Thanks for the comment, Joshua!

I'd caution that, as far as I can tell, the World Bank and Bernstein et al. numbers are basically made up.

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.

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.

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.

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).

1. ^{^}

   According to Open Philanthropy, “GiveWell uses moral weights for child deaths that would be consistent with assuming 51 years of foregone life in the DALY framework (though that is not how they reach the conclusion)”.