Thanks for writing this post, and the others, on your experience with Alvea - really interesting reading.

I think the thing that is most impressive to me is that you stopped before you ran out of money and returned money to investors. 

That, in my experience, is extremely unusual in the charitable/not for profit sector... where people often keep going with projects that in their heart of hearts they know are not having much or any impact.

Do you see a realistic prospect for any state with nuclear weapons giving them up? 

Either unilaterally or as part of some kind of agreement?

Thanks for writing this - I really enjoyed reading through it, and definitely value hearing from someone with clinical experience of treating patients with mental illnesses.

Speaking for myself, I find the DALY framework helpful in thinking about estimating the health burden of diseases, but definitely don't see it as the be all and end all. 

Likewise Nigeria: https://www.reuters.com/world/africa/nigeria-regulator-grants-approval-oxfords-malaria-vaccine-2023-04-17/

Thanks for the explanation, definitely agree that there are some big limitations on looking at careseeking behaviour in that way. No perfect solution but possibly excluding malaria cases as they are so seasonal would be appropriate, or if you can collect baseline data for a year then you can compare month to month. 

I think existing cost-effectiveness studies might be something you can mine to get to DALY/case... for instance, this study here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757489/#!po=51.5625 

suggests that in their intervention, treating an additional 124 cases of diarrhoea = saving almost 5 DALYs (if my quick skim of table 3 is right). That's modelled I think, but might be a good additional datapoint.

Great to see analysis like this on the forum, and I would love for more charities to try to lay out their impact like this.

I'm struggling a bit to get my head around this bit and wonder whether an alternative approach might work better (or maybe I'm just misunderstanding it):
"We used the average Global burden of disease DALY burden per patient in Uganda to estimate the DALY benefit of treating individual patients. This average includes everyone who suffered from each disease in Uganda, whether they were treated correctly, poorly or not at all. This accounts somewhat for what might have happened if we hadn’t treated the patient and avoids the counterfactual of assuming that patients would have not been treated without us."

I think the main pathways for impact from your model are (please add if I've missed something):
1) reaching patients who otherwise would have missed out on care
2) improved timeliness of care (probably quite a big deal for malaria, maybe less so for family planning)
3) improved quality of care vs. alternative (unclear whether you are claiming this or not, I could easily believe this is a big factor if the alternative is faith healers or traditional medicine but less so if you think govt clinics are similar standard)

Estimating the proportion of 1) is crucial I think. 

One way of generating more evidence would be a baseline of careseeking frequency from health facilities before you establish your centre. If it is 2 visits/year/family before and 4 visits/year/family after - that gives you a reasonable sense of how much additional access you are providing. It sounds like you might already have some of that data too.

So (made up numbers) if we were just thinking about malaria patients... say there are 10 per month, we could assume that 5 of those are 'additional' ones vs. counterfactual with no facility-> 100% of your treatment benefit is counted. The other 5 would have gotten slower care/poorer quality care -> 50% of your treatment benefit is counted.

Patients will also benefit from reduced travel cost. I think you could model that as just the equivalent to a givedirectly donation with no overhead probably. Time savings for patients could be substantial also, I imagine for rural people who need to plant crops/harvest this could be a big factor.

Thanks for the writeup!