NAO Updates, Spring 2024

From my own experience it seems really good you are trying to quickly get out in the field and trying to get hands-on experience doing these tests - I love it! Have you found any good way to assess when to stop doing desktop analysis and instead actually try to do the thing? And if so, do you think such guidance on when to pivot from "modelling to experiments" would be transferable to other initiatives in biosecurity or perhaps even EA more broadly? CE has written quite a bit on this I think but maybe there are differences between GH and biosecurity? Or maybe some other categorization that makes more sense (maybe biosecurity isn't a good category here). One thing I perhaps naively observe is that compared to GH which can be in hard-to-access areas for people living in the north, biosecurity is often supposed to be deployed right where we live, potentially making the cost of trying stuff out extremely low (like going outside and asking passersby to swab their nose).

I loved this update and felt super excited that the NAO team is collecting all sorts of dirt and seeing what can and cannot be detected and refining methods.

Executive summary: The Nucleic Acid Observatory (NAO) team provides updates on their progress over the past 6 months in wastewater sequencing, pooled individual sequencing, nucleic acid tracers, sequencing data analysis, cost modeling, and organizational changes to detect stealth pandemics.

Key points:

1. Developed and optimized protocols for extracting nucleic acids from wastewater samples, including influent, sludge, and airplane waste.
2. Collaborating with experts to adapt custom metagenomic sequencing protocols and compare results from different groups.
3. Starting a new effort to collect and sequence pooled nasal swab samples from public places.
4. Published a white paper and detailed reviews comparing sampling strategies for early detection of stealth biothreats.
5. Redesigned and reimplemented the metagenomic sequencing pipeline for improved scalability and performance.
6. Conducted cost modeling and theoretical analysis to understand the cost and efficacy of detecting stealth pandemics via metagenomic sequencing.

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