Cross-post from the new NAO blog.

Link: https://dx.doi.org/10.2139/ssrn.4823882

Airborne pathogens cause a significant amount of present harm and are the most likely cause of future pandemics. By targeting their primary mode of transmission, air sampling could enable earlier detection and persistent monitoring of such pathogens.

As part of our work on sampling strategies for early detection of stealth pathogens, we performed a comprehensive review of air sampling, which has now been published as a preprint on SSRN. In our review, we examine the sources and composition of viral bioaerosols, evaluate the benefits and drawbacks of sampling technologies, and lay out strategies for effective implementation of air sampling programs. We find that:

  • Both PCR and metagenomic sequencing have detected a wide range of human viruses in indoor air, including respiratory RNA viruses and skin-borne DNA viruses.
  • Sampling viruses in air remains challenging, largely due to the difficulties in efficiently collecting ultrafine viral aerosols. However, recent advancements in sampling technologies, such as condensation-based methods and wetted-wall cyclone sampling, have shown promising results in effectively capturing these viral particles.
  • HVAC systems and high-traffic locations like airports and hospitals are particularly promising sampling sites for aggregating airborne material, including viral pathogens, from many individuals.
  • Passive sampling approaches, such as sampling vacuum dust collected in buildings, also show potential but remain underexplored.

While we believe more research on air sampling would be valuable, we’re not currently planning on prioritizing it at the NAO, as we want to focus our limited resources on wastewater and swab sampling. We’d be excited for others to take this up and advance the state of the art in this area; if you’re interested in taking this on, please reach out!

Note: This preprint is a substantially more comprehensive version of an earlier preprint described in this forum post

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