JoshuaBlake

Karma: 1,373

I am an (almost finished) PhD student in biostatistics and infectious disease modelling (population-level); my research focuses on Bayesian statistical methods to produce improved estimates of the number of new COVID-19 infections. During the pandemic, I was a member of SPI-M-O (the UK government committee providing expert scientific advice based on infectious disease modelling and epidemiology).

I enjoy applying my knowledge broadly, including to models of future pandemics, big picture thinking on pandemic preparedness, and forecasting.

JoshuaBlake 24 Oct 2024 18:28 UTC
2 points
0 ∶ 0
on: How Likely Are Various Precursors of Existential Risk?

Type of estimate: Geometric mean of forecaster probabilities

This is a bit odd. Should probabilities be odds?

JoshuaBlake 16 Jul 2024 16:17 UTC
12 points
2 ∶ 0
on: Can a pandemic cause human extinction? Possibly, at least on priors
Could you please expand on why you think a Pareto distribution is appropriate here? Tail probabilities are often quite sensitive to the assumptions here, and it can be tricky to determine if something is truly power-law distributed.

When I looked at the same dataset, albeit processing the data quite differently, I found that a truncated or cutoff power-law appeared to be a good fit. This gives a much lower value for extreme probabilities using the best-fit parameters. In particular, there were too few of the most severe pandemics in the dataset (COVID-19 and 1918 influenza) otherwise; this issue is visible in fig 1 of Marani et al. Could you please add the data to your tail distribution plot to assess how good a fit it is?

A final note, I think you’re calculating the probability of extinction in a single year but the worst pandemics historically have lasted multiple years. The total death toll from the pandemic is perhaps the quantity most of interest.

JoshuaBlake 15 Jul 2024 8:40 UTC
6 points
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in reply to: Will Bradshaw’s comment on: The Precipice Revisited

If you were willing to start putting doses in arms without any safety or efficacy testing at all, that’s when you could start.

I think even this is pretty optimistic because there was very little manufacturing capacity at that point.

JoshuaBlake 11 Jul 2024 14:34 UTC
4 points
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in reply to: Jeff Kaufman 🔸’s comment on: Sample Prevalence vs Global Prevalence

I don’t see how you can say both that it will “almost never” be the case that NYC will “hit 1% cumulative incidence after global 1% cumulative incidence” but also that it would surprise you if you can get to where your monitored cities lead global prevalence?

Sorry, this is poorly phrased by me. I meant that it would surprise me if there’s much benefit from adding a few additional cities.

JoshuaBlake 10 Jul 2024 22:19 UTC
2 points
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in reply to: calebp’s comment on: Sample Prevalence vs Global Prevalence
The best stuff looking at global-scale analysis of epidemics is probably by GLEAM. I doubt full agent-based modelling at small-scales is giving you much but massively complicating the model.

JoshuaBlake 10 Jul 2024 22:15 UTC
4 points
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in reply to: Jeff Kaufman 🔸’s comment on: Sample Prevalence vs Global Prevalence
Sorry, I answered the wrong question, and am slightly confused what this post is trying to get out. I think your question is: will NYC hit 1% cumulative incidence after global 1% cumulative incidence?

I think this is almost never going to be the case for fairly indiscriminately-spreading respiratory pathogens, such as flu or COVID.

The answer is yes only if NYC’s cumulative incidence is lower than the global mean region (weighted by population). Due to connectedness, I expect NYC to always be hit pretty early, as you point out, definitely before most rural communities. I think the key point here is that NYC doesn’t need to be ahead of the epicentre of the disease, only the global mean.

One way of looking at this is how early on does NYC get hit compared to other cities/regions. This analysis (pdf) orders cities by connectedness to Wuhan to answer this question for COVID. It looks like they’ve released an online tool that lets you specify different origin locations and epidemiological parameters. So you could rank how early NYC gets hit for a range of different scenarios.

by carefully choosing a few cities to monitor around the world you can probably get to where it leads global prevalence

This would surprise me. It’s hard to imagine a scenario where the arrival time at different major travel hubs is very desynchronized as these locations are highly connected to each other. So you’d probably then end up looking at a long tail of locations which are poorly connected to the main travel hubs.

JoshuaBlake 10 Jul 2024 17:31 UTC
2 points
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on: Sample Prevalence vs Global Prevalence

This effect should diminish as the pandemic progresses, but at least in the <1% cumulative incidence situations I’m most interested in it should remain a significant factor.

1% cumulative incidence is quite high, so I think this is probably far along you’re fine. E.g. we’ve estimated London hit this point for COVID around 22 Mar 2020 when it was pretty much everywhere.

JoshuaBlake 9 Jul 2024 15:07 UTC
4 points
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in reply to: OscarD🔸’s comment on: Number of EAs per capita by country
Hmm.… That cutoff is really making it hard to assess what’s going on here IMO. Everything is kinda clustered close to the line making me suspect the selection effect is important.

JoshuaBlake 1 Jul 2024 7:18 UTC
4 points
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in reply to: Seth Ariel Green’s comment on: Farmed animals are neglected
This seems unnecessarily precise and long. I don’t think many people would get a different takeaway from the current title but it has over twice as many words.

JoshuaBlake 1 Jul 2024 7:10 UTC
2 points
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in reply to: OscarD🔸’s comment on: Number of EAs per capita by country
You could do a funnel type plot where your y-axis is EAs/capita and your x-axis is 1/sqrt(population), which is sort of what you’d expect the standard deviation to look like.

JoshuaBlake 1 Jul 2024 7:07 UTC
7 points
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on: Cost-effectiveness of epidemic/pandemic preparedness
This seems intuitively in the right ballpark (within an order of magnitude of GiveWell), but I’d caution that, as far as I can tell, the World Bank and Bernstein et al. numbers are basically made up.

I’ve previously written about how to identify higher impact opportunities. In particular, we need to be careful about the counterfactuals here because a lot of the money on pandemic preparedness comes from governments who would otherwise spend on even less cost effective things.

JoshuaBlake 1 Jul 2024 6:58 UTC
3 points
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in reply to: Dhruvin Patel’s comment on: Advice for current / potential PhD students
Glad you found it useful.

Your question is hard to answer because tackling GCBRs is extremely inter-disciplinary and I’m not familiar enough with the field at large to identify clear gaps. Personal fit probably matters more than the specific field. Most work on pandemic preparedness is applicable to GCBRs, and there’s lots of research groups on that.

Sorry that’s not a very helpful answer. If you’ve got more specific questions I’m happy to try and help.

Advice for current / potential PhD students

JoshuaBlake28 Jun 2024 15:43 UTC

27 points

3 comments5 min readEA link

(blog.joshuablake.co.uk)

JoshuaBlake 25 May 2024 12:14 UTC
8 points
3 ∶ 1
in reply to: Ramiro’s comment on: The Charity Commission has concluded its inquiry into Effective Ventures Foundation UK
My top line summary is: in several areas, EV were operating below the standard the commission would expect, but have rectified the issues to the commission’s satisfaction.

JoshuaBlake 25 May 2024 12:11 UTC
10 points
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in reply to: Ramiro’s comment on: The Charity Commission has concluded its inquiry into Effective Ventures Foundation UK

Is this about OCB?

The timings are description line up very closely to the public record, so I’m almost certain it must be.

JoshuaBlake 14 May 2024 12:07 UTC
5 points
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in reply to: defun 🔸’s comment on: GPT-4o Discussion Thread
Since the launch of GPT-4, the next relevant data point will be GPT-5. All the rest is ~noise.
Yes, and the longer until this release the more we should update towards longer timelines

JoshuaBlake 13 May 2024 21:18 UTC
3 points
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on: $14t BOTEC cost to eradicate all infectious diseases
Why are you ballparking $10b when all of the examples given are many multiples of that? $100b seems like a better estimate.

I also suspect we’re targeting easy to eradicate diseases. Those without animal reservoirs that will cause resurgences and where there are effective interventions. Therefore, I’d suggest this is a lower bound.

JoshuaBlake 7 May 2024 14:46 UTC
13 points
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on: Probably Good launched a new job board!
Can I get alerts when new jobs get added matching my criteria?

JoshuaBlake 6 May 2024 16:24 UTC
14 points
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in reply to: Grayden 🔸’s comment on: The market plausibly expects AI software to create trillions of dollars of value by 2027
Your objections seem reasonable but I do not understand their implications due to a lack of finance background. Would you mind helping me understand how your points affect the takeaway? Specifically, do you think that the estimates presented here are biased, much more uncertain than the post implies, or something else?

JoshuaBlake 5 May 2024 15:52 UTC
12 points
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on: Now THIS is forecasting: understanding Epoch’s Direct Approach
Thanks—I think this type of careful empirical analysis, and its distillation, is some of the next content on the forum. I found your section on varying parameters particularly helpful for quantifying how sensitive the approach is to these non-empirical inputs.

JoshuaBlake

Ad­vice for cur­rent /​ po­ten­tial PhD students

Advice for current / potential PhD students