Elie Hassenfeld: Hey everyone, this is Elie Hassenfeld, GiveWell's co-founder and CEO.

Today I'm going to be talking to Erin Crossett, who leads our water programs, about a grant we made to a program called WASHmobile, which focuses on water, sanitation, and hygiene to address the problem of child deaths from diarrhea.

And child deaths from diarrhea are a massive problem. Diarrhea is one of the leading causes of under-five child deaths globally. More than 400,000 children die every year from diarrhea, and so this is a problem that needs attention. GiveWell has directed funds to programs that support oral rehydration solution and zinc, and that's one way that we've attempted to address this very large problem.

And then the program that we'll talk about today, WASHmobile, is another program that has had, in a couple trials, extremely large effects. You know, these large effects lead us to a big question. We, on one hand, see this program as [00:01:00] extremely promising, and we're excited about supporting it, but also there's a lot of uncertainty about how this program will succeed, whether it will succeed when it is moved out of the research setting and into a real-world context implemented by normal program implementers rather than researchers.

There's also a big question about this program because we're supporting it in two extremely fragile contexts, in Eastern DRC and in South Sudan. These are places that have very high burden of diarrheal disease, and therefore the potential impact of this program is very high. But because these locations are so fragile, it's very challenging to implement a program effectively.

And so because of that, you know, this program is sort of different than the normal bread and butter that you might expect from GiveWell. You know, we've expanded the scope of what we do significantly over time, but still the stereotypical GiveWell program is one where there's substantial evidence that a program works. There's also an implementer that has a [00:02:00] long track record of implementing that program effectively, and we direct funds to scale it up.

This is a case where the program is very promising, and we think it really might work, but we have major questions about how well it will work, especially in the context that we are supporting it in. And so, therefore, learning is a major goal of this grant. In DRC, we're supporting a randomized control trial alongside our funding, and in South Sudan, we're supporting other evaluation so that we can determine whether this program is effective and whether we can and should continue to scale it up further.

And so in some sense, you could see this grant as a high-risk, potentially very high reward program if the effects come through. And then just one final note. This grant is an example of something that, you know, we started supporting after the cuts from the US administration last year. This was a program that, its support had been coming via Development and Innovation Ventures at USAID and after that was shut down last year, we picked it up and, [00:03:00] you know, that sort of led to our interest here. And so today I'll be talking to Erin about this program.

So hey, Erin. Thanks for doing this. Before we dive in on the program, can you just introduce yourself briefly?

Erin Crossett: Sure. My name is Erin Crossett. I'm a senior program officer, and I lead GiveWell's Water team.

Elie Hassenfeld: So tell us about this WASHmobile program. What's the program basically?

Erin Crossett: Sure. High level, you can think of WASHmobile as a WASH—which is water, sanitation, hygiene—prevention and treatment program. So the program delivers water treatment supplies and health messaging to people we think are at the highest risk of diarrheal disease and death during critical time periods, and I'll describe what I mean by that, in two countries, in the DRC and in South Sudan.

And so the main idea here that the creators of the program at Johns Hopkins had in their head was, like, the idea is that when someone in a [00:04:00] household—Elie, you have four kids, so you can probably relate to this—when someone in a household gets severe diarrhea, everyone around them is suddenly at a much higher risk of diarrheal disease as well.

Oftentimes, this comes through contaminated water. That water source is nearby in the neighborhood, potentially in the home. And so the idea is that instead of spreading resources really thin, we try to concentrate the program and target the program on these highest-risk families at the moment they're in more acute danger.

And so practically, there are two tracks. I think we'll talk mostly about the first one. We call it track A and track B. So track A, this is where the vast majority of the benefits that we model in our cost-effectiveness analysis come from.

So that targets the family of anyone who's been hospitalized for diarrhea. So the idea is you have an index patient, an index child who goes to the hospital for diarrhea. Health worker visits, gives them hygiene [00:05:00] supplies like vouchers for chlorine tablets, soapy water for handwashing, a little handwashing kit. And then the family gets phone reminders for a couple of months reminding them about the importance of safe water and hygiene practices.

And then track B, which is the much cheaper lighter-touch arm, this is trying to reduce transmission. So the idea is that when there are a cluster of cases, it signals an outbreak. Everyone who has a mobile phone within a certain radius, 500 meters of that outbreak, gets SMS alerts and a digital e-voucher for chlorine for a week that they can take to a local pharmacy and get chlorine and treat their water. So it's like cheap, cast a wide net.

And then this grant specifically is funding Johns Hopkins University and a number of other partners. Tearfund is the implementing partner for this, over five years to implement the program in both DRC and South Sudan, and then also run an RCT of the program in [00:06:00] DRC, and then a number of other data collection efforts we can talk about, like verbal autopsies and a process evaluation.

Elie Hassenfeld: And so like what's the underlying mechanism? Why is it the case that when you have that index patient with severe diarrhea that then you'd expect that other household members or other nearby households are at higher risk?

Erin Crossett: Yeah. So an earlier version of this program targeted cholera specifically, and we know that a key way that cholera is transmitted is through contaminated water. And so the idea is that if households are all exposed to the same contaminated water source, then if one person's sick, we should expect someone else to get sick.

The other is just like you're in close proximity with one another, so there's fecal-oral transmission is another pathway. And so again, if you're just living in really close quarters with people, touching the same things, you know, eating the same food, et cetera, then it's more likely for people to get sick in the same ways.

So this is a bundled program. I just mentioned that like there's multiple ingredients here, right? Like there's [00:07:00] a chlorine component, there's a handwashing component, there's an ORS component, although the control group also gets that, so it kind of nets out. And so we aren't exactly sure. We can talk about if we get into the, you know, the impacts from prior trials later. We don't exactly know what mechanism is actually driving the effect because we haven't been able to disaggregate them.

Elie Hassenfeld: The core idea is we have reason to believe that the people served by this program are at significantly higher risk of suffering from severe diarrhea and then from potential health outcomes including death, and therefore this significantly more intensive program focused on these higher-risk people could yield significant benefits.

Yeah, so maybe you could just explain a little bit about where the idea for this program comes from and what leads you to believe, what, you know, leads us to believe that it could be a promising approach to solving this problem.

Erin Crossett: So the program was developed by some researchers at Johns Hopkins University, primarily the principal investigator, Christine Marie George. And it builds [00:08:00] on two predecessor programs. There's a lot of acronyms here, so I'm gonna spell them out, but bear with me. There's one called CHoBI7, which started in Bangladesh, and CHoBI is the Cholera Hospital-Based Intervention for Seven Days.
It also is a bit of a pun. Chobi means picture in Bangla, and it's like a nod to this little flip book that the health promoters use to teach families how to actually, sufficiently treat their water, wash their hands, et cetera. And then the second program is PICHA7, which is Preventative Intervention for Cholera for Seven Days, and this was done in the DRC.

Picha also means photo in Swahili, which is spoken widely in Eastern DRC. So WASHmobile is basically you can think of as like all of these programs are in the same universe, and WASHmobile is like a slightly lighter touch version of CHoBI and PICHA7. And so Johns Hopkins developed this program over many years and in close [00:09:00] partnership with the Bangladesh Ministry of Health, the DRC Ministry of Health, and Vodacom, because there's like the telecom component, and then Tearfund, which is a big international NGO working primarily in humanitarian contexts.

They have a presence in both DRC and South Sudan, and they are running this specific program for the first time in both countries. So previously, Hopkins was implementing WASHmobile, PICHA, and CHoBI, all like in a research setting. So this is the first time you can think of the program is going to be operating as a standalone program by implementers. And then the last partner I want to call out is Catholic University of Bukavu in South Kivu, has been the prime DRC research partner.

Elie Hassenfeld: There's this program that's developed by researchers at Johns Hopkins. It's implemented in two different places at higher intensity, and then now, the program is [00:10:00] going to be implemented by Tearfund, sort of a standard large-scale international NGO.

You know, what are the biggest takeaways from those trials conducted by researchers at Johns Hopkins that made this type of approach, this, you know, more intensive approach with a few different simultaneous interventions aiming to reduce the severity of diarrhea and its consequences? Yeah, like what do we take away from those trials that lead us to believe that this could be promising now?

Erin Crossett: Yeah, right. Like, why is this the thing that we're really excited about right now? So we primarily pull from three trials of various versions of CHoBI and PICHA7, and then there was also a small pilot of WASHmobile in DRC.

And basically what we found at the end of the day was that the programs were consistently delivering material reductions, so around 60% reductions in diarrheal disease. And you know, you might have concerns about that because a lot of it is self-reported. I'm not as concerned about it because it was also [00:11:00] corroborated by other important health outcomes.

So, I believe this was in PICHA7, there was a material reduction in the risk of child stunting. So that's measured objectively through measuring, you know, child anthropometrics. And then also the process outcomes are also pretty promising or suggest that there's, like, a plausible mechanism here, which is there were meaningful increases in chlorination rates when enumerators actually tested people's drinking water, and then self-reported handwashing and hygiene practices. So bottom line is, like, we were seeing pretty consistent reductions in multiple trials again, with various little tweaks on kind of what ingredients were included, how often reminders were sent, et cetera—and sustained over, you know, a fairly long period of time. So, like, 12 months, I think, was the typical trial period

Elie Hassenfeld: You said that the trials that were conducted were more intense and that what we're supporting is a [00:12:00] lighter-touch version of this program. I know there are a lot of differences between the different trials and our program, but what would you highlight as the primary ways in which the program we're supporting is lighter touch than what was previously studied?

Erin Crossett: Yeah. So I think the big one is duration. So WASHmobile is three months of post-discharge messaging from text messaging. And then I think there's only, I believe there's like one to two in-person follow-up visits from community health workers, while there were many more over 12 months for CHoBI7 and PICHA. So, and that's also a big cost driver too, so that meaningfully reduces costs.

And then the other is just the amount of chlorine tablets people are getting. So, you know, people are getting tablets for about eight days for their full family as opposed to months' worth for the previous trials. And then there's also this track B component—like the outbreak e-voucher, right? So it's not just targeting these index hospital admission households, it's also targeting these larger [00:13:00] community transmission settings.

And then I would say because of that, so I think a natural reaction is like, well, then you should totally discount the effects because this seems like a pretty diluted program, and we agree. So we did include, and when we were modeling the effect size in our cost-effectiveness model, we discounted the effects by like 45 to 50% to account for the fact that this is a lighter touch model.

Elie Hassenfeld: Yeah, and I think this is a pretty common—but tell me if you agree with this experience—that you have programs that are studied as part of research-driven trials. And I think for the people running the trials, the question is, does this approach, like, work at all? Will we see a substantial effect? And so because that's the question, then the way the trial is set up is to do something fairly intensive because you just want to see, like, does this idea of having an index patient and then providing these additional resources to households, does that have any effect?

But then the question becomes for GiveWell and for funders or implementers, how can we get as much of that [00:14:00] effect as we can at a cost that is, you know, reasonable or high benefit per dollar spent? And then you have to make these tough choices about how to scale down the intensity of the program so that it is viable at the level of cost that would make sense to try and implement a program like this.
Like, if we were just to, I imagine, fully replicate the program as studied in the trial, that would presumably be fairly cost prohibitive. And, you know, we don't—and I don't know for sure, but I'm guessing that you—we—think we can get a more, more cost-effective outcome by trying to implement a lighter touch program. But how are you thinking about that question in general?

Erin Crossett: I think that's exactly right. I mean, I think that's, like, again, it's a bundled program, so we can't say definitively. We don't have a trial that tests each combination of all the different health products provided and says, like, "Okay, well, providing chlorine and ORS but not hand washing stations is, like, the most cost-effective."

But I do think that we have plausible hypotheses. I have plausible hypotheses about, like, what could be driving the effects. And again, just [00:15:00] from, like, understanding the field, understanding the evidence base for WASH programs more generally. Knowing, for example, like, you know, historically or today really, our GiveWell, the water team has focused pretty much exclusively on chlorine because it's so cheap and widely available and averts mortality.

And so, you know, I think the thought is like, yeah, if we're gonna pare the program down, you want to think of, like, what are the cost drivers? And then, like, what are the likely drivers of impact? And then trying to, like, get the balance right. So drivers of impact I would expect to be chlorine tablets, the initial visit from a community health worker to the index patient, right?

Because I think it's very top of mind that the person's very sick. They don't want to be sick anymore. The health worker is telling them how to not be sick. And then, you know, the periodic reminders of like, "Hey, it's important to, you know, treat your water." And then I think I'm excited about this new component because—this track B—because again, it's super cheap and we don't actually have a great way of modeling or understanding what the benefits are.

But it's just a very plausible hypothesis to me that [00:16:00] if there's an outbreak of disease, that you would want people living in that area to both know about it and then actually go and treat their water in that very acute window.

It doesn't add much cost, but it could potentially break up transmission in a way that some experts think could actually be the bigger share of the benefits here, but we don't currently model it that way.

Elie Hassenfeld: Right. So I guess that component, the track B, the SMS reminders, is a fairly low cost as part of the program overall. I think it's in the low single digit percent of the cost, and our expectation is that it's also fairly low benefit, like sort of at the same scale. You know, single percent benefit. But there's some possibility that it's extremely impactful, and we'll be surprised, and we'll learn from this program that it has more benefit than we anticipate.

Erin Crossett: Yeah, and I should say that we didn't spend a lot of time modeling or thinking about how to model track B. Both because track A was already so cost-effective that it already looked above our bar [00:17:00] without it and then also we can't break out the effects of track A and track B. And we thought about trying to model transmission for track B, but it just kind of felt like a house of cards very quickly. And again, like I said, we didn't, the cost-effectiveness case didn't require much from that benefit stream, but I do think it's plausible that we're underestimating it.

Elie Hassenfeld: Yeah. I want to quickly just ask sort of two operational questions about the program. And so the first is just you said that it builds off a patient being hospitalized, and so I'm just, like, curious am I right that that's how the program works?

And in the places where this program will be operating, is there sufficient health infrastructure that the health system will be able to, you know, take someone in who is hospitalized and then go out and find the people that they're connected to?

Erin Crossett: That's a really good question. I'm optimistic that that's possible in DRC in South Kivu because this team has been working there for a decade plus. I think it's a huge question in South Sudan. So I guess maybe to highlight how difficult it is to operate in South Kivu and Eastern DRC and in Jonglei State in South [00:18:00] Sudan.

In South Kivu, you know, you have this active armed conflict. There's also conflict in Jonglei state. You have, in both places, severe flooding, which is just like a physical barrier limitation to, you know, to people's mobility, and you have large displaced populations. And so I think the researchers estimated that in South Kivu, 20% of health areas—health areas as an administrative unit—are just flat out inaccessible at any given time due to fighting.

And so, yeah, I mean, I think a question—that is a key question— is like, if no one can get to the hospital, then we would expect the benefits from particularly the track A component to be very, very minimal. Fortunately, since we do [00:19:00] have prior evidence from the PICHA trial in DRC, which was also done in South Kivu, we have evidence to suggest that that wasn't a binding constraint, and people are still able, ultimately, to access health facilities. But I would expect just based on my knowledge of what it's like working in South Sudan, based on talking to Tearfund and other researchers who are familiar with the South Sudanese context, that it's just going to be extremely challenging. And that's a large part of the reason why we didn't consider really doing a trial there.

Elie Hassenfeld: You know, we're saying the word like hospital, but is there any like level of health facility that someone would have to reach? Because there's smaller clinics, there's like larger scale clinics, or is it just like enter into the health system with a case of severe diarrhea will get flagged? Like how does that work?

Erin Crossett: In DRC they have a surveillance system. So there are 115 health facilities. Every health facility, private and public, are included in Hopkins, in University of Bukavu, in their surveillance system. So you [00:20:00] can go in at any level and you will be tracked. Like, you will be part of the trial and this data set.

And so in addition to having this surveillance and being able to like have good data about who's actually checking into a hospital, we're also funding this area-based mortality survey. So surveyors are actually going to go directly to households and track who in the household is dying. Were they dying like post-discharge, on their way there, just unable to access a facility, et cetera?

Elie Hassenfeld: And so I guess with this index patient that gets flagged, at least in DRC, the team has experience, you know, working in that exact location, so we have good reason to believe it works. In South Sudan, I guess less clear. So how do you think about the challenge in South Sudan given that there's less of a track record that this particular approach would work there?

Erin Crossett: I mean, I think ultimately, like, this is just a constant trade-off in our work. Because it cuts both ways, right? [00:21:00] Like, the parts of the world that are highest burden and highest need and where presumably, you know, dollars can go furthest, are also areas that are extremely fragile contexts where there's, you know, endemic cholera, ongoing conflict, weather events.

And so part of the reason why we wanted to do this, why we're interested in trying to fund this in South Sudan is because burden is so high. I mean, we estimate that even with pretty significant haircuts to effect size, et cetera, we estimate the program is 20 times as cost-effective as cash transfers in this context in Jonglei.

And so there is a high risk that the program just fails. We assume, like, there's a 25% risk, that this just, like, totally doesn't work at all. But if it does work, that there's, like, pretty significant upside, and I think it matters who your implementing partner is. Tearfund has been working in South Sudan, in Jonglei State in particular, for a very long time. They understand the context. There's still a lot of things we need to [00:22:00] figure out about chlorine supply chains, about, like, yeah, people's access to healthcare facilities, things like that.

And we have baked into the grant, like, a one to two-year buffer period for them to do what they call, like, formative research, which is basically to figure out, okay, we have a sense of how the program works or should work, but what adjustments do we need to make to account for the local context?

Elie Hassenfeld: That's really helpful. I want to come back to the question of how we will know how successful the program was, you know, after the fact. But couple more just, like, operational questions about the program. So we're supporting Tearfund, the organization that is running this, and then the program also relies on the existing health facilities, And so, what is the, let's say, country health system doing in this program, and what is Tearfund doing in this program?

Erin Crossett: So in DRC, Hopkins and the university are working closely with the Ministry of Health. Like I [00:23:00] said, they have this existing surveillance infrastructure. And I think another cool thing about this grant actually is that they're also providing technical assistance to the Ministry of Health on basically how to properly count deaths and mortality and basically improve their administrative record keeping.

I guess in like very simple terms, I think the main function that the Ministry of Health is bringing is the community health worker labor. So when people are in the hospital, you know, they're doing the visits, and then they're also doing the subsequent home visits. The other costs are borne by the implementing partner themselves.

I'm not sure what it's going to look like in South Sudan, and I think that's going to depend on the piloting and the formative research.

Elie Hassenfeld: Okay, that makes sense.

I want to shift gears a bit and talk about, you know, what and how we expect to learn from this grant. I mean, I think different from many things that GiveWell does. You might consider our standard [00:24:00] bread-and-butter approach be something like there's a lot of evidence that something works, we go and aim to scale up something that has a lot of evidence behind it and has been operating for a while, and it just needs more scale. That's kind of the stereotypical maybe GiveWell program.

And then on the other hand, this is something where there is, you know, in the scheme of things, really good evidence, you know, multiple randomized control trials that show something like this works. The underlying components make a lot of sense that they would work, but also a fair amount of uncertainty here, and so a major part of this grant is being in a position to learn about the extent to which it does work in each of these two contexts, in DRC and in South Sudan. So can you talk a little bit more about, you know, in each case, what we'll learn, how we'll learn it, those kinds of questions?

Erin Crossett: Yeah. I'm really excited about this grant because it's a large grant, $9 million, and it's pretty much 50/50 in terms of the budget going, like, half to direct implementation, half going to RCT and other data collection efforts. So I think we're going to learn a ton [00:25:00] here.

Just really quickly what the design looks like. Again, the RCT is only in DRC. Cluster randomized trial randomizing thirty health areas in South Kivu—just under eight thousand households total over twelve months. And the primary outcome here is hospital admissions for diarrhea for children under five, detected via this facility surveillance that I was talking about.

Okay, the most important parameters that we're going to learn about. I can kind of like quickly walk us through there. So one is this risk multiplier. And so what do I mean by that? The whole program, I think I said this earlier, is predicated on the idea that the families that are targeted in WASHmobile are much higher risk.

So we think that we currently model that children under five are three times more likely to die of diarrhea than the average household. We're pretty confident that they're infected more often. Like, I don't think that that's something that's a contentious claim. But we're unsure about whether that infection risk actually translates into higher death risk. So [00:26:00] basically, we are going to learn about that through the RCT. It's basically going to be measured in control areas by comparing mortality rates in diarrhea patient households against randomly selected ordinary households in the same area.

So we'll get the former, the diarrhea patient household's mortality rates, from the facility surveys, and then we'll get the latter, the household mortality rates, from these area-based mortality surveys and verbal autopsies that we're funding. And the idea is that because neither group, by function of being in the control group, because neither group got the program, then the gap between them reveals just like the natural risk difference. So like how much higher these families' baseline risk really is.

Elie Hassenfeld: You know, there's the treatment group and then control group, and then we have—tell me if this is right. We have just two, primarily, like, two things that we're looking at to assess the impact of the program.

One is hospitalizations for diarrhea, where if the program is successful, there should be [00:27:00] fewer cases of severe diarrhea in the treatment group. And then another is asking, when there are deaths, what is the cause of those deaths? Because the pathway through which this program has effect, is that it reduces mortality from diarrhea.

Erin Crossett: That's right. But we're also—we also want to say, okay, wait, but are we sure that WASHmobile is actually targeting people who are at higher risk of death? Because they're—if they're not, then that's a key driver of benefits here. And this is important because, well, it makes a big difference on the quantitative bottom line because we're assuming a 3X multiplier here.

And we talked with four academic cholera experts, and there's a real split. I would say two think that we're potentially overestimating the multiplier. They think, like, well, actually, sure, they're more likely to get infected, but they're going to the hospital, so they're exhibiting health-seeking behavior. They might have better access to the hospital or to healthcare facilities generally. And so, like, we think they're probably at lower risk than the [00:28:00] average population. And then there's also reason to think that actually they could be at higher risk just because their, you know, their household situation is, you know, more susceptible to enteric infections for whatever reason.

And so, yeah, because of that, we think there's a range of what the multiplier could be. We chose something on the conservative side. But since this is such a big driver of benefits, it's very important for us to try to triangulate the best we can.

Elie Hassenfeld: So how is the verbal autopsy gonna help us better understand the risk multiplier?

Erin Crossett: Sorry, you need both. You need the area-based mortality survey plus the verbal. So the area-based mortality survey is what allows us to go around to households who haven't been admitted, who are just normal households, you want to get the baseline mortality rate. So you just want to go around, knock on doors, understand how many people are dying, and then the verbal autopsy allows you to go back and say, "Actually, okay, what are these people dying from?"

And that allows us to understand, people are dying from, you know, diarrheal disease, what we're looking for, as opposed to something that we think is an unrelated death that this [00:29:00] program couldn't target.

Elie Hassenfeld: And the verbal autopsy on the control group will give us additional evidence about a particular question of importance, which is once you have someone who is seen in a hospital for diarrhea, what is the additional risk to mortality in that household?

Erin Crossett: Yeah.

Elie Hassenfeld: That makes sense.

Erin Crossett: One, one quibble is, like, again, you need the verbal autopsy plus the area-based mortality survey. But yes.

Elie Hassenfeld: Right. Right. Okay. So in DRC, we're doing a lot to get information. We're going to learn a lot about how this program went and how successful it was, what we could do next. What are we going to learn in South Sudan where we're not running an RCT?

Erin Crossett: So a couple of things in South Sudan. South Sudan, they're also going to be tracking operational metrics, again so that we can understand is the program being implemented with fidelity? Are people actually getting to health clinics? Are they actually getting, like, the key ingredients in the program?

And then we're also funding a verbal autopsy [00:30:00] there. So this is going to look different than DRC because, again, we don't have the treatment-control contrast. But this is going to be a population-wide survey that will basically give us better data on what baseline mortality looks like. We won't be able to estimate the multiplier, but this is a really big uncertainty of ours because South Sudan has never had a DHS, a Demographic and Health Survey, which is a key input of our modeling of baseline mortality and, you know, IHME and GBD rely on, Global Burden of Disease.

I think the last major nationwide health survey was in 2010, so like a year prior to their independence. And so the current estimate that we're using for baseline mortality is just, like, largely extrapolation and modeling.

Elie Hassenfeld: Okay, let's just zoom out for a second, and I'm curious if you have theories about why this program hasn't been funded earlier. Like, why is this the program that GiveWell is funding and that there isn't, you know, someone else who would fund [00:31:00] this in our place?

Erin Crossett: Yeah. A couple of thoughts here. One is that it was being funded by someone else. Development Innovation Ventures at USAID was funding a version of, a new variation on the CHoBI7. They were funding a trial in Bangladesh. And when USAID cuts happened, we, GiveWell, stepped in, and we actually plugged that funding gap. So they were getting funding from USAID, I think a couple of other funders.

I mean, the other thing is that, like, as I mentioned, you know, a lot of the focus on Hopkins to date has been on—they've had, like, a very ambitious research agenda, right—so it was a lot on understanding what the program's effects are on reducing diarrheal disease. And I think now they're really starting to focus on scale. So I think it's kind of the question for the near future is, like, are other people going to be really interested? I mean, I think they're having a lot of good conversations with other INGOs in the humanitarian space to operate in Yemen, Sudan, couple of other countries.

So yeah, I think that's [00:32:00] something that'll be interesting to watch in the future. Another thing that I think is just interesting, though, is that I mentioned that we talked with a couple of cholera experts, and one in particular highlighted that these effect sizes that this group, the research group, has seen are unprecedented for the cholera case-targeted intervention space.

And so it's possible that there's just, like, something really promising about the intervention, in which case, like, great. We will learn that, and we will try to scale it up. Or when we try to implement this in, like, quote-unquote, "real-world settings," that the effect sizes will just collapse.

And so I don't think that's a reason why this hasn't been scaled up more, but I do think that that's a reason to temper potentially our expectations.

Elie Hassenfeld: Great. Well, thanks, Erin.
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Elie Hassenfeld: Hey everyone, this is Elie again. Thanks so much for listening through to this conversation. I think this is a really interesting deep dive into a promising program in an area, water, [00:33:00] that is, you know, still one that GiveWell is increasing our focus on over time.

And I'm especially excited about the extent to which we've been able to expand and or increase our capacity as a team so that we're able to help bridge this gap between programs that are studied in academic settings, and then ones that are being brought into the real world, being handed off to implementing organizations and studied so that we can find ways to scale them up further if the results in the real world in, you know, when implemented as they would be without researchers heavily involved, you know, if those hold. And so we're, you know, optimistic, cautiously optimistic I should say, about this program, and hoping that what we learn will enable us and others to determine how to scale this up further.

Thanks as always for your interest in GiveWell and for your support. We really appreciate it.