@Justin Sandefur I absolutely love this post, and am surprised there isn’t more positive Karma!
First I’d like to thank (as a public health guy working in healthcare in Uganda) the American people on the forum for all your taxes you have poured into PEPFAR. This program has been one of the great successes of the late 20th/21st century, and required a rare kind of large scale commitment and thinking that is vanishingly rare. Americans should feel proud that your tax dollars achieved so much more than they would have spent locally, an incredible gift for the poorest region of the world.
I strongly agree with most of your article, and only have a couple of additional reflections
Feasibility, easy logistics and scalability is PART of cost-effectiveness analysis, not a extra sideline. When effective altruists think of “tractability”, I often don’t see enough focus on whether this can be easily rolled out and achieved on the ground, in the country concerned. This is largely because people doing calculations aren’t ops people. That “single pill which could save millions of lives”
My impression is that these cost effectiveness analysis heavily underrated the importance of ARVs in stopping the spread of HIV, If you are taking ARVs then you hardly spread HIV at all. This stopping the spread has actually been more important from a public health and cost effectiveness perspective than the life saving effect of the individuals taking the ARVs. This effect can in a sense be compared with vaccination in terms of prveventing the diseasel I think this plus the overestimate of long term ARV cost were the main factors which led these analysis to grossly underestimate the cost effectiveness.
If I recall, it was only really in the 2010s, following the release of this study (catchily named HPTN 052), that we realised that ART/ ARV was so effective in stopping HIV transmission, so I think that was a justifiable oversight.
Assuming that prices will remain constant seems to be a genuine issue—I think we need to think about this more when we look at cost-effectiveness generally—but I have an inkling as to why this might be common.
In Mead Over’s (Justin’s colleague) excellent course on HIV and Universal Health Coverage, we modelled the cost effectiveness of ART compared to different interventions. The software package involved constant costs for ART (and second line ART) as a default setting, and didn’t assume that there would be price reductions. I didn’t ask why this was, but after adding price reductions to the model for my chosen country (Chad), I realised that the model then incentivises delaying universal ART within a country, and instead focusing on other interventions which are less likely to decrease in cost over time.
Delaying might be wise in some contexts, but I’m sure many health ministers are just looking for excuses to delay action (letting other countries bring the price down first), so politics doubtless plays a role.
Yes I wasn’t blaming economists at all, just emphasising a couple of reasons why they got it wrong. I still think its good to build in price drops into a model—when we model we should try and most accurately estimate the situation, not try and fudge it to support our position and second guess the political game.
Herd immunity is a threshold effect. Since the analyses (correctly!) said that few people would receive treatment, it doesn’t matter whether the treatment stopped spread, it would have only small effect on the analysis.
Hey Douglas I might be missing something, but the vast majority of people ended up getting HIV treatment, so how was that a correct part of the analysis?
@Justin Sandefur I absolutely love this post, and am surprised there isn’t more positive Karma!
First I’d like to thank (as a public health guy working in healthcare in Uganda) the American people on the forum for all your taxes you have poured into PEPFAR. This program has been one of the great successes of the late 20th/21st century, and required a rare kind of large scale commitment and thinking that is vanishingly rare. Americans should feel proud that your tax dollars achieved so much more than they would have spent locally, an incredible gift for the poorest region of the world.
I strongly agree with most of your article, and only have a couple of additional reflections
Feasibility, easy logistics and scalability is PART of cost-effectiveness analysis, not a extra sideline. When effective altruists think of “tractability”, I often don’t see enough focus on whether this can be easily rolled out and achieved on the ground, in the country concerned. This is largely because people doing calculations aren’t ops people. That “single pill which could save millions of lives”
My impression is that these cost effectiveness analysis heavily underrated the importance of ARVs in stopping the spread of HIV, If you are taking ARVs then you hardly spread HIV at all. This stopping the spread has actually been more important from a public health and cost effectiveness perspective than the life saving effect of the individuals taking the ARVs. This effect can in a sense be compared with vaccination in terms of prveventing the diseasel I think this plus the overestimate of long term ARV cost were the main factors which led these analysis to grossly underestimate the cost effectiveness.
More global health posts please!
If I recall, it was only really in the 2010s, following the release of this study (catchily named HPTN 052), that we realised that ART/ ARV was so effective in stopping HIV transmission, so I think that was a justifiable oversight.
Assuming that prices will remain constant seems to be a genuine issue—I think we need to think about this more when we look at cost-effectiveness generally—but I have an inkling as to why this might be common.
In Mead Over’s (Justin’s colleague) excellent course on HIV and Universal Health Coverage, we modelled the cost effectiveness of ART compared to different interventions. The software package involved constant costs for ART (and second line ART) as a default setting, and didn’t assume that there would be price reductions. I didn’t ask why this was, but after adding price reductions to the model for my chosen country (Chad), I realised that the model then incentivises delaying universal ART within a country, and instead focusing on other interventions which are less likely to decrease in cost over time.
Delaying might be wise in some contexts, but I’m sure many health ministers are just looking for excuses to delay action (letting other countries bring the price down first), so politics doubtless plays a role.
Great insight Jack!
Yes I wasn’t blaming economists at all, just emphasising a couple of reasons why they got it wrong. I still think its good to build in price drops into a model—when we model we should try and most accurately estimate the situation, not try and fudge it to support our position and second guess the political game.
But perhaps that’s naive ;).
Herd immunity is a threshold effect. Since the analyses (correctly!) said that few people would receive treatment, it doesn’t matter whether the treatment stopped spread, it would have only small effect on the analysis.
Hey Douglas I might be missing something, but the vast majority of people ended up getting HIV treatment, so how was that a correct part of the analysis?
How do you know how many people got treatment? I don’t see any numbers in this post or its sources.