The Crisis EA Cannot Afford to Ignore
More than two years ago, Sudan descended into war. What began as a clash between the army and paramilitary quickly became one of the world’s worst humanitarian crises. Millions have been displaced. Families are going hungry. Communities are cut off from medicine. Violence and disease spread in silence. And the world keeps looking away, even as the human cost grows daily.
So why are you seeing more about Sudan in the news now? On October 26, the RSF captured El Fasher after an 18-month siege. What followed: 460+ patients and companions killed at a Maternity Hospital. 82,000 people fled on foot. Mass graves visible in satellite imagery.
Since the war began in April 2023: 150,000+ killed (which is most likely undercounted). 13 million displaced, the largest displacement crisis in the world. 30 million people, over half of Sudan’s population, need humanitarian assistance. Famine confirmed in El Fasher and elsewhere. Acute malnutrition rates up to 35% in children.
Listen to today’s episode of the Daily, where New York Times correspondent Declan Walsh explains how this became one of the worst humanitarian crises in decades.
But here’s what makes this different from a “hopeless” crisis. The infrastructure to save lives and build a future peace already exists and is working.
How do I know this? I led USAID programs in Sudan until September. When the Agency was dismantled, we had to shut everything down overnight. One day we were supporting women’s coalitions, youth volunteers, and radio stations broadcasting lifesaving updates. The next day we were gone. But the Sudanese organizations we partnered with? They’re still there, still operating, still saving lives under impossible conditions.
Emergency Response Rooms are still delivering food, water, and shelter to displaced families fleeing the violence in El Fasher and elsewhere. Independent outlets are still warning people which roads are safe, information that literally means the difference between life and death. Women’s coalitions are still pressing for peace, even as war rages around them and atrocities mount. These efforts work. The courage and capacity are there. What they need now is solidarity and resources.
For the EA community, Sudan is the kind of crisis we are called to confront:
Impartiality: Every life matters equally, whether in Portland or Port Sudan.
Cause Prioritization: Sudan ranks extraordinarily high on scale, neglect, and tractability. Despite being the world’s worst humanitarian crisis, it receives minimal international attention, making it severely neglected.
Evidence-Based Strategies: Emergency networks, women’s coalitions, and independent media have proven they can reach people effectively, even amid active conflict, siege conditions, and atrocities.
Maximizing Impact: Small amounts of flexible funding can keep entire networks running, expand radio coverage to warn hundreds of thousands more of danger zones, and amplify women’s voices pushing for peace. These are dollars that save lives.
Global Focus: EA asks us to act where need is greatest, even if the world is not watching. As bodies are being burned in El Fasher’s streets to destroy evidence and the international powers continue inaction, Sudan is surely one of those places.
Scout Mindset: Sudan is not hopeless. Even after El Fasher’s fall, civilian networks continue operating under unimaginable conditions. With support, they can do far more.
Put Sudan on the EA agenda. Fund frontline responders who are reaching people fleeing El Fasher. Support independent media that provides life-saving information about safe routes. Back Sudanese women who continue building peace even as their communities face genocide.
The world may look away. We should not.
Image credit: 2023 “All We Want is Life” (c) Galal Yousif
Thanks for writing this, and many kudos for your work with USAID. The situation now seems heartbreaking.
I don’t represent the major funders. I’d hope that the ones targeting global health would be monitoring situations like these and figuring out if there might be useful and high-efficiency interventions.
Sadly there are many critical problems in the world and there are still many people dying from cheap-to-prevent malaria and similar, so the bar is quite high for these specific pots of funding, but it should definitely be considered.
Thank you. I really value this kind of thoughtful engagement, and I think you’re raising exactly the right questions about efficiency and trade-offs.
I want to explore whether Sudan might actually meet the cost-effectiveness bar, even when compared to GiveWell top charities. Here’s what the independent research suggests:
Efficiency indicators that might rival malaria prevention:
Volunteers working unpaid for over two years = essentially 0% overhead
Operating in areas where international responders cannot reach = extremely high counterfactual impact
Community-based accountability without expensive M&E infrastructure
Direct cash to services: when funding goes through intermediaries, ERRs complain that 10% administrative fees could instead fund more relief supplies or volunteer stipends
The epistemic challenge: You’re right that we lack the kind of rigorous cost-per-life-saved calculations GiveWell produces. But I want to distinguish between two scenarios:
“We studied this and it’s not cost-effective”
“We can’t study this during an active war, so we’ll assume it’s not cost-effective”
The independent research from SSHAP (London School of Hygiene & Tropical Medicine) and ACAPS confirms ERRs are operating at massive scale. Between 2023-2024, they provided first aid, delivered medicines, mapped evacuation routes, supported IDPs, ran communal kitchens, distributed food, and operated hospitals. We just can’t quantify it the way we’d like.
A question for the community: Should EA develop any framework for responding to acute crises where traditional cost-effectiveness analysis isn’t possible? Or is our position that if we can’t measure it with near-certainty, we won’t fund it—even during famines?
I’m genuinely asking, because I think this gets at something important about what EA is for. If the answer is “we focus exclusively on interventions we can measure precisely over long timeframes,” that’s a legitimate choice, but it means explicitly ceding all emergency response to non-EA actors. I’m not sure that’s the right call, especially when volunteer networks with exceptional efficiency characteristics are already operating at scale.
What do you think?
Those are all great questions. i think with option 2 i wouldn’t assume it’s not cost effective, its often just that we don’t know. I for one would be surprised if there weren’t really cost effective places to donate in Sudan, to just that it’s hard to know which ones.
With acute crisis as well i think there is often an assumption that they are getting relatively well funded anyway, but like you say that might not be the case any more.
i think if you made a decent case for one particular situation that was cost effective and needed funding you night be able to convince folks here.
“Should EA develop any framework for responding to acute crises where traditional cost-effectiveness analysis isn’t possible? Or is our position that if we can’t measure it with near-certainty, we won’t fund it—even during famines?”
This is tricky. I think that most[1] of EA is outside of global health/welfare, and much of this is incredibly speculative. AI safety is pretty wild, and even animal welfare work can be more speculative.
GiveWell has historically represented much of the EA-aligned global welfare work. They’ve also seemed to cater to particularly risk-averse donors, from what I can tell.
So an intervention like this is in a tricky middle-ground, where it’s much less speculative than AI risk, but more speculative than much of the GiveWell spend. This is about the point where you can’t really think of “EA” as one unified thing with one utility function. The funding works much more as a bunch of different buckets with fairly different criteria.
Bigger-picture, EAs have a very small sliver of philanthropic spending, which itself is a small sliver of global spending. In my preferred world we wouldn’t need to be so incredibly ruthless with charity choices, because there would just be much more available.
[1] In terms of respected EA discussions/researchers.
Thank you for sharing Allegra! Welcome to the Forum, and congrats on writing and sharing this.
I think this is well written and engaging! I agree it seems a real shame for these people and for the world that the existing services have been cut. And I do think that your bullet point list suggests it’s worth considering/evaluating.
I think a stronger case would delve into more detail on these claims, which aren’t currently substantiated: “Sudan ranks extraordinarily high on scale, neglect, and tractability”, and “Emergency networks, women’s coalitions, and independent media have proven they can reach people effectively”, then compare explicitly and quantitatively to other candidates for top cause areas and interventions. Is the problem area more promising than others? Are the available interventions more cost-effective? (Or in the same ballpark?)
Jamie, thank you so much for this thoughtful and constructive feedback! I really appreciate you taking the time to engage with this so carefully.
You’re absolutely right that these claims need more substantiation. I made a deliberate choice to keep the initial post relatively brief to give people baseline knowledge and invite engagement rather than overwhelming readers with data upfront. But I’m glad you’re pushing me to go deeper.
Let me provide more detail on each dimension, while being honest about where the evidence is strong and where it’s limited:
On Scale: According to UN OCHA’s December 2024 report, an estimated 30.4 million people need assistance in 2025, nearly two thirds of the country’s population and marking an increase of 5.6 million people from 2024. The ACAPS October 2024 report notes that conflict-induced displacement has affected more than ten million people, while livelihoods, markets, and services across the country have collapsed.
According to UN OCHA’s report from August 2024, famine conditions are now prevalent in Zamzam internally displaced persons camp in North Darfur State, marking the first such report globally since 2017, with the IPC Famine Review Committee concluding that thousands more people are likely experiencing similar conditions in 13 other areas at risk of famine.
The IRC’s 2025 Emergency Watchlist ranks Sudan at the top for the second year running, describing it as “the largest humanitarian crisis ever recorded,” accounting for 10% of people in humanitarian need globally despite being home to just 1% of the global population.
On Neglectedness: This is what I think has the strongest case. The SSHAP October 2024 case study notes that in April 2024, donors came together in Paris in an effort to raise the USD 2.7 billion that the UN estimated is required. I helped prepare US government officials for that meeting, and remember how unbelievably difficult it was for donors to agree on coordinated action. But current estimation suggests funding is just 41% of what is needed. Media coverage, political will and funding all remain low when compared to the magnitude of the crisis.
According to UN OCHA’s July 2024 dashboard, by the end of July, the 2024 Sudan Humanitarian Needs and Response Plan was still less than 40 per cent funded of the $2.7 billion required.
The Norwegian Refugee Council’s 2023 report found that Sudan was among the nine most underfunded crises globally, with funding coverage between 2019 and 2023 averaging 15 percent lower than other humanitarian response plans.
And critically: the SSHAP report notes that in December 2023, research indicated that only 16% of aid was able to reach those in need, with access most restricted in the besieged Khartoum, Darfur and Kordofan states.
On Tractability and Cost-Effectiveness: This is where I need to be most honest about evidence limitations. I cannot provide you with a GiveWell-style cost-per-life-saved calculation. Here’s what I can tell you from the independent research reports:
Efficiency indicators:
The ACAPS report documents that ERR volunteers have worked unpaid for over two years, meaning overhead costs are near-zero
Some ERRs in Khartoum voiced that intermediary NGOs would take a significant percentage (often 10%) of grants for administrative fees while not doing much in terms of operational work, with ERRs carrying out implementation including running kitchens and clinics
ERRs implement informal yet effective accountability measures, such as public complaint handling and transparent procurement rules, including the formation of procurement committees
Access advantage:
ERRs’ adaptability, presence in conflict areas, and proximity to communities have enabled them to respond where other national and international responders could not
This means the counterfactual impact is potentially very high—these aren’t services duplicating what others could provide, they’re often the only services reaching certain populations
Demonstrated scale:
By October 2024, an estimated 360 ERRs were operating across seven states
Between 2023-2024, ERRs provided first aid, delivered medicines including for chronic diseases, mapped safe evacuation routes, supported IDPs in shelters, established communal kitchens, distributed food, and operated hospitals and local health facilities
The Honest Comparison to Top Cause Areas: You asked for explicit quantitative comparisons. I can’t provide them at the level of rigor EA typically expects, and I want to be clear about why:
Global health interventions (malaria nets, deworming, etc.) have decades of RCT evidence. I cannot compete with that level of certainty.
What I can argue: In a context where two-thirds of a country’s population needs humanitarian assistance including confirmed famine conditions, volunteer networks with ~0% overhead operating where no one else can reach might have cost-effectiveness in the same ballpark as top interventions. But I’m making an educated argument based on the available evidence, not proving it with RCTs.
The epistemic challenge: This raises a real question about EA’s framework. Should we only fund interventions we can measure with near-certainty? Or should we have some capacity for high-uncertainty, high-potential-impact interventions during acute emergencies?
What Would Stronger Evidence Look Like?
Honestly? It would probably require EA funding a proper evaluation. You could fund:
Retrospective analysis of ERR operations with health economists
Prospective monitoring of specific interventions
Comparative analysis of ERR vs. traditional NGO cost structures in Sudan
But there’s a chicken-and-egg problem: we can’t get that evidence without some initial funding, but we can’t get funding without that evidence.
My Ask: I’m not claiming Sudan definitively beats GiveWell top charities on cost-effectiveness. I’m arguing it’s plausible enough that it warrants serious evaluation, and that the combination of massive scale + extreme neglectedness + demonstrated local capacity should be enough to trigger that evaluation.
What would you need to see to consider this worth deeper investigation? I’d really value your thoughts on how EA might approach situations like this where the need is urgent but the evidence base doesn’t yet meet our typical standards. Thanks again for engaging with this so thoughtfully!
I think most people would say that the analysis should be close to risk-neutral. However, global-health donors seem more risk-averse in practice.
That being said, I would submit that we probably should penalize early-stage research and cost-effectiveness analysis, not based on risk tolerance per se but because experience teaches that effectiveness often goes down as analytical rigor goes up. To analogize to a different domain, lots of drugs look great in early trials but fall apart in late-stage trials. So I think that the necessary showing is probably this: is there a substantial probability that the cost-effectiveness significantly exceeds the counterfactual use of the money (which I will assume to be GiveWell All Grants?)
GiveWell has made malnutrition grants, such as this one. The estimated cost-effectiveness was somewhat less than its usual bar (8x, as opposed to 10x, would have been 10x absent funging adjustment). This appears to be a program for extremely malnourished young children, as evidenced by a cost of $215 per child. I’m not qualified to say what the sweet spot for combating malnutrition is (e.g., whether a program for somewhat less malnourished young children might be more cost-effective because it could use less specialized foods, or whether the extra costs of feeding a larger population predominate.) On the other hand, if our starting point is that young-child extreme malnutrition programs are close to the bar, then it seems likely that programs for mild-to-moderate malnutrition and adult malnutrition probably wouldn’t clear the bar. All that is very shallow and out of my domain expertise. But that’s my initial stab at how we might start to bridge the evidentiary deficit here.
We also have pre-existing work (e.g., by GiveDirectly) on the effects of just giving cash to people in poverty, and emerging work that suggests giving the cash at the right time (e.g., shortly before childbirth) has a multiplier effect. Although selecting a multiplier would be dicey here, I would be willing to accept that there’s a multiplier here (and that provision of food and basic medicine is close enough to providing cash in these circumstances to use the cash data). You’d need a large multiple to get to 10x, though.
In any event, I think trying to adapt existing cost-effectiveness estimates to project results for a different context is a reasonable first step here. The projections are going to be error-prone, but I think they could inform whether to invest in more specific work.
There’s another awkward issue here. It’s more likely that ERRs engage in some programs that are more effective than the marginal GiveWell dollar than it is that the marginal dollar given to an ERR outperforms the marginal dollar given to GiveWell All Grants. While recognizing the diversity of ERRs, could we give (e.g.) $1MM dedicated to young-child malnutrition work and predict that ~$1MM more in that work will get done? Or will money get shifted around such that we get (e.g.) $250K more of that, of communal kitchens, of paying those who currently volunteer, and of something else? If the latter, we would need to base the cost-effectiveness estimate off the true marginal effect of the donation.
I fear it’s even worse than that. The classic EA global-health model assumes a fairly stable situation: malaria is ~malaria, and usually the world hasn’t changed that much in 5-10 years (and isn’t so different from country to country in a similar area) to render reliance on prior work dicey. By the time you were able to get high-quality results on ERRs, would the situation have changed enough to undermine reliance on that data? How much confidence could we justifiably have that results on ERRs obtained during one crisis would hold for a different crisis in a different country?
In the end, you have to do the best you can with the information you have. But if evidence will become stale quickly and is very context-dependent, that would make me somewhat less excited about spending a lot of resources to gather it.
Thanks for posting this Allegra! I was actually looking into this the other day and one thing that stopped me from giving as an individual donor was understanding exactly how cost-effective groups working on this are. My general understanding is that traditional humanitarian efforts aren’t particularly cost-effective if your goal is to help the most people (I think largely because these efforts raise lots of money through salience and they are not as rigorously designed as GiveWell charities might be—but these might not be true in this case).
Do you have any information or research into Emergency Response Rooms or other groups working in Sudan on how many people they are helping or lives they are saving?
Great question! I completely understand wanting to see rigorous data on cost-effectiveness. You’re right that traditional humanitarian efforts don’t always meet the same standards as GiveWell charities. However, the Sudan context presents some unique challenges for quantitative measurement.
I know of two independent research reports on ERRs:
1. Social Science in Humanitarian Action Platform (SSHAP) case study (June-August 2024, published October 2024) affiliated with the London School of Hygiene & Tropical Medicine and the Institute of Development Studies (linked here: SSHAP report)
2. ACAPS report (October 2024) - ACAPS is an independent humanitarian analysis organization (linked here: ACAPS report)
What we know about ERR impact:
Both reports confirm ERRs are operating at significant scale. Between 2023-2024, ERRs provided first aid, delivered medicines including for chronic diseases, mapped safe evacuation routes, supported IDPs in shelters, established communal kitchens, distributed food, and operated hospitals and local health facilities. Between December 2024 and May 2025, after over 1 million people returned to Khartoum, ERRs initiated water and electricity infrastructure repairs, rehabilitation of damaged health facilities, and provision of food and health services.
The challenge with quantifying lives saved:
Both reports acknowledge a critical limitation: ERRs are volunteer networks operating in active conflict zones, not formal organizations with monitoring & evaluation systems. ERRs face time-consuming reporting obligations that volunteers describe as onerous and a mismatch with their communal neighborhood accountability mechanisms. They use transparency with their local communities rather than the formal impact metrics international NGOs produce.
Why ERRs might be more cost-effective than you’d expect:
Extremely low overhead: Volunteers have worked unpaid for over two years, meaning nearly 100% of donations go directly to services
Access where others can’t reach: ERRs’ adaptability, presence in conflict areas, and proximity to communities have enabled them to respond where other national and international responders could not
Community accountability: Being members of communities themselves allows ERRs to implement informal yet effective accountability measures, such as public complaint handling and transparent procurement rules
My honest assessment: You won’t find GiveWell-style cost-per-life-saved calculations for ERRs. The operating environment makes that impossible. They’re running communal kitchens during bombardments and evacuating people from active conflict zones. The independent research confirms they’re filling critical gaps at massive scale, but if you’re looking for quantified cost-effectiveness metrics, those don’t exist yet.
Dear Allegra, thank you very much for your excellent post. I couldn’t agree more. In my view, the zero-sum debate about whether bed nets are more cost effective than humanitarian action keeps us from realizing additional positive impact. It doesn’t seem to be an accurate reflection of donor behaviour. For example, there is empirical evidence which shows that salient disasters (in the US) expand total giving rather than merely shifting funds away from other causes [1]. Also, a study of several major appeals launched by the UK Disasters Emergency Committee (DEC) showed that major fundraising interventions lifted total donations, even to organizations not included in the appeal, rather than crowding them out [2]. So I think we can help more effectively in Sudan without taking anything away from other global health interventions. Moreover, while Sudan is not receiving the attention it deserves, it still does motivate many people to give. The EA community (or someone else with knowledge of its concepts) should have an answer for donors who want to direct their money to the most cost-effective options within this crisis. I am currently working on such recommendations and would love to exchange further and learn more about your experience in the region.
All best and thanks again, Elias
[1] https://www.aeaweb.org/articles?id=10.1257/aeri.20200230
[2] https://www.bristol.ac.uk/efm/media/workingpapers/working_papers/pdffiles/dp17687.pdf
But the question here is whether that is true in the EA community. I don’t know the answer to that. I suppose each donor has to figure that out for themselves, ultimately.
I’d agree with that.
Hi all,
Thank you, Allegra for the well presented initial post, and for constructive replies. I thought I would share how I’ve been grappling with this standard EA dilemma regarding donations to acute humanitarian crises (as we see now in Sudan). The default position is that while morally urgent, these donations may be 1-2 orders of magnitude less cost-effective (in $ per life saved) than top GiveWell picks. This often leads to a “head vs. heart” framework, where one might allocate a 10-20% “moral” portion to crisis relief.
However, in thinking this through, I believe this binary view misses several distinct, high-impact frameworks that are defensible from an EA perspective.
1. The Middle Ground: Anticipatory Action (AA)
The first and most obvious “fix” is to reframe disaster aid as proactive rather than reactive. This is the “Anticipatory Action” (or Early Warning, Early Action) model.
This framework applies most significantly to predictable shocks (floods, droughts) and represents investment rather than mere relief. The data on its cost-effectiveness is compelling:
High ROI: Multiple agencies, including the UN’s Food and Agriculture Organization (FAO) and the World Food Programme (WFP), have demonstrated that every $1 invested in anticipatory action can save over $7 in avoided losses and added benefits for beneficiaries (e.g., protecting assets, avoiding debt, and reducing the need for costly emergency food aid) [1, 2].
A Proven Case (Somalia 2011 vs. 2017): This is a powerful A/B test. In 2011, a delayed, reactive response to famine warnings saw over 260,000 deaths. In 2017, similar drought forecasts were met with a large-scale early response, which successfully averted a full-blown famine [3].
For predictable crises, AA seems to be a high-CE, evidence-based intervention that fits comfortably within EA frameworks.
1. The “Tourniquet” Framework for Protracted Crises
This is the point I’m most focused on, as it applies to complex, ongoing crises like Sudan, where the “anticipation” window may seem to have passed.
My concern is that even in a full-blown crisis, things can always get worse. The crisis “cascades.” An initial conflict (a security crisis) triggers a displacement crisis, which triggers a health system collapse, which triggers a cholera epidemic and a food security crisis (IPC Phase 4).
The “tourniquet” framework argues that humanitarian aid in this context, while reactive to the initial shock, is critically preventative of the next, worse cascade.
This is not a hypothetical. This is what is happening in Sudan right now:
Preventing Mass Famine: As of September 2024, the Integrated Food Security Phase Classification (IPC) has confirmed that Famine (IPC Phase 5) is already occurring in towns like El Fasher and Kadugli. Over 21 million people are in Crisis (IPC Phase 3+) [4]. Aid from the WFP is not just “reacting” to hunger; it may be the only tourniquet preventing the 375,000+ people currently in Catastrophe (IPC 5) and the millions in Emergency (IPC 4) from cascading into mass starvation.
Preventing Epidemic Collapse: As of late 2024, Sudan is facing one of the world’s worst cholera outbreaks, with over 120,000 suspected cases [5]. With 70-80% of health facilities non-functional, UNICEF and WHO’s work to provide oral rehydration salts and clean water is not just “reacting” to cholera; it is applying the tourniquet to prevent an uncontrolled epidemic from killing tens of thousands.
I recognize the cost-effectiveness evidence here is less precise than for GiveWell interventions. But in crisis contexts, waiting for perfect data is itself a choice with costs. The cascade logic—preventing famine from becoming mass starvation, preventing cholera from becoming uncontrolled epidemic—is structurally high-impact even when exact figures are elusive. Demanding Randomized Controlled Trial level evidence for crisis response is effectively a decision to not act, which itself has an implicit CE assumption baked in.
1. The Portfolio Risk-Return Framework
It may be worth thinking about crisis giving in terms of portfolio theory. Different interventions have different risk-return profiles:
GiveWell charities: Steady, reliable impact with strong evidence (high certainty, proven returns)
Anticipatory Action: Strong expected value with good evidence (7:1 ROI, growing evidence base)
Crisis “tourniquet”: Higher variance, but with significant upside potential and bounded downside
In crisis response, the downside is bounded—even if Sudan aid is “only” as cost-effective as a standard charity, you’ve still saved lives. But the upside is significant: if you successfully prevent cascade collapse (famine to epidemic to state failure), you may have 10-100x impact. Focusing on reputable organizations (MSF, IRC, UNICEF) with operational excellence increases the probability of realizing those high returns.
A sophisticated giving portfolio can include high-certainty interventions alongside some allocation to higher-variance, higher-upside opportunities. This isn’t abandoning EA principles; it’s applying them with more nuance.
1. Portfolio Sustainability and Donor Engagement
Finally, there’s a meta-consideration: donor sustainability. Allocating 10-20% to emotionally engaging, tangible crises—even if the CE evidence is less certain—may sustain long-term commitment to effective giving. If this prevents burnout and maintains 80% highly effective giving over decades rather than years, the expected value is substantial.
This isn’t “giving in” to emotion; it’s recognizing that sustained impact requires sustainable practice. Humans are the optimization engine in EA, and maintaining that engine matters too. Personal connection to tangible crises may also help prevent the abstract utilitarian failure modes that can come from treating all suffering as mere numbers.
A Revised Framework
This suggests a more nuanced “moral portfolio” for donations:
80% Core (GiveWell): Maximizing CE on chronic, tractable problems
10% High-Impact Crisis (AA): High-CE prevention for acute, predictable problems
10% Urgent “Tourniquet” (Acute Response): High-leverage prevention for ongoing, cascading problems
Portfolio Sustainability: Maintaining long-term donor engagement and impact
From this perspective, donating to a high-quality organization (like MSF, UNICEF, or the IRC) in Sudan isn’t just a low-CE “heart” donation. It’s a defensible allocation that combines cascade prevention logic, portfolio diversification, and long-term sustainability considerations.
EA’s strength is rigorous thinking about impact. But rigor shouldn’t mean rigidity. A sophisticated giving approach can include all of these elements while remaining committed to doing the most good possible.
Sources
[1] FAO (Food and Agriculture Organization). (2023). “Impact of disasters on agriculture and food 2023.” Cites cost-benefit ratios of up to 7.1 (i.e., $1 saves $7.10) for anticipatory action.
<https://www.fao.org/3/cc7900en/online/impact-of-disasters-on-agriculture-and-food-2023/anticipatory-action-interventions.html>
[2] WFP (World Food Programme). (2025). “COP30: How Anticipatory Action helps people prepare.” Notes their first large-scale AA rollout was “at half the cost” of a traditional response.
<https://www.wfp.org/stories/cop30-how-anticipatory-action-helps-people-prepare-extreme-weather-strikes>
[3] Refugees International. (2022). “We Were Warned: Unlearned Lessons of Famine in the Horn of Africa.” Details how the “hard lessons” from the 2011 famine failure were applied to successfully avert famine in 2017-2018.
<https://www.refugeesinternational.org/reports-briefs/we-were-warned-unlearned-lessons-of-famine-in-the-horn-of-africa/>
[4] IPC (Integrated Food Security Phase Classification). (September 2024). “Sudan: Famine confirmed in El Fasher and Kadugli towns.” The official analysis confirming Famine (IPC Phase 5) and detailing that 21.2 million people faced high acute food insecurity (IPC 3+) as of September 2024.
<https://www.ipcinfo.org/ipcinfo-website/countries-in-focus-archive/issue-137/en/>
[5] Wikipedia / Health Authorities. (October 2024). “2024–2025 Sudanese cholera epidemic.” Synthesizes WHO, UNICEF, and Ministry of Health reports, noting over 120,496 cases and 3,368 deaths recorded by mid-October 2024.
<https://en.wikipedia.org/wiki/2024%E2%80%932025_Sudanese_cholera_epidemic>
For crises as severe and as underfunded as Sudan, I would question that (especially the ~2 OOM part). If I remember correctly, GiveDirectly-style cash is perhaps ~1 OOM off on cost-per-life-saved (without considering non-mortality benefits) even without a targeted population. It seems likely that an intervention like this would equal or likely beat GiveDirectly on that metric due to the particularly dire situation which people are facing.
That’s an excellent point, and you’re absolutely right to question that “1-2 OOM” heuristic. I agree with you, and I think your insight gets to the core flaw in that “default” assumption (which I was also challenging).
That heuristic seems to originate from a (now quite old) 2010 GiveWell blog post, “Can choosing the right charity double your impact?” [1]. In it, they made the case that the total range of charity effectiveness “can easily vary by 2-3 orders of magnitude” and guessed that “disaster relief funds are closer to the less-cost-effective end of the range.”
This appears to have hardened over time into a “default position.” This isn’t just because of that old post, but because GiveWell’s current research still reinforces this gap. Their top-tier picks are consistently modeled at ~$4,000-$5,500 per life saved [2], while their current minimum bar for new programs is “10x cash” (i.e., one order of magnitude) [3]. To my knowledge disaster response has never been recommended; their current page on the topic still states it “may not be the ideal cause,” effectively placing the entire category (by default) below the 10x cash threshold [4].
But as you’ve correctly pointed out, this heuristic is flawed because it lumps all disaster relief into one category.
I agree that even basic cash transfers targeted to Sudan’s crisis-affected populations are likely much more cost-effective than the old heuristic suggests—your GiveDirectly comparison is well-taken. But my argument focuses on irreplaceable service delivery like MSF, where the calculation may be even more stark. In a total system collapse, the CE calculation changes. The “tourniquet” value of an org like MSF is not “Cost of MSF” vs. “Cost of Malaria Net.” It’s “Cost of MSF” vs. “very high preventable mortality” for that specific cohort (e.g., cholera patients, surgical trauma victims) because the service is the only thing preventing the next cascade.
So, I fully agree. The 1-2 OOM gap is a flawed heuristic to apply here, and it’s highly plausible that this specific, targeted “tourniquet” intervention is dramatically more cost-effective than the old model suggests. The primary cost-effectiveness gap that remains is likely one of operational delivery in a warzone, not a lack of impact-per-dollar received by the beneficiary. The data would tell more of the story, but accessing high-quality data in a crisis is hugely challenging.
Thanks for adding that critical distinction. It’s a more accurate way to frame the problem.
[1] GiveWell. (2010). “Can choosing the right charity double your impact?” https://blog.givewell.org/2010/01/28/can-choosing-the-right-charity-double-your-impact/
[2] GiveWell. (2025). “Our Top Charities.” https://www.givewell.org/charities/top-charities
[3] GiveWell. (2024). “GiveWell’s Cost-Effectiveness Analyses.” https://www.givewell.org/how-we-work/our-criteria/cost-effectiveness/cost-effectiveness-models
[4] GiveWell. “Disaster relief charities.” https://www.givewell.org/international/disaster-relief
Allegra,
Thank you for your post. I wanted to reiterate your point that though the operating environment in Sudan makes it difficult to calculate the exact cost effectiveness of a donation, there is overwhelming evidence that suggests individuals are frequently dying from preventable causes such as cholera, malaria, dengue fever, and malnutrition. Also, as you mentioned, the humanitarian infrastructure is already in place, so resources are the principal impediment to say, providing saline drips and oral rehydration solution to prevent the spread of cholera, running community kitchens at greater scale, and distributing medical supplies and food baskets. In the past two weeks 90,000 have been displaced from El Fasher and an additional 50,000 in Khordofan—many who have arrived in Tawila are still suffering from malnutrition and need support.
Though I don’t know of any way of donating directly to the ERRs, I work with the ERRs through Mutual Aid Sudan Coalition, a project of the non-profit Proximity2Humanity. We work with ERRs in two capacities: 1) we help ease administrative burdens on ERRs (e.g., managing grant requirements, writing narrative and financial reports for donors, providing oversight and support on their reporting processes and data analysis etc.) so that they can focus on the planning and implementation of humanitarian activities across Sudan. 2) we engage in fundraising and advocacy, ensuring that international donors feel confident donating to the ERRs while also adjusting their reporting expectations to better reflect the grassroots context of the movement. So far we have raised and managed almost $5.5. million for the ERRs; money donated through us gets to ERRs in under 2 weeks, and our overhead is under 5%. Here’s the link to our site: https://www.mutualaidsudan.org/
Because we receive questions about cost effectiveness and “lives saved per dollar” frequently, we put together the following estimates of the cost per beneficiary from ERR financial reports. ERR volunteers fill out “F-5s” for every activity detailing its cost (documenting receipts etc.), type of activity, and (roughly) estimating the number of beneficiaries; we help them track and manage these reports, aggregating data that makes the following estimates possible:
$15 can provide safe evacuation, temporary shelter, and food upon arrival for one person during an emergency (based on $10 for transport + shelter and $5 for five meals)
$100 can help provide 100 hot meals through local communal kitchens. (At $1 per meal per person)
$100 can help provide medical support for 100 people, including life saving saline drips and oral rehydration solution, and clean water to prevent the spread of cholera (based on about $530K reaching ~520,000 people)
$85 helps evacuate and protect 90 people fleeing active conflict (on an average cost of under $1/person for recent evacuations)
$100 can fund emergency take-home food baskets for over 60 people in need (based on $550K reaching ~350,000 people)