Map of Biosecurity Interventions
Summary
I recently created a visual map of biosecurity. It covers my interpretation of foundational biosecurity interventions. The map is designed to broadly answer “what are people working on in biosecurity?”
(Link to a larger, higher resolution image)
‘Low-downside Interventions’ are interventions that are on the lower-risk side. These might be good discussion topics or companies to work on. ‘Promising GCBR Interventions’ are interventions with general consensus among biosecurity experts for being effective at preventing catastrophic pandemics.
Not all interventions are made equal. Some are much more effective than others, but I’ve included the ‘less-promising’ interventions all the same. I didn’t want my biases (or the biosecurity community’s biases, for that matter) about what is and isn’t promising to obscure solutions from a first-principles breakdown.
Though I consulted experts and peers, all final decisions were ultimately mine and may differ from the biosecurity community. The rest of the post will go over my rationale for certain decisions.
GCBR vs. Covid-scale pandemics
This map covers preventing pandemics, not just the catastrophic ones, but also the Covid-scale ones which might occur more frequently.
EA focuses a lot on global catastrophic biological risk (GCBR) pandemics. This seems pretty important given its neglectedness and potentially catastrophic impact. I’ve outlined the interventions that I think would be promising for GCBRs.
At the same time, many in biosecurity consider the effects of AI to outweigh those from biorisks (the magnitude is usually 10-100x). Progress in alignment is influenced by factors like international cooperation, institutional distrust, and nuclear conflict. All of these factors are affected by Covid-scale pandemics, whether through decreases in trust, sudden scarcity of resources, or armed international conflict. Considering the possible detrimental effect of even small-scale but more frequent pandemics, it seems worth exploring interventions focused on this scale. There may be more low-hanging fruit than we imagine.
Mitigate-Prevent breakdown
I decided on a two-factor framework of Mitigate-Prevent because I think it covers the space of interventions well and because it resulted in a nice visual. Part of this framework is Survive which involves bunkers and food resilience. I didn’t include it because I wanted more emphasis on preventing diseases from becoming pandemics in the first place, which is much more important than escaping to a bunker. If we’re escaping to bunkers, then it’s likely that we’ve lost. That said, I could imagine creating another map that covers this axis of resilience.
Thoughts on some specific interventions
Agricultural disease monitoring and farm-animal testing
Factory farms practically incubate viruses due to the high concentration of animals. Because diseases can pass from animals to humans, more vigilance here could be an effective preventative measure. Wet markets experienced pushback for being viral breeding grounds, and it’s about time that factory farms undergo the same scrutiny.
In addition to worrying about human and animal infection, crops are also vulnerable. Agricultural practices are monoculture in nature, meaning there is a lack of genetic diversity in the crops grown. Blights exist, and countries are surprisingly dependent on a few sources of food. Monitoring agricultural diseases through runoff water or random sampling seems worth consideration.
Bioenhancement
By bioenhancement, I mean health and performance-boosting drugs. Most people have a negative connotation with drugs, but there’s evidence that supplements like caffeine pills, melatonin, and ashwagandha are relatively safe and effective (though this is not an endorsement of any of those products). Ultimately, bioenhancement means giving humans better control of their biology, whether through continuous glucose monitoring, increased alertness and productivity, or reduced anxiety. Increased productivity and reduced anxiety are multiplier effects for working on interventions, and it’s possible that some bioenhancement interventions will increase our viral resistance, much in the way that better sleep makes people far less prone to disease and sickness.
Policy and regulation
All of these interventions can benefit from better policy or regulation, but some interventions are more dependent than others. For example, it’s really hard to reform the BWC without engaging with the policy side of things. I think most people should at least test their fit in policy, whether through a brief research position at a think tank or through learning about different people’s experiences working in policy.
Far-UVC
Far-UVC is a specific spectrum of UV light at a wavelength of about 220nm. It’s shown promise for being safer on human cells than regular UV light, allowing use for (limited) sterilization of surfaces and killing pathogens in the air. I think far-UVC has good potential for mitigating pandemics, but there’s a lot more research that needs to go into this field. It’s possible that it isn’t as safe as many people claim and that its impact is constrained.
Closing thoughts
I hope this gives a clearer picture of what the field of biosecurity is broadly working on and excited about. I want to highlight that the process of creating the visual map was quite simple and replicable. In my case, I just went on Fiverr to hire a graphic designer, and I proceeded to give suggestions and revision notes. I think it’s seriously worth considering doing something similar if your cause area or idea would benefit from a clear visual or map.
I encourage people who are interested in learning more to reach out to people in the biosecurity space! Feel free to send me an email at james218.lin@gmail.com. I’ll try my best to answer questions or point you in the direction of someone who knows more than me.
Many thanks to Aman Patel, Chris Bakerlee, Dewi Erwan, Jonas Sandbrink, and Will Bradshaw for their thoughts on improving the graphic and input on specific biosecurity interventions.
- List of Short-Term (<15 hours) Biosecurity Projects to Test Your Fit by (17 Apr 2023 5:10 UTC; 167 points)
- Map of the biosecurity landscape (list of GCBR-relevant orgs for newcomers) by (17 Sep 2023 8:56 UTC; 148 points)
- On-Ramps Into Biosecurity—A Model by (14 Dec 2023 15:42 UTC; 70 points)
- Effective Altruism Reading List Information Design Poster (2/2) by (6 Jan 2023 14:49 UTC; 50 points)
- EA & LW Forums Weekly Summary (31st Oct − 6th Nov 22′) by (8 Nov 2022 3:58 UTC; 39 points)
- Map of maps of interesting fields by (LessWrong; 25 Jun 2023 14:02 UTC; 24 points)
- EA & LW Forums Weekly Summary (31st Oct − 6th Nov 22′) by (LessWrong; 8 Nov 2022 3:58 UTC; 12 points)
- 's comment on EA & LW Forums Weekly Summary (31st Oct − 6th Nov 22′) by (8 Nov 2022 11:13 UTC; 2 points)
I love this! These kinds of maps give so much clarity, and I find this one particularly well designed. Makes me want many more of these for other causes!
This is a great process and a great product!
One way I could see this being enhanced is a link between the poster and an updateable online list of informational resources for people who wish to go deeper.
A way you could accomplish this is by including a QR code on the poster that links to a durable URL (i.e. not bit.ly, a URL you own), which either hosts or redirects to a repository of deeper information on each topic.
For example, as I look at the poster, one think that jumps out at me is this:
No wet market, no factory farms, better regulation and protocol for labs → No source of zoonotic viruses
Zoonotic viruses are infections spread between people and animals. There is some ambiguity between whether zoonotic means “previously didn’t infect humans, but recently made the jump from an animal host” (i.e. the feared jump of H5N1 from birds to humans) vs. “routinely is transmitted between humans via an animal vector” (i.e. malaria).
People contact wild animals in other settings than wet markets, farms, and labs. For example, a possible COVID precursor infected a large number of mine workers in China via a bat vector. Malaria of course is transmitted by mosquito in ordinary domestic settings. People eat wild meat that they hunted themselves rather than purchasing it in wet markets. So eliminating wet markets, factory farms, and lab leak risk is not sufficient to eliminate all potential sources of zoonotic illness.
I have questions about the rationale for labeling pan-virus vaccines as not being a low-downside intervention, or what evidence we have that factory farms present serious zoonotic risks. But I don’t think this level of nuance can be included on a poster, of course. Creating a way to link the poster to a deeper explanation for those who have these thoughts might be valuable. It would also let you point them to resources if they’re excited about these topics and want to work on them.
I’ve had succeess in a previous project using QR codes on permanent signage to link viewers with specifically crafted informational articles. If this idea interests you, I’m a resource—feel free to reach out!
Thanks for the constructive feedback! I’ve added a link to a larger image as per your suggestion.
An updateable online list of resources seems useful, and I’m currently working on something similar. QR codes didn’t occur to me at all, so thanks for pointing that out! And on zoonotic risk, I was thinking of the other definition (i.e. previously didn’t infect humans), though I agree that vectors such as mosquitoes would also count.
On specific rationales, it’s often hard to speak explicitly about why things are and aren’t low-downside because of info hazard concerns. This is of course a problem when trying to communicate risk levels. This map is just my take on the state of biosecurity interventions. Even within the biosecurity community, there are debates for and against each side. That said, I agree that directed links and resources would be helpful.
Thanks again for taking the time to respond!
That makes sense, best of luck as you continue to develop this resource. I’d also suggest finding a way to make clear what sort of epistemic backing the map has on the map itself. Right now, it is essentially a list of claims. Here on this post, you give some context for those claims, but the map itself doesn’t. So if I was seeing the map as a standalone, I can only evaluate whether or not the connections between the items seem reasonable to me. This is easy to do for well-informed people, but the downside is that this tool is probably most useful for less-informed people. Optimizing this tool for the intended audience might take some more work, but I think it’s a great foundation to build on.
A couple other notes on the map from the standpoint of manufacturing.
The size is nonstandard, meaning that if you have it printed, you’ll have a large zone of whitespace and therefore a lot of wasted cost.
Depending on where and in what format you have it printed, all those colors may add significantly to the cost of printing as well.
Extremely unfortunately from the perspective of animal welfare, factory farming is possibly a net benefit for disease prevention.
I think this is mainly because this enormously reduces human-animal interactions. So zoonotic diseases have a lower chance to both develop and spread to humans compared to open air/backyard farms
Diseases can be contained in the unnatural, environments inside factory farms[1].
Note that this is not because factory farms are clean or healthy.
Factory farms are both disgusting, and chronic sources of deadly disease, deadly bird flu is literally happening across the US constantly
In a deep sense, the animals tend to be very unhealthy for a number of reasons, including genetics, e.g. they would be much more likely to perish from disease and other issues, in an outside backyard farm
If this isn’t true, I would really like to be updated.
This truth is very inconvenient for farm animal welfare people. But it is good to say the truth and inform people working in other areas.
Often by, well, sort of torturing the animals to death by heat.
I’d be careful about this claim. I’m not an expert, but I also don’t see cited sources here.
The limiting factor for zoonotic transmission isn’t the level of animal-to-human contact. It is the virus-to-human contact.
In a small, low-density farm with better ventilation and greater care invested in caring for or separating out sick animals, whatever virus is emitted by sick animals may be at a much lower concentration in the air. This would limit virus-to-human contact. By contrast, a high-density large farm puts a huge number of viral bioreactors (animals) in a cramped facility and exposes the same small number of people to that high-viral-concentration environment over and over again.
I don’t know which of these factors would win out on net. I wouldn’t trust one answer over the other without a lot of good hard evidence. My guess is that the details matter and you’d need to overstudy the issue to really be able to draw any general conclusions on this topic.
It’s not really possible for me to communicate how much I don’t want my first comment to be true.
I think scientific citation is good when done cluefully and in good faith. However, there are levels of knowledge that don’t interact well with casual citations in an online forum and this is difficult to communicate. For literatures, I think truth/expertise can be orthogonal to agreement with some literatures, because knowledge is often thin, experts are wrong or the papers represent a surprisingly small number of experts with different viewpoints[1].
I think this is a good argument to begin a conversation with an expert.
I’m not sure this argument is proportionately informed about current intensive farming practices that would be a useful update to my comment.
For one, ventilation systems are substantial in farms, and get more sophisticated in more intensive farming (until they mess up or turn it off, cruelly cooking the animals to death).
More generally, I think it’s good to try to communicate how hostile, artificial and isolated from the outside world intensive farming environments are.
Workers often literally wear respirators:
Together with the respirator, farm workers often wear full body coveralls, gloves.
This produces a suit that should look familiar to people working in biosecurity.
I can keep going—you can get showers, change stations, positive/negative pressure airflow, and maybe literally airlocks.
Here is a representative equipment manufacturer.
https://www.theseo-biosecurity.com/en/our-expert-appraisals/breeders/
Note how alien and hostile these environments are: the suits and preparations resemble a biohazard lab.
I think you can see how large, intensive farms allow this to happen.
I think the above gives a good sense of the very issue in the top comment:
Basically, once you have an intensive farm, you can put capex into intensifying and concentrating and greatly increasing suffering in one place, and dissolve a lot of biosecurity concerns plausibly. That’s what factory farms do well.
I’m not super interested in elaborating because I’m hoping someone shuts this down and proves this wrong. Help? Rethink Priorities?
I actually do have the cites. I distrust the EA forum to handle scientific expertise and I’m really hoping not to make the case or codify this comment—maybe someone else might make the counter case decisively.
You make a plausible, vivid case in this comment for why factory farming might be lower risk (workers wear PPE and buildings are designed to lower infection risk). And as I said in my reply above, I fully accept that there’s a plausible case why factory farming might pose a lower risk for zoonosis than non-factory farms. I’m just not certain and would want to see a sufficient amount of hard, high-quality evidence.
Consider also that factory farms, by lowering costs and driving up supply, cause a greater amount of animals to be produced than would counterfactually be the case on small farms. People would eat less meat, fewer farm animals would be raised, and there would be less opportunity for viral exposure by farm workers because the industry would be smaller as a whole.
You claim to “have the cites,” but don’t share them because you “distrust the EA forum to handle scientific expertise?” I’m a biomedical engineering graduate student. I eat citations for breakfast lunch and dinner. I barely trust them when I can read them. I trust arguments without citations even less. All that stuff about “distrusting EA forum” and “hoping not to make the case or codify” doesn’t make sense to me, and neither does the bit about “a good argument to begin a conversation with an expert.”
To be clear, I am not making a confident claim about whether or not factory farming is better or worse than other forms of farming or alternative industrial structures. I’m saying that it’s probably a very complex question and that we should not make casual guesses about the answer—we should rely on evidence, and if we don’t have it, we should admit our uncertainty.
Interesting, thanks for sharing!
In general, it seems to be the case that the sign of the longterm effects of neartermist interventions is often unclear.
I don’t know what you mean, and to the extent that I do understand, I think I disagree. If you are making an empirical claim, you should back it up with clear arguments and evidence. If there’s a relevant expert field/literature, you should cite it and if you differ from its distribution of consensus, you should signal that and argue for why. For example, I think your second comment is much better in this regard than your first. The tendency to skimp on this is detrimental to the discourse, I think.
If you just want to say “This is what I reckon” then fair enough, it’s only an internet forum. But this should be signalled. And it would lead me to put near-zero weight on the content.
Might be related: Reality is often underpowered
(I skimmed bits of this discussion, so I might be off! Unfortunately, I don’t have time to engage properly.)
I agree, there’s lots of cases where there isn’t robust empirical literature or trustworthy expert views. But the relationship between factory farms and zoonotic spillover doesn’t seem like such a case, such that casual speculation without citing evidence is not very useful.
Your comment is really interesting for a lot of reasons. Just curious, did you click on my profile or try to figure out who I am?
No I didn’t. I had some vague sense of your background being in software engineering from looking at your profile a few months ago, and some sense of your views from seeing many of your comments over time. Why do you ask?
Does ‘figure out who I am’ mean ‘Charles He’ is a pseudonym? If so I wasn’t aware.
Edit: although I seem to remember seeing something about software, I may be mis-remembering and guessing due to the tagged subscription under your name, which is probably a new thing/maybe misleading.
Ok, thanks, this makes sense. (As a digression, yes, the software tag is misleading.)
This depends on the path to no factory farms right? If the path is mainly via alternative meat being grown in factories then that would reduce pandemic risk. I
f the path is mainly via replacing factory farms with other farms then I think you make an interesting argument for how this could increase pandemic risk, but I’m not sure whether I agree or disagree.
This is cool! I’m often confused and feel ignorant about the field.
Is this the full resolution version? If not, maybe upload one and link to it? It’s a bit hard to read on my phone at least.
On a computer you can open the image in a new tab for the full-size version.
Just added a link, hopefully that makes it more accessible! Thanks for pointing this out.
Perfect, thanks!
I love visual presentations of ontologies, and this is a beautifully done one. More people should do such things.
That said, I am pretty confused about your ontology. Why is early detection in mitigation and sterilization in prevention? Like, I can kinda see it in that in order to detect a thing it has to already be spreading, but presumably sterilization (UVC, etc) is actually only useful in the worlds where the pathogen is spreading?
I feel like a more natural ontology would be “reducing R0 for generic pathogens”, “early detection” and “vaccines / treatment”. (I feel most confident that the first one is a natural category.)
Thanks for the thoughts!
I think you’re right on sterilization making more sense for mitigation. My thought process was that sterilization of surfaces in hospitals and the air can almost fully prevent infections from spreading. The case for mitigation does feel more natural though.
On choosing ontologies, I think that several frameworks could have worked in theory, but in practice I felt that the mitigate-prevent framework was the simplest to understand for a general audience. As with all frameworks, there are gray areas, but the distinction is clear enough so that the visual makes sense.
And the things about built environment, and better PPE, are also, in this view, most useful for preventing an infection from ever getting off the ground?
I would really expect PPE to be a mitigation as well.
Thanks for the nice overview! Just wanted to note that shelters (on earth) do not seem to be worth it.
Thank you for this effort! This adds a lot of clarity to someone (me) who is relatively new to biosecurity and wants to orient in the current biosecurity landscape.
I was wondering if it might be possible to do an interactive map where you could for example click on a concept and it would give you more details about it, who is currently working on it, etc. (maybe there is a mindmap software that allows this?). I’m not sure how to go about implementing that and it would obviously only be available in a digital format, but I think it could be another useful project. Either way, thank you for the effort you have made for this map!
Thank you for the great work—I wonder which other fields might benefit from the same treatment (all of them?).
One note: you mark “built environment” as low downside risk. Is this true? I’d assume that a constant low-level exposure to pathogens is what builds up our immune systems (perhaps why allergies and asthma levels are rising is our increasingly disinfected environments?) so I’d assume that built environments (which I presume mean those with controlled air-flow and sealed from the outside) actually do carry possible significant downside risks through weakening immune systems.
I am not an expert and hold this opinion weakly, just wanted to learn more :)
Edit: likewise for “drills and online classes”—we have seen it has a mental impact on children when they do shooter drills, and that online classes have costs in the socializing of children. Perhaps we do not mean the same when we say “low downside risk”?
Hello James, big thanks for your global overview of biosecurity interventions.
I was thinking about the “Better PPE” one: do anyone know if there are already projects to raise awareness on this issue to key organisations like ISEA?
Hi James, this is great, we should be in touch! Bryce Rogers (at highimpactengineers.org) and I are working on cross-cause-area technology-focussed mapping project and biosecurity is one of the areas we’re starting with for our prototype. Some comments below mention how it would be useful to link/attach information to different nodes in the map and that’s precisely what we’re doing. I believe Bryce emailed you and I’m CC’d. I’d love to get in touch and get your thoughts on the matter.
Seems like a cool distillation, thanks for doing it!
As a point about visualizing the data, I personally wonder if this would be easier to read as a table (here’s an extremely crappy one I made of a subset of your graph), or maybe with the same idea but arranged as a ‘sideways tree’ — e.g. something that looks like a decision tree but without the percentages.
It was a bit hard for me to parse as is that e.g. “early detection” and “early response” are your main pathways into mitigation (and I think having it laid out more cleanly might make it easier to maintain this project + understand and audit the reasoning behind your taxonomy)