomatic screening or sentinel surveillance. 

FYI: the banner shows an air sample being taken behind the bar. Perks of the job!

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Microbiology
Life Sciences > Biological Sciences > Microbiology

Related Collections

With collections, you can get published faster and increase your visibility.

Pre-clinical drug discovery

We welcome studies reporting advances in the discovery, characterization and application of compounds active on biologically or industrially relevant targets. Examples include emerging screening technologies, the development of small bioactive compounds/peptides/proteins, and the elucidation of compound structure-activity relationships, target interactions and mechanism-of-action.

Publishing Model: Open Access

Deadline: Mar 31, 2024

Biomedical applications for nanotechnologies

Overall, there are still several challenges on the path to the clinical translation of nanomedicines, and we aim to bridge this gap by inviting submissions of articles that demonstrate the translational potential of nanomedicines with promising pre-clinical data.

Publishing Model: Open Access

Deadline: Mar 31, 2024