Pretty funny CGD blog post by Victoria Fan and Rachel Bonnifield: If the Global Health Donors Were Your Parents: A (Whimsical) Comparative Perspective. Quoting at length (with some reformatting):

Navigating the global health funding landscape can be confusing even for global health veterans; there are scores of donors and multilateral funding mechanisms, each with its own particular structure, personality, and philosophy. For the uninitiated, PEPFAR, GAVI, PMI, WHO, the Global Fund, UNITAID, and the Gates Foundation can all appear obscure and intimidating. But if your head is spinning from acronym-induced vertigo, fear not! We are here to help you make sense of it all. How, you ask? With a clear method for donor identification: comparing the donors to your parents. So what would happen if the donors were your parents and you asked them for a new car? 

• PEPFAR: Ok, we’ll buy you a new car, but we’re going with you to the dealership and it must be American-made. At least one seat must be devoted to abstinence and the delay of sexual debut. Before you drive the car, you must promise not to support prostitution. Each quarter, you must report how many miles you’ve driven with how many passengers, with a target of 1000 passenger-miles per month.
• President’s Malaria Initiative: We’ve made it very clear that we only support four proven, cost-effective interventions for child rearing: food, clothing, health care, and education. What, do you think money in the Malaria family just grows on trees? Just because HIV/AIDS has a shiny new car doesn’t mean we can afford it.
• UNITAID: We’ve identified pediatric vehicles as a niche market which is currently underserved by the major transport providers. By buying cars for you and all our other children, we are helping to create a pediatric automotive market with new and superior transportation commodities. Prior to our innovative entry into the pediatric vehicle market, most of our potential beneficiaries were getting around using lower-quality forms of transportation, such as bicycles, buses, and walking.
• GAVI: We will purchase and a deliver a car for you from a particular GAVI-approved dealership. However, you must co-finance the purchase with wages from your part-time job. Gas and insurance will require separate applications.
• WHO: Sorry, we haven’t had a car budget in ten years. But we DO have a new set of guidelines on best practices for safe car driving, and a box full of old carfax vehicle reports that you’re welcome to look at any time. Please let us know right away if you experience any engine trouble; regular and reliable reporting allows us to maintain an up-to-date transmission failure surveillance system. And don’t forget to celebrate Vehicle Safety Day on May 11!
• Gates Foundation: Of course, darling, we gave your boarding school plenty of money to buy a car. And since we’re on the Board, we’ll make sure they buy the right car. And you can drive it any time you want…as long as one of us is in the passenger seat to make sure you’re going the right way.
• Global Fund: We’ve reviewed your proposal for a Range Rover and according to Consumer Reports it is a technically capable car for city driving. Here is a $70,000 check for you to go and buy the Range Rover, as discussed in your proposal.

Oliver Kim's How Much Should We Trust Developing Country GDP?, a review of Morten Jerven's 2013 book Poor Numbers: How We Are Misled by African Development Statistics and What to Do About It, makes the same point about GDP as well. Improving data collection in underresourced areas in general seems like a cross-cutting 'cause X'.

Some quotes: 

Hollowed out by years of state neglect, African statistical agencies are now often unable to conduct basic survey and sampling work. Jerven writes:

In 2010, I returned to Zambia and found that the national accounts now were prepared by one man alone… Until very recently he had had one colleague, but that man was removed from the National Accounts Division to work on the 2010 population census. To make matters worse, lack of personnel in the section for industrial statistics and public finances meant that the only statistician left in the National Accounts Division was responsible for these data as well. (pg. x)

Without the staff to collect and analyze survey data, statistical agencies are usually forced to improvise, guessing the size of the economy from population figures, which are themselves extrapolated from censuses that are decades-old.

... I’m haunted by the words of the lone Zambian statistician, sitting in his empty office, who asks Jerven plaintively: “What happens if I disappear?”

Many African states are failing at the basic task of knowing how many people live in their borders—let alone accurately measuring their economic activity. The vast, unobserved informal sector (which includes subsistence farming, and something like 60% of working people) is usually estimated just as a direct function of population.⁵ Lacking direct harvest yields, estimates of agricultural output are often produced using FAO models based on planting-season rainfall data.⁶ Even the minimal task of measuring the goods traveling across borders—in theory, the easiest thing for a sovereign state to accomplish—is occasionally beyond the reach of statistical agencies. Until 2008, landlocked Uganda only collected trade data on goods that eventually passed through the Kenyan port of Mombasa, ignoring the four other countries on its borders.⁷

In the absence of good underlying data, the prevailing approach for GDP in developing Africa can be summarized as:

Income estimates… derived by multiplying up per capita averages of doubtful accuracy by population estimates equally subject to error. (p. 39)

Poor Numbers came out in 2013, attracting a wave of scholarly and policy attention (including by Bill Gates). Once you’ve heard its arguments, it’s virtually impossible to look at a GDP statistic the same way again.

But what actual progress has been made in the statistical capacity of nations?

Seemingly, not much. In late 2014, perhaps in response to Jerven’s book, the World Bank relaunched its website for its Statistical Capacity Indicator—a metric on a 0-100 scale which scores countries based on the strength of their “Methodology”, “Source Data”, and “Periodicity and Timeliness”. But even by this clunky internal metric, progress has been glacially slow: in 2004, the average score for African countries was 58.2; in 2019, it was just 61.4.

Moreover, over six years of an economics PhD, I have never heard of any economist using this statistic. Poor Numbers is well-cited and well-read (at least by Africa specialists), but its lessons about the fundamental unreliability of statistics have largely not been absorbed in how we actually do economics.

It's in Table 3. I do agree this should be visualised as well.

Makes sense. Their analysis treats large donors differently, although they don't mention anything about retention differences vs other pledgers. Given that GWWC say they "often already have individual relationships with them", my guess is it's probably slightly higher.

There's this chart from the What trends do we see in GWWC Pledgers’ giving? subsection of GWWC's 2020-22 cost-eff self-evaluation:

Joel's comment on this is worth reading too.

Agree with the lower bound on fungal burden. For the post you linked I'd signal-boost J Bostock's 7 criticisms too.

I think you're right re: cheap distribution. My guess is it would be hard for a new charity to beat VisionSpring, who have been executing on this strategy for a while and have the resources (~300 staff, $15M grant from MacKenzie Scott, etc), the results to show for it (e.g. 1.9 million eyeglasses distributed last year with 535 partners, etc), and "expansion plans" secured (e.g. their new $70M flagship project to screen 8M workers over the next 5-7 years based on the PROSPER RCT). Their 2022 financial summary (page 17) claims to have distributed 1.52 million eyeglasses for $11.9M in total expenses i.e. ~$7.80 per eyeglasses, nearly half opex (mgmt ops, fundraising, program & sales ops) and ~2/3rds of the remainder program delivery costs, although the expenses were inflated by the delivery of ~1.3 mil "covid safety materials" (PPEs etc) so I'd guess the true figure is closer to $5-6 per eyeglasses all-inclusive. 

I did the same, so I predictably agree-voted. I'm curious if disagree-voters can explain why. 

That's fair, no need to take it. 

The criticism, if there is one, would be that Scott's concept doesn't add anything to the work done by academics

Stuart Armstrong (author of the OP in the link above) seems to think it was academically inspiring, cf. the passage starting with

Academic Moloch

Ok, now to the point. The "Moloch" idea is very interesting, and, at the FHI, we may try to do some research in this area (naming it something more respectable/boring, of course, something like "how to avoid stable value-losing civilization attractors").

The project hasn't started yet, but a few caveats to the Moloch idea have already occurred to me. ...

Not sure if that counts for you.

(I'm not socially tied to Luke in any way. I had the same misconception as you a long time ago, remember reading that comment as clarifying, and thought you would appreciate the share.)