Interesting analysis! I don't have any experience conducting such analyses myself, but I was curious which interventions are considered part of pandemic preparedness when calculating the total cost. Does it also include indirect costs, such as research funding or capacity-building projects?
Thanks for the relevant question, Dhruvin!
Below is the relevant section from Bernstein et. al 2022. I have bolded the 6 measures included in the annual cost of 20 G$.
THE COSTS OF PRIMARY PREVENTION
Previously, we provided preliminary estimates of how much primary prevention might cost (9). We presented six estimates of annual costs. We estimated $19 billion to close down China’s wildlife farming industry, based on a Chinese report (76). A total of $476 million to $842 million were needed to reduce spillover from livestock based on (77) and the World Bank One World One Health farm biosecurity intervention program (78). The report provided the cost of implementing enhanced biosecurity for zoonoses around farming systems in low to middle income countries, and we extrapolated those data to the 31 countries with high risk of wildlife viral spillover risk from (65, 66).
The other four were our estimates for viral discovery ($120 million to $340 million), early detection and control ($217 million to $279 million), wildlife trade surveillance ($250 million to $750 million), and programs to reduce spillover from livestock ($476 million to $852 million). The most complicated estimate was reducing deforestation by half ($1.53 billion to $9.59 billion). These broad-brush estimates provide essential insights into the relative magnitude of each task. Here, we provide more details of the underlying issues determining costs and the challenges of implementation.
These kinds of analyses are generally a waste of time, because the people performing them have no idea about how outbreaks are identified and controlled. They have good intentions, but outbreak control isn't a simple linear world where you know all the variables and you can work with averages. As a result, these estimates tend to have little basis in reality.
Take the numbers from Berstein et al - they're patently ridiculous! "$19 billion to close down China’s wildlife farming industry". Never mind the credibility of the $19bn figure... who's going to tell China to shut down anything? Who think's the CCP are just going to do what they're told? What kind of a plan is this??
If you want to do a cost/benefit analysis, you need to do it by strategy. And there are lots of different strategies.
For example, what's the cost/benefit of a rapid elimination strategy? What's the cost/benefit on having wastewater / sewerage / environmental / random testing in major international ports of entry? What's the cost/benefit of investing in rapid testing manufacturing capacity? Or of training HCWs to implement the strategy?
If you respond quickly, you can reduce the size of the problem by orders of magnitude, and therefore reduce the costs of resolving it by orders of magnitude too. So where does that appear in the analysis? Nowhere, because these kinds of analyses don't allow for it. Instead, they just make vague assumptions about reducing healthcare costs, which is totally unsatisfactory.
I've tried to explain this before...
https://forum.effectivealtruism.org/posts/utE4WqYjjmYDwoiuJ/pandemicriskman-s-quick-takes#u2JxaKrmfJF4hbfh5
Thanks for the comment!
I took Millett & Snyder-Beattie 2017's and Bernstein et. al 2022's numbers at face value, but they are far from rigorous estimates, and I would agree better modelling is needed.
Take the numbers from Berstein et al - they're patently ridiculous!
Sidenote. I would not be surprised if their numbers are very off, but I think it is better to avoid terms like "ridiculous", which are confrontational, and therefore can make thinking clearly more difficult.
Interesting! This is a very surprising result to me because I am mostly used to hearing about how cost effective pandemic prevention is and this estimate seems to disagree with that.
Shouldn't this be a relatively major point against prioritizing biorisk as a cause area? (at least w/o taking into account strong long termism and the moral catastrophe of extinction)
Not really. This post's cost-effectiveness calculation was done at the cause area level, so it's an average of many interventions of highly varying cost-effectiveness, while GW top charities' cost-eff are evaluated at the (org-specific) intervention level.
Thanks for the comment, Jacob!
This is a very surprising result to me because I am mostly used to hearing about how cost effective pandemic prevention is and this estimate seems to disagree with that.
Note that the cost-effectiveness of epidemic/pandemic preparedness I got of 0.00236 DALY/$ is still quite high. The value of a statistical life in high income countries is around 1 to 10 M$, which, for 51 DALY averted per life saved[1], leads to 5.10*10^-6 (= 51/(10*10^6)) to 5.10*10^-5 DALY/$ (= 51/10^6), i.e. 0.216 % (= 5.10*10^-6/0.00236) to 2.16 % (= 5.10*10^-5/0.00236) of my estimate for the cost-effectiveness of epidemic/pandemic preparedness.
Shouldn't this be a relatively major point against prioritizing biorisk as a cause area?
Not so much for prioritising global health and development over biorisk, since GiveWell's top charities being 4.21 times as cost-effective is not much considering uncertainty in my estimates. However, I would say definitely so for prioritising animal welfare over biorisk.
(at least w/o taking into account strong long termism and the moral catastrophe of extinction)
It is unclear to me whether such considerations would lead to prioritising biorisk, even under expected total hedonistic utilitarianism (which I strongly endorse).
Note that the cost-effectiveness of epidemic/pandemic preparedness I got of 0.00236 DALY/$ is still quite high.
Point well-taken.
I appreciate you writing and sharing those posts trying to model and quantify the impact of x-risk work and question the common arguments given for astronomical EV.
I hope to take a look at those more in depth some time and critically assess what I think about them. Honestly, I am very intrigued by engaging with well informed disagreement around the astronomical EV of x-risk focused approaches. I find your perspective here interesting and I think engaging with it might sharpen my own understanding.
:)
Thanks, Jacob! That is nice to know.
My calculations are in this Sheet.
I Fermi estimate the cost-effectiveness of epidemic/pandemic preparedness of 0.00236 DALY/$ multiplying:
The epidemic/pandemic deaths per human-year from 1500 to 2023 of 1.98*10^-4, which is the ratio between 160 M epidemic/pandemic deaths, and 808 G human-years from Marani et. al 2021[1].
Relative to epidemic/pandemic preparedness, I calculate:
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.
Thanks for the comment, Joshua!
Because we do not know the relative reduction in the expected annual deaths caused by their proposed measures, right? I guess their values are optimistic, such that GiveWell's top charities are more than 4.12 times as cost-effective.