Quick takes

So... what's the general take on the hantavirus outbreak?

Gavi's investment opportunity for 2026-2030 says they expect to save 8 to 9 million lives, for which they would require a budget of at least $11.9 billion[1]. Unfortunately, Gavi only raised $9 billion, so they have to make some cuts to their plans[2]. And you really can't reduce spending by $3 billion without making some life-or-death decisions. Gavi's CEO has said that "for every $1.5 billion less, your ability to save 1.1 million lives is compromised"[3]. This would equal a marginal cost of $1,607 $1,363 per life saved, which seems a bit low to me. But I think there is a good chance Gavi's marginal cost per life saved is still cheap enough to clear GiveWell's cost-effectiveness bar. GiveWell hasn't made grants to Gavi, though. Why? ---------------------------------------- 1. https://www.gavi.org/sites/default/files/investing/funding/resource-mobilisation/Gavi-Investment-Opportunity-2026-2030.pdf, pp. 20 & 43 ↩︎ 2. https://www.devex.com/news/gavi-s-board-tasked-with-strategy-shift-in-light-of-3b-funding-gap-110595 ↩︎ 3. https://www.nature.com/articles/d41586-025-02270-x ↩︎

According to someone I chatted to at a party (not normally the optimal way to identify top new cause areas!) fungi might be a worrying new source of pandemics because of climate change. Apparently this is because thermal barriers prevented fungi from infecting humans, but because fungi are adapting to higher temperatures, they are now better able to overcome those barriers. This article has a bit more on this: https://theecologist.org/2026/jan/06/age-fungi Purportedly, this is even more scary than a pathogen you can catch from people, because you can catch this from the soil. I suspect that if this were, in fact, the case, I would have heard about it sooner. Interested to hear comments from people who know more about it than me, or have more capacity than me to read up about it a bit.

EU opportunities for early-career EAs: quick overview from someone who applied broadly I applied to several EU entry programmes to test the waters, and I wanted to share what worked, what didn’t, and what I'm still uncertain about, hoping to get some insights. Quick note: I'm a nurse, currently finishing a Master of Public Health, and trying to contribute as best I can to reducing biological risks. My specialisation is in Governance and Leadership in European Public Health, which explains my interest in EU career paths. I don’t necessarily think the EU is the best option for everyone. I just happen to be exploring it seriously at the moment and wanted to share what I’ve learned in case it’s useful to others. ⌨️ What I applied to & how it went * Blue Book traineeship – got it (starting October at HERA.04, Emergency Office of DG HERA) * European Committee of the Regions traineeship – rejected in pre-selection * European Economic & Social Committee traineeship – same * Eurofound traineeship – no response * EMA traineeship (2 applications: Training Content and Vaccine Outreach) – no response * Center for Democracy & Technology internship – no response * Schuman traineeship (Parliament) – no response * EFSA traineeship – interview but no feedback (I indicated HERA preference, so not surprised) If anyone needed a reminder: rejection is normal and to be expected, not a sign of your inadequacy. It only takes one “yes.” 📄 Key EA Forum posts that informed and inspired me * “EAs interested in EU policy: Consider applying for the European Commission’s Blue Book Traineeship” * “What I learned from a week in the EU policy bubble” – excellent perspective on the EU policymaking environment 🔍 Where to find EU traineeships All together here: 🔗 https://eu-careers.europa.eu/en/job-opportunities/traineeships?institution=All Includes Blue Book, Schuman, and agency-specific roles (EMA, EFSA, ECDC...). Traineeships are just traineeships: don’t underestimate what

I’ve seen a few people in the LessWrong community congratulate the community on predicting or preparing for covid-19 earlier than others, but I haven’t actually seen the evidence that the LessWrong community was particularly early on covid or gave particularly wise advice on what to do about it. I looked into this, and as far as I can tell, this self-congratulatory narrative is a complete myth. Many people were worried about and preparing for covid in early 2020 before everything finally snowballed in the second week of March 2020. I remember it personally. In January 2020, some stores sold out of face masks in several different cities in North America. (One example of many.) The oldest post on LessWrong tagged with "covid-19" is from well after this started happening. (I also searched the forum for posts containing "covid" or "coronavirus" and sorted by oldest. I couldn’t find an older post that was relevant.) The LessWrong post is written by a self-described "prepper" who strikes a cautious tone and, oddly, advises buying vitamins to boost the immune system. (This seems dubious, possibly pseudoscientific.) To me, that first post strikes a similarly ambivalent, cautious tone as many mainstream news articles published before that post. If you look at the covid-19 tag on LessWrong, the next post after that first one, the prepper one, is on February 5, 2020. The posts don't start to get really worried about covid until mid-to-late February. How is the rest of the world reacting at that time? Here's a New York Times article from February 2, 2020, entitled "Wuhan Coronavirus Looks Increasingly Like a Pandemic, Experts Say", well before any of the worried posts on LessWrong: The tone of the article is fairly alarmed, noting that in China the streets are deserted due to the outbreak, it compares the novel coronavirus to the 1918-1920 Spanish flu, and it gives expert quotes like this one: The worried posts on LessWrong don't start until weeks after this article was p

Striking paper by Anant Sudarshan and Eyal Frank (via Dylan Matthews at Vox Future Perfect) on the importance of vultures as a keystone species.  To quote the paper and newsletter — the basic story is that vultures are extraordinarily efficient scavengers, eating nearly all of a carcass less than an hour after finding it, and farmers in India historically relied on them to quickly remove livestock carcasses, so they functioned as a natural sanitation system in helping to control diseases that could otherwise be spread through the carcasses they consume. In 1994, farmers began using diclofenac to treat their livestock, due to the expiry of a patent long held by Novartis leading to the entry of cheap generic brands made by Indian companies. Diclofenac is a common painkiller, harmless to humans, but vultures develop kidney failure and die within weeks of digesting carrion with even small residues of it. Unfortunately this only came to light via research published a decade later in 2004, by which time the number of Indian vultures in the wild had tragically plummeted from tens of millions to just a few thousands today, the fastest for a bird species in recorded history and the largest in magnitude since the extinction of the passenger pigeon.  When the vultures died out, far more dead animals lay around rotting, transmitting pathogens to other scavengers like dogs and rats and entering the water supply. Dogs and rats are less efficient than vultures at fully eliminating flesh from carcasses, leading to a higher incidence of human contact with infected remains, and they're also more likely to transmit diseases like anthrax and rabies to people. Sudarshan and Frank estimate that this led to ~100,000(!) additional deaths each year from 2000-05 due to a +4.2%(!) increase in all-cause mortality among the 430 million people living in districts that once had a lot of vultures, which is staggering; this is e.g. more than the death toll in 2001 from HIV/AIDS (92,000), malaria

Ajeya Cotra writes: Like Ajeya, I haven't thought about this a ton. But I do feel quite confident in recommending that generalist EAs — especially the "get shit done" kind —  at least strongly consider working on biosecurity if they're looking for their next thing.

The recent work on SAEBER, which applies sparse autoencoders (SAEs) to the screening of dna synthesis printers marks a big step towards effective function based screening. This allows for printers to be monitored just as a lab technician uses computational gel electrophoresis to separate a messy mixture into clear, readable bands through the use of a specialized gel. SAEs happen to do the exact same thing by taking the muddied activation results of a neural network and projecting them out onto a higher dimensional space until the individual viral motifs can be seen clearly. This allows for the motifs to be tracked as they move through the system in real-time, rather than waiting for a final product. However, while SAEBER is undoubtedly an effective method, can we say for a fact that it is the best tool for function based screening? Would it be better to scan the digital thoughts of the AI responsible for guiding the system generating the product, or monitoring the stability of the system itself, given that we can model the printer's physical state at any given time step during the printer's run? While scanning the digital motifs helps provide an understanding of the AI's intent, it would be interesting to see if monitoring the physical state of the printer might provide a more resilient safety net. My intuition is that modelling the printer’s state as a physical landscape and understanding the implications of changes in the landscape might be more prone to false positives from natural noise, but it also has the potential to be better at detecting divergence much earlier than waiting to interpret a complex digital signal. Has there been much discussion on combining these—using the physics of the machine to flag a problem, and the AI’s internal motifs to figure out exactly what that problem is?