Many of us can save a child’s life, if we rely on the best data
There are many ways to improve the world, but their cost-effectiveness varies immensely. You can achieve a lot more if you rely on the best data on where to donate.
Giving money to a charity is one of the best things you can do for others. As we will see, your donation can make a huge difference.
But whether or not your donation makes a difference greatly depends on where you donate. If you give your money to the least cost-effective charities, it will not do much. If you give it to an exceptionally effective charity, the same amount of money can save someone’s life.
We all feel that some charities are more effective than others, but, as we will see, we tend to underestimate just how large the differences are. I will present the data on these differences and make the point that once you know them, the question of where to donate becomes morally crucial.
How much does it cost to save someone’s life?
One reason life expectancy in the world’s richest countries is three decades longer than in the poorest countries is that they can spend much more on people’s health. Most interventions that improve people’s health — medical checks, medication, public health measures, surgeries — cost money.
For example, in the United Kingdom, the government is typically willing to spend up to about one million dollars to save a life.1 Many of us know people who would not be alive without costly treatment. Giving someone some more years to live is, of course, a fantastic way to spend money.
The share of people who donate some of their money has increased strongly in recent years. Asked whether they had donated last month, 37% answered yes in a global survey in 2023.2 In many countries, the majority donate some of their money — 61% donated in the United States, 67% in the UK, and 90% of people in Indonesia.
The total sum donated in the US was 530 billion dollars in 2022. This means the average American adult donated $2,000.3
Many of the charities that receive this money aim to improve people’s health. What do they achieve with these donations?
It’s clear to all of us that there is some variation across charities — some charities do a little worse, others do a bit better. Researchers Lucius Caviola, Stefan Schubert, and colleagues asked people how large they thought this difference to be among charities that help the world’s poorest people. They found that, on average, people believed the most effective charity to be about 1.5 times as effective as the average charity.4
The chart illustrates this perception.
To make it more memorable, let’s give these charities names. I’ll call the average charity the Good Charity, and since the top charity is even better, I’ll call it the Extraordinary Charity. For example, a 1.5-fold difference between them would mean that one million dollars given to the Good Charity would save two lives, compared to three lives for the Extraordinary Charity.
Now, the point of my article is that this perception is very far from reality.
The reality of our world is much more extreme. The difference between the average and the top charity is much larger.
In the same study, Caviola and colleagues contrast the perception of laypeople and experts in global health and charity evaluation.5 According to these experts, the difference between the average and most cost-effective charities is 100-fold, as shown in the next chart.
In the earlier example, I said the Good Charity can save two lives with one million dollars. If the ratio is 100-fold, the Extraordinary Charity could save two hundred lives with a million dollars.
Are the experts right? What does the actual data look like?
No complete dataset details the cost-effectiveness of all the world’s charities. However, plenty of good data exists on various health interventions. This data confirms that the differences across them are very, very large. At the end of the article, I reference evidence that brings together many such cost-effectiveness comparisons. Whether it is about social policy, educational interventions, or measures to reduce greenhouse gas emissions — dataset after dataset, we see very large differences across the various available options.
Here, I want to show you one of these comparisons. This is arguably the highest quality comparison that the world has. This data comes from a study called DCP3, a large global health study produced by more than 500 experts and published in nine volumes.6 For this article, I created a visualization of all cost-effectiveness estimates included in this study. You can find the details on each intervention in the DCP3 study; the point here is to see the large differences between them.
This dataset of interventions differs from a representative dataset as it is a sample of interventions that are all effective. Unfortunately, in the real world, this is not the case — governments and charities sometimes pay for health interventions that are known to be ineffective.7
Given that it is a sample of high-quality studies of health interventions that are all effective, these very large differences across health interventions are, therefore, particularly striking.
The true differences between alternatives are likely even higher than such comparisons suggest. This is because this overview only compares health interventions that are relatively easy to measure. Beyond these, there are likely charities that are even more cost-effective. One example is the work by agriculturalist Norman Borlaug, which was largely funded by charitable organizations. By improving agricultural yields, he contributed to the historical reduction of global hunger and is credited with saving the lives of dozens of millions of people; this source claims that he saved about 245 million lives. Such exceptional charitable work can, at times, be extraordinarily cost-effective.
There are extraordinary charities
Of course, this data is hugely important for those who donate money to charities. If we can find charities that implement the most cost-effective health interventions, we can achieve much more with our money.
Several meta-charities called “charity evaluators” have solved the practical problem of finding these charities.
This field saw a revolution in recent years, and I think it has been one of the most important trends in global development research. Before this revolution, there was a fierce debate about aid effectiveness, with some people strongly opposing it and others strongly supporting it. In the last decade, this heated debate has made space for a more clear-eyed approach that acknowledges that many charities are not effective at all while others are extraordinarily effective.8
The research teams at charity evaluators find that many charities are not very effective — and tragically, the very worst ones actually achieve the opposite of what they set out to do. Some people's skepticism about charities has a foundation. But what charity skeptics overlook is that there are some outstanding charities at the other end of the spectrum. The best charities are extraordinarily effective and can do a lot with relatively little money.
At the start of this article, we saw that the UK is willing to spend about $1M to save a person’s life. What does the evidence look like for the most cost-effective charities in the world?
The charity evaluator that I have personally relied on over the past years for my own donations is called GiveWell. In 2024, GiveWell decided to support our work on Our World in Data with a grant; given that I consider them to be extraordinarily thorough in their evaluation of non-profits, I am particularly honored and proud that they decided to support our work.9
GiveWell found four charities that can save a child’s life for about $5,000 in donations.10
The four charities that achieve this level of cost-effectiveness do quite different things. One focuses on providing vitamin A supplements to children, the second provides seasonal medicine to protect children from malaria, the third distributes bednets to protect children from malaria, and the fourth incentivizes caregivers to give children their necessary vaccinations.
While they all do different things, they have two things in common. They all focus on the world’s poorest people, which makes sense as $1,000 makes a much larger difference to someone who has very little. They also all tend to focus on causes that don’t receive much public attention. That makes sense, too — for the causes that receive the most attention, all the lowest-hanging fruits have already been picked.
These charities are concrete, real-life examples of the Extraordinary Charity I mentioned at the start of my article.
The example I gave above — the difference between spending $1,000,000 to save a life in the UK and $5,000 to save a life with the world’s most cost-effective charity — is real. For $1M donated to the most cost-effective charities, we can expect to save the lives of 200 children.
This gives us an incredible opportunity to help others. I think spending a million dollars to save a person’s life in the UK is a very good way to spend money — but it’s fantastic that the best opportunities can do so much more.
Good data can save lives
What does all this mean for our own donations?
I think the data we’ve seen needs to be at the center of the ethical decisions we make in our lives.11 The fact that the best charities are much more cost-effective than the average ones is morally important.
Our resources are limited; we cannot do it all. We have to choose what we do with our limited means, and this data can help us tremendously. Giving to the Good Charity when you could give it to a 100 times more cost-effective Extraordinary Charity is a big mistake.
Or viewed more positively, if you give $1,000 to an Extraordinary Charity, you can achieve more than someone who gives $90,000 to a Good Charity.
The best charities are not just a bit better than the average ones but way, way, way better. For anyone wanting to make the world a better place, I believe this is one of the most important facts to know about the world. This is so important to take in because it goes strongly against our intuition — we’ve seen above that most people think the best charities are about 50% better than average — and because it is morally important for the limited resources that we have in our lives.
You have a great opportunity right in front of you. Many people in high-income countries have the chance to give away $5,000. Perhaps not in one moment, but it is possible for many over a longer period.
Saving a child’s life is certainly something that everybody can be extremely proud of. Guided by research on differences in cost-effectiveness, many people can do this.
More data on differences in cost-effectiveness:
In the article, I focused on health interventions. However, very large differences in cost-effectiveness exist in many other policy areas. Benjamin Todd wrote a great overview article, combining datasets from many fields. It includes datasets on social policies, educational interventions, criminal justice policies, interventions to reduce greenhouse gas emissions, and more. Here is the article by Todd (2023): How much do solutions to social problems differ in their effectiveness? A collection of all the studies we could find.
Such differences also exist in other aspects of life. This suggests that we should often spend a lot of time thinking about what we want to do instead of doing whatever is most convenient or is right in front of us.
Acknowledgments: I would like to thank Edouard Mathieu for his helpful comments on drafts of this essay and the visualizations. I would also like to thank the authors of the cited study — Stefan Schubert and Lucius Caviola — for answering my questions and advising me on this article.
Explore more research and data on Our World in Data:
Child mortality: an everyday tragedy of enormous scale that we can make progress against
We live in a world in which 10 children die every minute.
Endnotes
In health economics, “lives saved per money spent” is not the typical unit of measurement. Instead, researchers and policymakers consider cost-effectiveness using indicators called ICERs, QALYs, or DALYs.
However, because the units of measurement in health economics are a bit more arcane and much less intuitive to those who have not heard about them before, I avoid them in my article. In the context of my article, I think it is most helpful to think of “lives saved per money spent”, and crucially, the main insight of the article — cost-effectiveness differs a lot between different possible alternatives — holds true no matter which metrics you consider.
Health economists and policymakers consider the Incremental Cost-Effectiveness Ratio, or ICER, as the key metric. This is the ratio between the additional cost of one unit of the health intervention and its additional health benefit.
In the UK, health benefits are usually measured not as lives saved but as a more fine-grained unit of measurement. Typically, it is measured as one additional quality-adjusted life year, or QALY.
The National Institute for Health and Care Excellence (NICE) is the UK institution responsible for conducting these assessments.
NICE recommends spending up to an ICER of £30,000 per QALY gained.
The ratio between QALYs gained and lives saved depends on the population's structure and its particular health conditions. A conservative multiplier in global health is that 27 additional QALYs are equivalent to saving one additional life (for an alternative, see this analysis of the cost of saving a child’s life through the efforts of the Against Malaria Foundation in which saving a life is equivalent to averting 36.5 DALYs).
This tells us that the implied approved cost of saving a life in the UK is 27 x £30,000 = £810,000 = $1,015,000.
At times, higher ICERs have been approved in the UK. NICE approved, for example, the drug lenalidomide to treat myeloma with an ICER of £43,800. Applying the 27-x multiplier implies a cost per life saved of £1,182,600 or, at the current exchange rate, about $1.5M.
This illustrates that there is no fixed, irrevocable cutoff for the cost of saving a life in the UK healthcare system: the ICER is not fixed, and the ratio by which one can convert QALYs gained into lives saved is not a constant either. However, the data points I cited suggest that the implied willingness to save one life is conservatively estimated at $1M.
For more context, the Wikipedia entry on the “value of life” provides a great overview. The entry discusses the concepts of the value of preventing a fatality (VPF) and the implied cost of averting a fatality (ICAF), various methods for estimating them, and cites many comparable data points from other countries. This also makes clear that the number that I am relying on — one million dollars — is on the low end among high-income countries. Therefore, the cost-effectiveness differential I am focusing on in my article is also on the lower end of the spectrum.
Two additional studies, Owen et al. (2018) and Daroudi et al. (2021), provide more background.
For an overview of the cost-effectiveness of various health interventions in the UK see Owen et al. (2018) — The cost-effectiveness of public health interventions examined by NICE from 2011 to 2016. In Journal of Public Health, Volume 40, Issue 3, September 2018.
The study by Daroudi et al. (2021) estimates the implied cost per DALY averted across countries. The authors find very large differences. The difference between the cost for each averted DALY was even higher than the difference between GDP per capita between poor and rich countries. On average, the cost per DALY averted was 0.34 times the GDP per capita in low HDI countries and 1.46 times the GDP per capita in very high HDI countries. The cost per DALY averted was $998 in low HDI countries and $69,499 in very high HDI countries. A ratio of 70.
Rajabali Daroudi, Ali Akbari Sari, Azin Nahvijou & Ahmad Faramarzi (2021) — Cost per DALY averted in low, middle- and high-income countries: evidence from the global burden of disease study to estimate the cost-effectiveness thresholds. In Cost Effectiveness and Resource Allocation.
In 2013, the share answering yes was 28%. This data is from the Gallup World Poll for 2023. The data refers to the share who answered “yes” to the following question: “Have you done any of the following in the past month? How about donated money to a charity?”
The source of the data point that 530 billion dollars were donated in the US in 2022 is taken from “Giving USA”, givingusa.org. It is the latest available data as of April 2024.
The US adult (18+) population in 2022 was 264 million. So the average per American adult was $528,000,000,000 / 264,000,000 = $2000.
Lucius Caviola, Stefan Schubert, Elliot Teperman, David Moss, Spencer Greenberg and Nadira S. Faber (2020) – Donors vastly underestimate differences in charities’ effectiveness. In Judgment and Decision Making, Volume 15 Issue 4.
The ratio cited here (1.5) was the most common response, but there was some variation in the replies depending on the phrasing that was used in the researchers’ questions (tipping point, explicit comparison, and cost-per-life ratio). The highest ratio was 2 in the explicit comparison phrasing, vastly lower than the estimates of experts.
The researchers selected “experts in areas relevant to the estimation of global poverty charity effectiveness, in areas such as health economics, international development, and charity measurement and evaluation. The experts were identified through searches in published academic literature on global poverty intervention effectiveness and among professional organizations working in charity evaluation.” The sample of experts who shared their expertise with the researchers included 45 individuals.
DCP stands for Disease Control Priorities, and the current third edition is published at dcp-3.org.
Homeopathy is an example. It has no efficacy beyond that of the placebo effect. Yet, several public healthcare systems support homeopathic treatments. However, this has changed in recent years: The National Health Service in England no longer provides funding for homeopathic remedies, and France, too, has moved away from it. Homeopathy remains a multi-billion dollar industry and very popular in countries like Germany (imagine what we could do if this money were available for effective interventions to stop children from dying!).
One of the main breakthroughs in this regard was the application of randomized controlled trials in development research, pioneered by Nobel winners Michael Kremer, Esther Duflo, Abhijit Banerjee, among others. My colleague Saloni Dattani has written a detailed article on this methodology for Our World in Data: Why randomized controlled trials matter and the procedures that strengthen them
Today, there is still a debate about large questions in development research. Some scholars argue that we risk losing sight of how crucial economic growth is for improving people's health and well-being. They believe that focusing on particular interventions distracts us from the big challenge: how can poor countries become rich? See Lant Pritchett's recent writing on this and related points.
I agree with this view in many ways — see, for example, this article, this article, and this article of mine here on Our World in Data. However, for most of us individually, there is little we can do on the margin to make an economy grow, and the focus of this article is what each of us can do with our resources. I believe the research on individual interventions has been very helpful for this particular question and brought clarity and evidence to the debate.
Crucially, it is also the case that those interventions that are the focus of this article are often considered worthwhile by even the harshest critics of aid. On this point, see Holden Karnofsky’s The lack of controversy over well-targeted aid.
I have trusted GiveWell personally for many years because they are thorough in their assessments of charities and very transparent about how they arrive at their recommendations. Their write-ups make clear that they aim to be guided by the best available scientific evidence.
The full draft of this article was written in 2023 before GiveWell started considering supporting our non-profit with a grant.
UPDATE on 15 September, 2024: GiveWell’s announcement of a $400,000 grant to support our work on Our World in Data is now published here. In their announcement, they say that “This is an unrestricted grant, intended to provide broad support to an organization that produces high-quality research and is an important resource for GiveWell’s grantmaking. We are recommending this grant because OWID is a unique resource that is helpful to GiveWell in its work”.
$5,000 is a rounded number and currently (in April 2024) very close to GiveWell’s best estimates. Their estimates of the cost of saving a life vary over time, as they depend on which opportunities are available and as new research revises earlier findings. At the time of writing, they estimated that their top charities had an average cost-effectiveness of $5,500 (Against Malaria Foundation), $5,000 (Malaria Consortium), $5,000 (Helen Keller International), and $5,000 (New Incentives) per life saved.
There are sometimes large differences within countries. For example, in their report on Helen Keller International, they write, ”As of February 2024, we estimate that it costs between ~$1,000 and ~$8,500 (varying by country) to avert a death through Helen Keller-supported VAS campaigns.”
I respect and trust them because they are very transparent about how they arrive at these estimates. See here for a start.
On this topic, see the following beautiful essay: Toby Ord (2013) — The Moral Imperative toward Cost-Effectiveness in Global Health, published by the Center for Global Development.
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Max Roser (2024) - “Many of us can save a child’s life, if we rely on the best data” Published online at OurWorldinData.org. Retrieved from: 'https://ourworldindata.org/cost-effectiveness' [Online Resource]BibTeX citation
@article{owid-cost-effectiveness,
author = {Max Roser},
title = {Many of us can save a child’s life, if we rely on the best data},
journal = {Our World in Data},
year = {2024},
note = {https://ourworldindata.org/cost-effectiveness}
}
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