Hello Luke,

I suspect you are right to say that no one has carefully thought through the details of medical career choice in low and middle income countries - I regret I certainly haven't. One challenge is that the particular details of medical careers will not only vary between higher and lower income countries but also within these groups: I would guess (e.g.) Kenya and the Phillipines differ more than US and UK. My excuse would be that I thought I'd write about what I knew, and that this would line up with the backgrounds of the expected audience. Maybe that was right in 2015, but much less so now, and - hopefully - clearly false in the near future.

Although I fear I'm little help in general, I can offer something more re. E2G vs. medical practice in Kenya.

First, some miscellaneous remarks/health warnings on the 'life saved' figure(s):

• The effect size interval of 'physician density' crosses zero (P value ~ 0.4(!)). So with more sceptical priors/practices you might take this as a negative result. E.g. I imagine a typical Givewell analyst would interpret this work as an indication training more doctors is not a promising intervention.
• Both wealth and education factors are much more predictive, which is at least indicative (if not decisive) of what stands better prospects of moving the population health needle. This fits with general doctrine in public health around the social determinants of health, and rhymes with the typically unimpressive impacts of generally greater medical care/expenditure in lottery studies, RCTs, etc.
• Ecological methods may be the best we (/I) have, but are tricky, ditto the relatively small dataset and bunch on confounds. If I wanted to give my best guess central estimate of the impact of a doctor, I would probably adjust down further due to likely residual confounding, probably by a factor of ~~3. The most obvious example is physician density likely proxies healthcare workers generally, and doctors are unlikely to contribute the majority of the impact of a 'marginal block of healthcare staff'.
• I typically think the best use of this work is something like an approximate upper-bound: "When you control for the obvious, it is hard to see any impact of physicians in the aggregate - but it is unlikely to be much greater than X".
• The 'scaling' effect of how much returns of physicians diminish as their density increases is a function of how the variables are linearized. Although this is indirectly data-driven (i.e. because the relationship is very non-linear, you linearise using a function which drives diminishing returns), it is not a 'discovery' from the analysis itself. 
• Although available data (and maybe reality) is much too underpowered to show this, I would guess this scaling overrates the direct impact of medical personnel in lower-income settings: advanced medical training is likely overkill for primary prevention (or sometimes typical treatment) of the main contributors to lower-income countries burden of disease (e.g., for Kenya). If indeed the skill-mix should be tilted away from highly trained staff like physicians in low-income settings versus higher-income ones, then there is less of outsized effect of physician density. 

Anyway, bracketing all the caveats and plugging in Kenya's current physician per capita figure into the old regression model gives a marginal response of ~40 DALYs, so a 15x multiplier versus the same for the UK. If one (very roughly) takes ~20-40 DALYs  = 1 'life saved', each year of Kenyan medical practice roughly roughly nets out to 5-10k USD of Givewell donations. 

As you note, this is >>10% (at the upper end, >100%) of the average income of someone in Kenya. However, I'd take the upshot as less "maybe medical careers is a good idea for folks in lower-income countries", but more "maybe E2G in lower-income countries is usually a bad idea" as (almost by definition) the opportunities to generate high incomes to support large donaions to worthy causes will be scarcer. 

Notably, the Kenyan diaspora in the US reports a median houshold income of ~$61 000, whilst the average income for a Kenyan physician is something like $35 000, so 'E2G + emirgration' likely ends up ahead. Of course 'Just move to a high income country' is not some trivial undertaking, and much easier said than done - but then again, the same applies to 'Just become a doctor'.

I totally agree. The "western-by-default" messaging that sometimes occurs in EA spaces not only hurts the efficiency of the movement, but also likely turns some people off who otherwise would have joined the community. If EA is truly about viewing all of humanity as equal, then we need to make sure our communication addresses all of humanity equally, not just westerners. 

I live in a middle income country where most people are still relatively poor compared with people in developed world, although not as bad as the global extreme poor. So the uttermost priority for people here are to lift themselves out of poverty. When I occasionally mention that I gave money to charities, everyone thinks that I'm utterly insane. This makes me realize that EA is always going to have a limited audience, i.e., people who live in developed country who have a relatively comfortable life.