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JustinGraham54
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Hi! I'm Justin - I run Taimaka. We're an EA org, but pretty quiet on the forum - keep meaning to get around to writing up something about our work, but hasn't happened yet, so this is a good excuse to say hello!

This is a good question, and our cost-per-life-saved figure is also obviously a bold claim, so I'll share a bit about our thinking here. One disclaimer I'll make for clarity is that while our work is supported by GiveWell, our cost-effectiveness model is our own and the thoughts I'm sharing here are my own - I don't speak for GiveWell's team and their views. Our CEA is built off of their past work on acute malnutrition, but the end results + claims are ours. 

Generally, the way I think about our model and our $1.6k per life saved estimate is that this is the most accurate + true estimate we have for our program, but that you should probably read this estimate as having higher error bars surrounding it than estimates for current GiveWell top charities. I think there are two primary reasons for this:

  1. Taimaka is a younger charity with a shorter track record. We're extrapolating from a smaller data set than an organization like, say, New Incentives. Our costs could change (up or down) as we grow over the next few years, or things like the baseline conditions in Gombe State (like prevalence or coverage of acute malnutrition and treatment) where we work could change in ways we are not expecting. We try to build some of this into the model, like how we expect costs to change, but we are extrapolating. Our model is accurate to our current program, but things may change over time and the model may need to be revised.
  2. The evidence base for acute malnutrition treatment is more limited than we'd like it to be/for current top charities. There is no direct causal evidence (in the form of RCTs) for the mortality reduction benefits from acute malnutrition treatment, because treatment was developed before RCTs/clinical trials became popular in the 2000s, and now it's considered unethical to withhold treatment that works from kids to study treatment effect on mortality. Instead, GiveWell (and Taimaka by extension) model mortality reduction through a meta-analysis of historical data that provides information on mortality rate by anthropometric status, combined with data on change in anthropometric status from before/after treatment. This is just a worse evidence base than the RCTs we have for bed nets for instance, and so brings in higher error bars.
    1. We're working on some studies now to supplement this evidence base, but it's going to be a while before those bear fruit.

Hopefully this is helpful! In summary: we take this figure seriously, and stand by our modeling. We haven't put our thumb on the scales anywhere to make this number lower, it's the true result of a good faith effort to adapt GiveWell's model of other acute malnutrition treatment programs to our own. That said, expect higher error bars in this than you would in models for current top charities, both because of vagaries in Taimaka being younger + because of limitations in what we currently know about acute malnutrition treatment. If you're willing to accept that higher level of risk, I think Taimaka is a great donation option to do a lot of good, potentially even more cost-effectively than other places. Happy to have a call to chat this through in more detail if you'd like, feel free to shoot me an email! (My first name at taimaka.org). 

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JustinGraham
Always happy to answer questions! Thanks for your support + belief in what we do! Means a lot (which sounds very "charity language" but really is true for us and for the other people running charities hanging out around here). 
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Cause prioritizationEffective givingGlobal health & developmentCharity evaluationCost-effectiveness analysis
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Do you think this charity is legitimate? It seems like they are but I'd like your opinion before I donate a few thousand more dollars to them. https://taimaka.org/

They say they can save a human life for about 1600$ using the same formula as givewell. What do you think? Other effective altruist charities can't save a life for less than 3500$ and usually more like 5000 $

 

I've read some research on them https://www.happierlivesinstitute.org/taimaka-summary/ but it was more focused on how they improve lives I'm curious about whether or not they will save a life of someone who would have otherwise died for 1600 ish dollars. 

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JustinGraham54
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Hi! I'm Justin - I run Taimaka. We're an EA org, but pretty quiet on the forum - keep meaning to get around to writing up something about our work, but hasn't happened yet, so this is a good excuse to say hello!

This is a good question, and our cost-per-life-saved figure is also obviously a bold claim, so I'll share a bit about our thinking here. One disclaimer I'll make for clarity is that while our work is supported by GiveWell, our cost-effectiveness model is our own and the thoughts I'm sharing here are my own - I don't speak for GiveWell's team and their views. Our CEA is built off of their past work on acute malnutrition, but the end results + claims are ours. 

Generally, the way I think about our model and our $1.6k per life saved estimate is that this is the most accurate + true estimate we have for our program, but that you should probably read this estimate as having higher error bars surrounding it than estimates for current GiveWell top charities. I think there are two primary reasons for this:

  1. Taimaka is a younger charity with a shorter track record. We're extrapolating from a smaller data set than an organization like, say, New Incentives. Our costs could change (up or down) as we grow over the next few years, or things like the baseline conditions in Gombe State (like prevalence or coverage of acute malnutrition and treatment) where we work could change in ways we are not expecting. We try to build some of this into the model, like how we expect costs to change, but we are extrapolating. Our model is accurate to our current program, but things may change over time and the model may need to be revised.
  2. The evidence base for acute malnutrition treatment is more limited than we'd like it to be/for current top charities. There is no direct causal evidence (in the form of RCTs) for the mortality reduction benefits from acute malnutrition treatment, because treatment was developed before RCTs/clinical trials became popular in the 2000s, and now it's considered unethical to withhold treatment that works from kids to study treatment effect on mortality. Instead, GiveWell (and Taimaka by extension) model mortality reduction through a meta-analysis of historical data that provides information on mortality rate by anthropometric status, combined with data on change in anthropometric status from before/after treatment. This is just a worse evidence base than the RCTs we have for bed nets for instance, and so brings in higher error bars.
    1. We're working on some studies now to supplement this evidence base, but it's going to be a while before those bear fruit.

Hopefully this is helpful! In summary: we take this figure seriously, and stand by our modeling. We haven't put our thumb on the scales anywhere to make this number lower, it's the true result of a good faith effort to adapt GiveWell's model of other acute malnutrition treatment programs to our own. That said, expect higher error bars in this than you would in models for current top charities, both because of vagaries in Taimaka being younger + because of limitations in what we currently know about acute malnutrition treatment. If you're willing to accept that higher level of risk, I think Taimaka is a great donation option to do a lot of good, potentially even more cost-effectively than other places. Happy to have a call to chat this through in more detail if you'd like, feel free to shoot me an email! (My first name at taimaka.org). 

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wibnlypando478
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Thank you very much Justin. I really appreciate everything you're doing and your response. This does make me feel more comfortable about donating and I think I'll make another donation soon so I can save a second life. 

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JustinGraham6
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Always happy to answer questions! Thanks for your support + belief in what we do! Means a lot (which sounds very "charity language" but really is true for us and for the other people running charities hanging out around here). 

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NickLaing13
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My 2 cents, from decent quality second hand information, yes! Tamaika is a  legitimate charity that is doing fantastic work treating malnutrition cost-effectively.

I'll also piggyback off this great question and @JustinGraham's fantastic response below and point out there are many smaller orgs that have performed their own cost-effectiveness analysis (Introducing Lafiya Nigeria, Tamaika etc.) and judge ourselves to be cost-effective compared to top  GiveWell orgs - without having the direct RCTs on the exact work we do to be able to qualify for GiveWell's top charity list, nor necessarily having external bodies assess us. (Rethink did an analysis for Lafiya). I would think almost all CE charities will have an analysis along these lines performed in the first few years of operation, and some that weren't judged to be cost-effective might be shut down.

Unfortunately like @JustinGraham says, doing direct RCTs on the life-saving evfect of our work might be close-to-impossible now either for ethical reasons, or because the size of study needed these days to detect mortalty differences is very large, so studies powered for mortality have become rare. This is largely because far less kids die than in the past  - which is great. This doesn't mean though that we can't do high quality research on proxy measures though (for us at OneDay Health quality of care and healthcare access) which we are currently doing in collaboration with top universities.

I'm co-founder of OneDay Health and we've done a cost-effectiveness analysis which might put us between $800 and $1800 per life saved. Early stage analysis (and self performed) analysiss though often grossly overestimates cost-effectiveness, so this cost-effectiveness would likely be hugely reduced if others or GiveWell did their own analysis.
 

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