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Perhaps silly question as you’ve probably written about this before, have you tried getting people to (with you blinded) dump both natural and engineered DNA in wastewater in different quantities at random times to see how good your system is at picking it up?
Not a silly question, and not something where I think we’ve talked about plans publicly yet. Some sort of red-teaming is something I’d like to see us do in the second half of 2025. Most likely starting with fully computational spike-ins (much cheaper, faster to iterate on) and then real engineered viral particles.
Wow, this is so exciting!! Thanks for sharing, and congratulations team!
Wow 😍. That’s great. And if I read footnote 2 right, the implication is that by end of 2025, you’d aim to be able to detect a pathogen that sheds like Influenza A in cities you monitor before 2% of the population is infected? Or is that not quite right because you’re targeting 3 such runs weekly across all cities (maybe I should say “sewersheds”?) so you wouldn’t quite be able to hit that point yet?
I had some other basic / not-an-expert questions but no pressure to engage :)
Which cities are you monitoring again?
It sounds like from this notebook you’re still trying to figure out how valuable monitoring one city is from the perspective of catching any global pandemic, so I assume one weakness of this approach is in the geographic restrictions. Although I’ve vaguely heard of wastewater monitoring in a network of airports / aircrafts as a way to get around this (I can’t tell if that’s just an idea right now or if it’s already being implemented, though.)
Was the 2% threshold chosen for a particular reason?
Yes, that’s right. Though sensitivity in practice could be higher or lower:
As we gather more data we’ll get a better understanding of how easy or hard it is to detect Influenza A, along with other pathogens. Our influenza estimates are based on ~300 observations, but we now have the data to estimate for the 2024-2025 flu season with a lot more data. This is mostly a matter of someone taking the time to dig into it and put out an updated estimate.
We’re still trying to increase sensitivity:
Testing better wet lab methods
Getting pooled airplane lavatory samples again, which have a ~20x higher human contribution
Figuring out which municipal sewersheds have the highest human contribution and focusing there
The projection is based on an assumption of 9d end to end time, and is relatively sensitive to timing: if your pathogen doubles every 3d then the difference between a 9d and 12d turnaround time is 2x sensitivity. We’re currently well above 9d, but we’re on a track to get to ~7d via agreements with sequencing machine operators to reserve capacity and streamlining our processes. And then there are more expensive ways to get down to ~4d with serious investment in logistics (buy your own sequencer, run it daily, use the 10B flow cell for faster turnarounds, lab runs around the clock).
Chicago IL, Riverside CA, and several others we hope to be able to name publicly soon.
Yes, that’s a real issue. Cosmopolitan US cities are not terrible from this perspective, especially if you have a bunch with different international connections, but they’re still not good enough. Airplane lavatory sampling would be much better, not just because of this issue but also because (as I mentioned briefly above) they’re much higher quality samples. We’re working on this, but it’s much more difficult than bringing on municipal treatment plant partners.
No, it’s that 3x 25B is about the most we’re able to scale to at this stage. If we thought we could manage the scale 1% would have probably been our target, though 1% is still pretty arbitrary. Lower is better, since that means mitigations are more effective when deployed, but cost goes up dramatically as you lower your target.
Do you think 1% is very useful in practise? That seems very high to me and I would have thought by that stage we would know through other means already? Or is the plan to lower the threshold as the tech improves and aim for something lower?
I agree 1% high, and I wish it were lower. On the other hand, we’re specifically targeting stealth pathogens: ones where any distinctive symptoms come well after someone becomes contagious. Absent a monitoring system, you could be in a situation most people had been infected before anyone noticed there was something spreading. Flagging this sort of pathogen at 1% cumulative incidence still gives some time for rapid mitigations, though it’s definitely too late to nip it in the bud.
From this post:
I see, that answered some of my questions. I still feel confused how big a sewershed is relative to a city, and how much that matters from the perspective of early detection. But no pressure to engage, was just curious. Exciting!
A sewershed can vary dramatically in size: it’s the area that drains to some collection point (generally a treatment plant) and different cities are laid out differently. I’m most familiar with Boston (after refreshing the MWRA Biobot Tracker intently during COVID-19) and here the main plant serves ~2M people divided between the North and South systems:
Some other cities have much smaller plants (and so smaller sewersheds), a few have larger ones.
We’re not sure yet about the effect of size. It’s possible that small ones are better because the waste is ‘fresher’ and you spend fewer of your observations (sequencing reads) on bacteria that replicates in the sewer. Or it’s possible that larger ones are better because they can support more observations (deeper sequencing).
Nice. You’re such a fast writer! Very helpful, thank you!
It helps that I’m writing about stuff we’ve discussed internally a lot! Thanks for the good questions!