Country Director @ OneDay Health
5410 karmaJoined Oct 2018Working (6-15 years)Gulu, Ugandaonedayhealth.org



I'm a doctor working towards the dream that every human will have access to high quality healthcare.  I'm a medic and director of OneDay Health, which has launched 35 simple but comprehensive nurse-led health centers in remote rural Ugandan Villages. A huge thanks to the EA Cambridge student community  in 2018 for helping me realise that I could do more good by focusing on providing healthcare in remote places.

How I can help others

Understanding the NGO industrial complex, and how aid really works (or doesn't) in Northern Uganda 
Global health knowledge


After reading a bit more, one potential issue here is that most of the white sorghum and cassava processed by this project (Anthony can correct me if I'm wrong) will be used for making alcohol, which could cause negative externalities through increasing alcohol production or reducing price, although this is hard to measure.

There could also be more local brewing as well using these crops.

Anthony what do you think about this potential negative to selling sorghum to the alcohol companies?

@Thomas Kwa in my eyes this is a hugely insightful (perhaps even spectacular) response, thanks for taking the time to think about it and write it. Perhaps consder writing a full post with these kinds of insights about benefits of CEAs.

That is If you can stomach spending more time away from your real job making sure that we still exist in 50 years to even talk about GHD ;).

Perhaps then in this case you just don't agree or disagree when it's 50/50? Looking at it now I also don't think my little CEA is plausible, I do think it perhaps got taken a bit too seriously though :D!

I also probably "disagree" with my analysis

Disclaimer I don't know much about the HPMOR thing - for example I didn't know it only tangentially plugged EA. I was just giving a 2 minute example of the kind of analysis you might do (obviously with better info then I had), and that it is possible to do that CEA. I wasn't trying to justify the grant at all my apologies if it came across that way!

Also I don't think this post is getting that hostile a response?

I understand the sentiment but disagree. For global health interventions, cost effectiveness analysis is doable and adds value. Most CE orgs and other aspirational cost effective orgs like my own have done some form of CEA as part of making their case

For Whytham Abby and Harry potter fan fiction that may be more difficult to do.

Although I think there should be far more CEAs across all fields. Like for Harry Potter giveout I would have done something like (obviously this is full hack)...

DISCLAIMER: I'm not saying this actual BOTEC is meaningful, I'm just giving it as an in example that these kind of CEAs are possible.

650 Students given books, I assume that of these 100-300 of these students will read them, and 0-5 will change their life trajectory towards giving or altruism to a small degree counterfactually due to the book. 0 to 2 will give 50,000 to 500,000 more over their lifetime and 0 to 5 will change their life direction and save 1 more life than they would have otherwise.

So cost effectivenss might be between 0 x $50,000 = 0 raised + 0 x 1 = 0 lives saved  and 500,000 x 2 = 1,000,000 dollars and 1 x 5 lives saved.

So the book handout might be somewhere between completely useless and raising $1,000,000 extra dollars for EA causes and saving 5 lives (I don't stand by this analysis, it's just a brief hack)

So compared with saving 6 children with nets it might be comparable-ish based on my 2 minute math. This kind of math might also have been done and not shared in the grant review!

Again, a disclaimer that I'm not trying to justify the grant here, just mocking up the basic mechanics of the kind of botec you could do.

Hey Anthony

I've changed my mind a bit. I think you're right you aren't trying to exaggerate the stats - UBOS is the problem here more than the media or anyone else. I'm now going to have to consider UBOS statisticians non-serious, which is quite problematic (I might even write a post about this given how terrible their work has been here). Thanks for sending me that video - others should watch it too so you can see what I mean. It blew my mind that the "statisticians" who as you say should be the best in the country, appear not to understand their own survey.

They srart with this bizarre statement

"The proportion of people who are poor increases from 8 million to 8.3 million people"

Then it gets worse from there...

UBOS makes at least 3 completely false statements in that video, compared to their official report.

To reiterate one more time, the UBOS report states extreme poverty rates in one part of the report in 2019/2020 at 66.7% in Acholi, 65.7% in Karamoja, and 29.4% in Busoga. Because the population in Busoga is so much higher than either Acholi or Karamoja (more than double the population), the Busoga region has the highest total number of extremely poor people of any region in the country, which is where the confusion comes in. So Busoga region itself is less poor than other parts of Uganda, even though it has a higher total number of poor people - not the easiest thing to understand.


I would love to have a chat to discuss this more if you have time today or anther day, I'll send you a message with my phone number.


Thanks Anthony.

I think the confusion is coming in terms of number of people vs. percentage. A couple of those news articles were confused at the meaning of some of the statistics. Uganda news sources are notoriously unreliable when reporting statistics. That watchdog article for example completely misrepresents the statistics.

The karamoja region has a low overall population but far higher extreme poverty rates than busogoa in all the surveys you shared. That would make most people consider it the poorest region. I don't think you'd find any serious statistician who would consider busoga to be "poorer" or to have a higher poverty rate than places like karamoja. I'm not sure if you've been to karamoja, but the free yours i have been there it really shocked me as the level of poverty really seems on a different level from other places.

The population of busoga is high, so it has the highest raw number of poor people in the country, while poverty rates as a percentage are lower than some other regions. I think that's what caused some of the confusion here.

This isn't too say busoga doesn't have a lot of poverty, it remains one of the poorest areas of the country and that point of yours still stands correct.

I think it's important though to be super careful how we frame our statistics so we don't exaggerate, which can help built trust in our argument in general.

Hey Anthony, a quick question (I might comment more later)

"In short, while Uganda as a country is the very last in Sub Saharan Africa in terms of poverty reduction, our region Busoga is the worst in Uganda, and even in Busoga, our 2 twin districts Kamuli & Buyende, being the remotest, are simply the most miserable." 

Any poverty scale of Uganda will show the Karamoja region being the poorest - I'm not saying Kamuli and Buyende are doing well, but any scale will show the region of Karamoja being far poorer than Busoga, with at least 10 districts of Karamoja faring far worse, an often other Northern Districts faring worse than Kamuli and Buyende as well. Could you show me a poverty rating that rates Busoga as the poorest region or Kamuli and Buyende as among the poorest districts in Uganda?


Thank Jamie, I think cause prioritisation is super important as you say, but I don't think its as neglected as you think, at least not within the scope of global health and wellbeing. I agree that the substance of your the 3 part list being important, but I wouldn't consider the list the best measure of how much hard cause prioritisation work has been done. It seems a bit strawman-ish as I think there are good reasons (see below) why those "exact" things aren't being done. 

First I think precise ranking of "cause areas"is nearly impossible as its hard to meaningfully calculate the "cost-effectiveness" of a cause, you can only accurately calculate the cost-effectiveness of an intervention which specifically targets that cause. So if you did want a meaningful rank, you at least need to have an intervention which has  probably already been tried and researched to some degree at least.

Secondly I think having public specific rankings has potential to be both meaningless and reputationally dangerous.  I think clustering the best interventions we know of and sharing the estimated cost effectiveness is fantastic (like Givewell, 80,000 hours, CEARCH and Copenhagen do), but I don't think adding ranked specificity is very helpful because....

  1. Uncertainty is so high and confidence intervals so wide in these calculations that specific rankings can be fairly meaningless. When all confidence intervals for interventions overlap, I think providing a specific ranking can be almost dishonest
  2. Specific public rankings for causes/interventions has the potential downside of being inflammatory and unhelpful for the effective altruism movement. We've already seen some obvious backlash and downside of the big plug for working towards AI safety being  put forward as something like "the most important"  intervention. Imagine if orgs were publicly pushing seemingly concrete rankings? Much of the public and intellectual world is likely to misunderstand the purpose of it and criticise, or even understand well and criticizse...

I think that 80,000 hours, Open Phil and CEARCH do the substance what you are looking for pretty well and put a lot of money and hours into it - I don't think hard work in this area is "surprisingly rare" I'm not sure if adding a whole lot more organisations here would achieve much, but there might be more room for efforts there!

Also I personally think  that GiveWell might  do the most work which achieves the substance of what you are looking for within global health and wellbeing. They are devoted to finding the most cost effective interventions in the world that exist right now. Their "top charities" page is in some ways a handful of what they think are the "no 1" ranked interventions. Yes they only consider interventions with a lot of evidence behind them and are fairly conservative but I think it achieves much of the substance of your 3 steps.

Also like you mentioned the Copenhagen Consensus also does a pretty good job of outlining what they think might be the 12 best interventions (best things first) with much reasoning and calculation behind each one. This is not ft off a straight rank

I'd be interested to hear what you think might be the upsides of "ranking" specifically vs clustering our best estimates at effective cause areas/interventions. 

I'd be interested to get comment from @Joel Tan here as he and the CEARCH team have probably considered this question more than most of us

Interesting point thanks!

Thanks Bella, this has crossed my mind and definitely updates me towards dairy farmed cows in New Zealand being more likely to be net negative. I'm not sure whether the veal thing happens in New Zealand though I'll look into it.

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