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Hypothesis: Humanitarian funding is not distributed across crises only according to need, but political interests and public awareness about each humanitarian crisis.
In any resource-allocation decision, there are forces pushing in multiple directions and humanitarian funding should not be different. Humanitarian operations happen in some of the most watched conflicts in the world, they interact with military, political, and economic interests that are orders of magnitude larger and would like to influence them.
To test this, we assessed humanitarian response plans funded in 2024 compared with the number of people in need stated in each of these plans to come up with a value for dollars spent per person in need in a humanitarian crisis. This data is available from the UN Office for the Coordination of Humanitarian Affairs (OCHA).[1]
“Humanitarian Response Plans” (HRPs) are done annually until a response is more or less considered over. The experts involved in estimating the population in need in a country are similar professionals using a similar methodology, budgeting similar response programs. While the data contained may be biased or wrong in different ways, errors are likely to be in similar directions across plans.
The first result was this graph:
This is not an unreasonable dispersion, we would prefer a flat one, but it is easy to understand why Ukraine stands first: It is a brutal conflict and also an expensive location to operate a humanitarian response. It is sad to see so many Latin American countries at the bottom, but at first sight they seem to be having less dramatic situations than the top 10 countries. Sudan’s place around the middle is probably wrong, but all observers would agree this is a neglected crisis and this is what the data reflects. Myanmar is not that poorly funded, but the number of people in need is very large. Chad’s position is slightly surprising, and Cameroon’s position is the least funded African humanitarian crisis in line with what has been published in the past. However, we should not pay too much attention to fine differences within the ranking, our analysis is a simplification of very complex processes and funding decisions.
A few big crises were missing from this analysis. “Humanitarian Response Plans” (HRPs) are not the only type of humanitarian plans used in 2024. There are other instruments that work similarly. There were 10 “Flash Appeals” in this same period. Flash appeals are a tool intended to be a more agile version of the Humanitarian Response Plans, covering the first 3 or 6 months of a crisis. There are other types of plans such as regional response plans (funding for operations in countries receiving refugees rather than those where refugees come from). Flash appeals appear relevant to this comparison, so we also included them. Regional refugee responses are complex to compare with the others, and generally happen in better-off countries, so we excluded them for now.
Including the flash appeals brought us extreme outliers for both ends, Libya, Lebanon, and Palestine at the top, and Zambia and Malawi at the bottom. This is reasonable considering they are more agile tools.
We would love to hear your own thoughts. These are some of ours:
- It is extremely unlikely that an extra dollar in Guatemala, Malawi, or Zambia is 90 times less lifesaving than an extra dollar in Palestine, and it is fairly likely that it is more useful.
- We recommend to any individual or institution thinking of sending funds to a humanitarian response, to send to programs and individuals in countries on the bottom 10 of this list, particularly if their first inclination had been to send to countries on the top 5 of this list.
- Many of the countries at the bottom are fairly peaceful or have conflicts of a smaller magnitude. Most countries at the top have the wars everyone knows about. We will explore in another post the link between fatality and funding, and we encourage others to think about that!
Thanks for sharing this analysis, very interesting.
Thank you very much! we will repeat the analysis at the end of 2025 with 2025's data.