I currently work with CE/AIM-incubated charity ARMoR on research distillation, quantitative modelling, consulting, and general org-boosting to support policy advocacy for market-shaping tools to incentivise innovation and ensure access to antibiotics to help combat AMR.
I previously did AIM's Research Training Program, was supported by a FTX Future Fund regrant and later Open Philanthropy's affected grantees program, and before that I spent 6 years doing data analytics, business intelligence and knowledge + project management in various industries (airlines, e-commerce) and departments (commercial, marketing), after majoring in physics at UCLA and changing my mind about becoming a physicist. I've also initiated some local priorities research efforts, e.g. a charity evaluation initiative with the moonshot aim of reorienting my home country Malaysia's giving landscape towards effectiveness, albeit with mixed results.
I first learned about effective altruism circa 2014 via A Modest Proposal, Scott Alexander's polemic on using dead children as units of currency to force readers to grapple with the opportunity costs of subpar resource allocation under triage. I have never stopped thinking about it since, although my relationship to it has changed quite a bit; I related to Tyler's personal story (which unsurprisingly also references A Modest Proposal as a life-changing polemic):
I thought my own story might be more relatable for friends with a history of devotion – unusual people who’ve found themselves dedicating their lives to a particular moral vision, whether it was (or is) Buddhism, Christianity, social justice, or climate activism. When these visions gobble up all other meaning in the life of their devotees, well, that sucks. I go through my own history of devotion to effective altruism. It’s the story of [wanting to help] turning into [needing to help] turning into [living to help] turning into [wanting to die] turning into [wanting to help again, because helping is part of a rich life].
The modelling study has a "costs" section (quoted below), but for what it's worth GiveWell said they "were unable to quickly assess how key parameters like program costs... were being estimated" so I don't think this quote will satisfy you:
Given the Ghana Health Service (GHS)'s dominant role, the government perspective in this analysis included healthcare treatment costs and incremental last mile delivery (LMD) costs. The societal perspective also accounted for externalities such as caregivers’ wage loss and transport costs.
To calculate the total cost for aerial LMD of vaccines, we analyzed Zipline’s monthly operational costs and the depreciation of capital expenditures for the GH4 distribution center in the Western North Region. These were adjusted to 2023 US dollar values, and the corresponding portion attributed to vaccine delivery was determined, resulting in a cost per dose of $0.27.
To estimate the incremental cost of the intervention, we took into account that the impact of aerial logistics on vaccination rates can be explained through either a pure expansion of access (ie, health facilities receiving vaccine doses that they otherwise would not have) or more efficient access (ie, health facilities receiving the same number of vaccine doses they would have otherwise received but in a more timely manner, leading to fewer missed opportunities of vaccination). Anecdotal evidence suggests that the impact is likely a combination of both factors. The distinction is significant when computing costs in an ICER: in the former, aerial logistics LMD cost is an additional expense to the existing supply chain cost for the government, whereas, in the latter, aerial logistics LMD replaces the traditional supply chain cost for transporting those vaccines. ...
Due to the absence of detailed data on traditional LMD, we were unable to differentiate between incremental and replaced doses within the number of doses delivered with aerial logistics during the intervention period. To mitigate the impact of this uncertainty on our estimations, for our primary ICER calculation, we proceeded with the conservative assumption that all doses delivered by aerial logistics during this period were incremental. This approach may inflate our incremental cost estimates but ensures the solidity of our findings amid the well-known ambiguous quality and high variance of the traditional LMD data that were used for illustrative purposes in the sensitivity analysis.
But no input numbers, just methods and a dash of conservatism.
I share your annoyance re: modelling studies. Garbage in garbage out as they say (not accusing Zipline of putting garbage data into their model of course!)
Re: NGOs using trucks and cars unnecessarily, I'm just speculating here but I wonder if it's got a bit to do with the NGOs wanting to attract "top talent" (salary difference being the main attractor but also "you get to ride in a car instead of on a bike" being implicitly part of the "comp package", sort of like how top talent in higher-income countries are lured to prestigious industries by not just pay but "comped stays in nice hotels" or whatever). This paper I read awhile back made me think of that: The unintended consequences of NGO-provided aid on government services in Uganda. It argues that NGOs sometimes "poach" scarce local skilled government workers via higher pay, resulting in various adverse effects, although I guess it's a bit different in this case because the adverse effects happen as a result of the pay structure (NGO workers who would've otherwise distributed health products instead sell household products like soap and fortified oil because they get paid on a per-piece basis).
Ah, I missed this, thanks! And I appreciate the pointer to EarthEnable in particular. Although it looks like their analysis stopped at the shallow level, so maybe no future report...
EarthEnable looks quite impressive by their own lights: 35,000+ "housing solution projects" completed or in progress benefiting 200,000+ people, and over 1,000 jobs created in East Africa (they "developed training curriculum for masons to learn to build our products to earn a livelihood of 2-3x the median income"). I also appreciate how most of their senior team seems local at a glance.
Just posting HLI's chart here for others' benefit:
Quoting their qualifier too:
Note that our task was to bring together all the work that had already been done. All the research had the same output (WELLBYs per dollar) but the inputs were ‘lumpy’: some analyses were much deeper than others. It was out of scope to re-analyse and update all the pre-existing estimates. So take this as the first word on the topic, not the last!
I think you're right in general, you're just pointing to a different thing than Deena is, so maybe tabooing "biodiversity" might be useful here. They're at OP GHD so unsurprisingly the part of conservation loss they care about is human mortality impact.
We are orienting to this issue at the ‘local systems’ level (see below). We acknowledge that many organizations are tackling related issues at the earth systems level (climate change) and individual level (animal welfare). We feel there are important, tractable and neglected strategies that emerge when operating at this level.
This table visualizes the relationships between ecosystems and other aspects of our world and core systems we speak to throughout this proposal.
Quantifying species diversity is an interesting mathematical problem in its own right. Tom Leinster's slides make the case that the three popular measures of species diversity (species richness, Shannon entropy, Gini–Simpson index) all problematically diverge from intuitively-desired behavior in edge cases of consequence, so the formalisation you really want is Hill numbers, which depend on a so-called "viewpoint parameter" q that changes how the former are sensitive to rare species. (Your professed stance corresponds to low q; it'd be useful to know if your interlocutors prefer high q; Tom's charts visualise this.) You can then extend this line of reasoning in ways that affect actual conservation policy.
It could in theory, but OWID's summary of the evidence mostly persuades me otherwise. Again I'm mostly thinking about how the Easterlin paradox would explain this OWID chart:
I'm guessing Easterlin et al would probably counter that OWID didn't look at a long-enough timeframe (a decade is too short), and I can't immediately see what the timeframe is in this chart, so there's that.
Thanks for the links! And for the pics, makes me feel like I'm glimpsing the future, but it's already here, just unevenly distributed. Everything you say jives with both what GiveWell said about Zipline in their grant writeup
Though this is our first engagement with Zipline, there are some early signals that we might be well-aligned as partners. Zipline’s proposal specifically calls out a few elements that are important to GiveWell: a) emphasis on cost-effectiveness , b) plans to establish an M&E framework early on for any potential pilots, and c) interest in evaluation and learning
Interesting, I got the opposite impression from their about page ("4,000+ hospitals and health centers served, 51% fewer deaths from postpartum hemorrhaging in hospitals Zipline serves, 96% of providers report increased access to vaccinations in their area" which I assume means they're already targeting those hard-to-access areas), but of course they'd want to paint themselves in a good light and I'd be inclined to trust your in the field experience far more (plus general skepticism just being a sensible starting point).
Actually your point about a cheap bike being able to carry a lot more stuff makes obvious sense, and so me wonder how Zipline's modelling study in Ghana can claim that their cost per incremental fully immunised child was cheaper than "monthly immunization by mobile teams" which I assume includes dirt bikes.
That's really kind of you Angelina :) I think top-level posting makes me feel like I need to put in a lot of work to pass some imagined quality bar, while quick takes feel more "free and easy"? Also I hesitate to call any of my takes "analyses", they're more like "here's a surprising thing I just learned, what do y'all think?"
I'm not seeing where Deena wrote that biodiversity in general was important?
Both studies suggest that protecting certain animal populations might have large, direct effects on human health that we’re overlooking. But there are good reasons to be cautious. These are outlier results; there isn’t much else in the way of evidence for estimates of this magnitude for the impact of biodiversity loss on human mortality. There’s also the possibility of publication bias. In particular, since both papers come from the same author, this may be driven by a file drawer effect, where a researcher looks at many potential similar cases but the null findings are less likely to see the light of day.
Still, if these effects are real, they could change how we think about conservation. Saving vultures or bats wouldn’t just be about biodiversity—it could also be a form of public health policy.
Deena's post only mentioned "of at least one large RCT underway, with results expected in a few years" without further reference, but on cursory googling it might be the CRADLE trial?
The Cement-based flooRs AnD chiLd hEalth trial is an individually randomised trial in Sirajganj and Tangail districts, Bangladesh. Households with a pregnant woman, a soil floor, walls that are not made of mud and no plan to relocate for 3 years will be eligible. We will randomise 800 households to intervention or control (1:1) within geographical blocks of 10 households to account for strong geographical clustering of enteric infection. Laboratory staff and data analysts will be blinded; participants will be unblinded. We will instal concrete floors when the birth cohort is in utero and measure outcomes at child ages 3, 6, 12, 18 and 24 months.
The primary outcome is prevalence of any STH infection (Ascaris lumbricoides, Necator americanus or Trichuris trichiura) detected by quantitative PCR at 6, 12, 18 or 24 months follow-up in the birth cohort. Secondary outcomes include household floor and child hand contamination with Escherichia coli, extended-spectrum beta-lactamase producing E. coli and STH DNA; child diarrhoea, growth and cognitive development; and maternal stress and depression.
We will report findings on ClinicalTrials.gov, in peer-reviewed publications and in stakeholder workshops in Bangladesh.
While GiveWell doesn't seem to have looked into this specifically, this 2015 review of GiveDirectly mentioned that lack of cement floors was in one of GiveDirectly's two sets of eligibility criteria for its standard campaigns:
Thatched roofs: To date, GiveDirectly has used housing materials to select recipients in all of its standard campaigns, enrolling households who live in a house made of organic materials (thatched roof, mud walls, and a mud floor) and excluding households with iron roofs, cement walls, or cement floors.170 In GiveDirectly's campaigns in Kenya, about 35-45% of households have been eligible based on these criteria, while in Uganda about 80% of households have been found to be eligible.171...
Happier Lives Institute's 2021 annual review did mention cement flooring among the "micro-interventions" they wanted to look into (alongside deworming, cataract surgery, digital mental health interventions, etc), but I haven't seen anything by them since on this, so I assume it didn't pass their internal review for further analysis.
Always enjoy your posts, you tend to have fresh takes and clear analyses on topics that feel well-trodden.
That said, I think I'm mainly confused if the Easterlin paradox is even a thing, and hence whether there's anything to explain. On the one hand there are writeups like Michael Plant's summarising the evidence for it, which you referenced. On the other hand, my introduction to Easterlin's paradox was via Our World in Data's happiness and life satisfaction article, which summarised the evidence for happiness rising over time in most countries here and explain away the Easterlin paradox here as being due to either survey questions changing over time (in Japan's case, chart below) or to inequality making growth not benefit the majority of people (in the US's case).
The reply that Easterlin and O’Connor (2022) make is that Stevenson, Wolfers, and co. are looking over too short a time horizon. They point out that the critique looks at segments of ten years and to really test the paradox requires looking over a longer time period, which is what Easterlin and O'Connor (2022) do themselves. Easterlin and O'Connor (2022) write that they don't really understand why Stevenson and Wolfers are using these short time segments rather than the longer ones.
But the chart for Japan above, which is from Stevenson and Wolfers (2008), spans half a century, not ten years, so Easterlin and O'Connor's objection is irrelevant to the chart.
This OWID chart (which is also the first one you see on Wikipedia) is the one I always think about when people bring up the Easterlin paradox:
But Plant's writeup references the book Origins of Happiness (Clark et al., 2019) which has this chart instead:
So is the Easterlin paradox really a thing or not? Why do the data seem to contradict each other? Is it all mainly changing survey questions and rising inequality? On priors I highly doubt it's that trivially resolvable, but I don't have a good sense of what's going on.
I wish there was an adversarial collaboration on this between folks who think it's a thing and those who think it isn't.
The modelling study has a "costs" section (quoted below), but for what it's worth GiveWell said they "were unable to quickly assess how key parameters like program costs... were being estimated" so I don't think this quote will satisfy you:
But no input numbers, just methods and a dash of conservatism.
I share your annoyance re: modelling studies. Garbage in garbage out as they say (not accusing Zipline of putting garbage data into their model of course!)
Re: NGOs using trucks and cars unnecessarily, I'm just speculating here but I wonder if it's got a bit to do with the NGOs wanting to attract "top talent" (salary difference being the main attractor but also "you get to ride in a car instead of on a bike" being implicitly part of the "comp package", sort of like how top talent in higher-income countries are lured to prestigious industries by not just pay but "comped stays in nice hotels" or whatever). This paper I read awhile back made me think of that: The unintended consequences of NGO-provided aid on government services in Uganda. It argues that NGOs sometimes "poach" scarce local skilled government workers via higher pay, resulting in various adverse effects, although I guess it's a bit different in this case because the adverse effects happen as a result of the pay structure (NGO workers who would've otherwise distributed health products instead sell household products like soap and fortified oil because they get paid on a per-piece basis).