Forecast: The Impact of USAID Malaria Cuts
by Bruce Tsai
More than 600,000 people die every year from malaria — just under 1% of all yearly deaths. Nearly half of the world’s population is at risk of infection. The vast majority of deaths are in sub-Saharan Africa, over 80% among children under 5, making malaria a leading cause of childhood mortality.
It also inflicts a heavy economic burden. Endemic malaria slows GDP growth by as much as 1.3% annually in hard-hit countries, perpetuating cycles of poverty and underdevelopment.
We have made significant progress on malaria control; it has been successfully eliminated in more than 40 countries.1 Annual malaria deaths have dropped from a peak of 900,000 in the early 2000s to around 600,000 today.2 Malaria incidence and mortality in Africa, specifically, have fallen roughly 40% over the same period.
However, progress on malaria control depends on steady effort, and therefore funding. When routine services are disrupted, cases and deaths can surge rapidly. For example, malaria death rates increased in 2020 for the first time in two decades, primarily a result of COVID-related disruptions to services.3 A smaller increase also occurred during the 2014 Ebola outbreak, which overwhelmed health systems in West Africa. These cases illustrate how temporary disruptions can reverse progress in malaria control, and point to the potentially devastating consequences of the more extensive reductions in aid now being undertaken by the Trump administration.4
A brief history
USAID (and its predecessor programs) first became involved in malaria control during the 1950s and 1960s, when the global community embarked on the Global Malaria Eradication Program, primarily through DDT spraying and mass drug administration. That campaign achieved malaria elimination in Europe, North America, the Caribbean, and parts of Asia and South America. USAID has been contributing to malaria control ever since, making it one of the agency’s longest-running global health commitments.
USAID initiated the Malaria Vaccine Development Programme, which laid the groundwork for both of the malaria vaccines that are approved for use today. The United States has also contributed significantly to the development of many antimalarials, first via military research and then later via USAID, which helped advance artemisinin-based combination therapies (ACT)5 in the late 1990s onwards, when drug-resistant malaria was spreading.
Modern malaria control efforts began in the 2000s. In 2003, the US Leadership Against HIV/AIDS, Tuberculosis, and Malaria Act authorized significant funding for both bilateral programs as well as the then-recently created Global Fund, which is now the world’s largest overall funder of malaria efforts.6 In 2005, the US government launched the President’s Malaria Initiative (PMI), with the goal of rapidly scaling-up proven interventions (insecticide-treated nets, indoor-residual spraying, artemisinin-based combination therapies).7 PMI now operates in 27 countries: 24 in sub-Saharan Africa, and three in Asia. It has invested over $9 billion since inception and represents about 20% of all global malaria funding today.
2025 US foreign aid developments
It is unclear how much of USAID’s roughly $800 million budget for malaria funding is impacted after the initial cuts. A recent CGDev estimate puts the cuts at around 29%, while a forecasting report commissioned by GiveWell and Open Philanthropy estimates a 44% decrease when comparing FY2026 with FY2024. Most recently, the Trump administration released its FY2026 budget request, which represents a ~62% cut to total global health spending, though the extent to which USAID is cut is to be determined.8
Estimates of excess deaths attributable to Malaria
I estimate:
A full 90-day funding freeze will lead to between 18,000 and 39,000 excess malaria deaths [more]
A full one-year funding freeze will lead to between 43,000 and 90,000 excess malaria deaths [more]
A full five-year funding freeze will lead to between 250,000 and 410,000 excess malaria deaths [more]
To arrive at these numbers, I first estimate the effect of a one-year funding freeze, then adjust those results to approximate impacts over 90 days and five years. I model two main disruption scenarios — one that includes the President’s Malaria Initiative9 only, and PMI + the US-funded portion of the Global Fund.10
For these estimates, we were asked to assume 100% of funding would be frozen to start, although I also consider scenarios with partial disruptions and donor compensation, based on the aforementioned estimates, and use these to inform my topline estimates.
However, discussions with USAID sources suggest that despite waivers and previous terminations being rescinded, payments have not been coming through. Combined with other operational and logistical challenges, and the RIF that is due to take effect later this year,11 it’s plausible that the 100% cut is closer to the real-life impacts than the 29% cut for the shorter time frames, though the exact figures are difficult to estimate.
I take a weighted average of four different estimates to come to a rough figure for excess malaria deaths over one year.12
Method 1 (Malaria Atlas Project model) [more]
Topline figure: 107,000 to 216,000 excess malaria deaths for a one-year projection
For my first estimate, I defer to modeling done by the Malaria Atlas Project (MAP). According to MAP, PMI funded by business-as-usual contributions was likely to avert 107,000 deaths in Africa in 2025. This serves as a reasonable benchmark for the one-year scenario.
I estimate that PMI accounts for 20% of global malaria funding.13 The Global Fund in total accounts for another 62%. The United States funds about 33% of the Global Fund, which is equivalent to another ~20% in total malaria funding from the United States.14 Given this, the two scenarios are:
~20% cut, representing all PMI activities being halted.
~40% of all malaria funding, attributable to PMI + Global Fund.15
PMI only: ~107,000 excess deaths
PMI + Global Fund: ~216,000 excess deaths
Method 2 (estimating impacts based on case studies of previous disruptions) [more]
Topline figure: 102,000-240,000 excess malaria deaths for a one-year projection
We can also look at real-world evidence in the form of two actual disruptions to malaria services: COVID-19 and the 2014 Ebola outbreak.
First, I take the average increase in excess mortality from several sources. One analysis found that an 8% decrease in access to antimalarials resulted in an 8% increase in excess deaths during the 2020-2021 period of the pandemic. Another model, done early in the pandemic, suggested a 35%, 66%, and 99% increase in deaths for a 25%, 50%, and 75% reduction in services, respectively. Taken together, these figures translate to an increase of approximately 11% excess deaths for an 8% disruption.
In absolute numbers, this would be 62,000 excess deaths. Later calculations from the WHO based on real data suggested that there were 47,000 deaths attributable to disruptions to malaria interventions. Adjusting for this overestimate, the true ratio is approximately a 10% increase in deaths for a 10% disruption.
We can then compare these estimates with disruptions that occurred during the 2014 Ebola outbreak. One study found that a 50% reduction in treatment coverage increased malaria deaths by roughly 50% — equivalent again to a roughly 10% increase in deaths for a 10% disruption. Another estimate suggested that the absence of hospital and clinic services for malaria resulted in an increase in malaria-attributable mortality of 35% in Guinea, 50% in Sierra Leone, and 62% in Liberia. This (very crudely) translates to an average of 4.9% increase in mortality for a 10% disruption.
These scenarios suggest that a 10% disruption in malaria services results in an 8.6% increase in deaths, on average.
I again estimate two scenarios: one in which either PMI or Global Fund contributions cease, and the other in which both PMI and Global Fund contributions cease.
For my lower bound, I use the average ratio at which disruptions in malaria funding increase deaths (i.e., 8.6% increase in mortality for a 10% reduction in services), and assume cuts only to PMI.16 For my upper bound I use a 1:1 ratio (i.e., 10% increase in mortality for a 10% reduction in services) and assume cuts to both.
This works out to:
PMI only, more conservative ratio: ~102,000 excess deaths
PMI + Global Fund; 1:1 ratio: ~240,000 excess deaths17
Method 3 (WHO averted deaths adjustment) [more]
Topline figure: 190,000 to 380,000 excess malaria deaths for a one-year projection.18
The WHO estimates19 malaria interventions averted over one million deaths in 2023.20 This likely overstates the benefits directly attributable to interventions specifically, because it overlooks reductions in malaria burden that would have happened absent any malaria-specific interventions, including economic growth, better urban planning, WASH interventions, and more. However, it serves as a useful upper range. Pegging this to the total percentage of malaria funding provided by PMI and the Global Fund gives us:
PMI only: ~190,000 excess deaths
PMI + Global Fund: ~380,000 excess deaths
Method 4 (CGDev estimates) [more]
Topline figure: 140,000 to 290,000 excess malaria deaths for a one-year projection.
I defer to CGDev’s “gross estimates” in table 1, which includes both deaths averted by PMI and the US-funded portion of the Global Fund, and calculate the PMI-only figure from there. Methodologically, this is very similar to method 3 (WHO).
PMI only: ~140,000 excess deaths
PMI + Global Fund: ~290,000 excess deaths
Time frame adjustments
Harms won’t be uniform over time. For the first few weeks or months of the pause, countries will still have access to stockpiles of bed nets and medication. We may also see other countries reallocate resources over time. However, there’s also the possibility that there will be increased harms if malaria is reintroduced or becomes endemic in new areas, as well as second order effects of a sudden surge in malaria cases.
Adjustment based on PMI figures [more]
For the 90-day estimate, I defer to PMI’s methodology and apply their ratio to my estimates above. [more]
PMI estimates 17,000 deaths in the first 90 days, and 107,000 deaths for the year, for a ratio of 0.159, or ~16% of total projected deaths.
For the five-year period, I extrapolate from months 6-12 rather than the entire year to estimate excess deaths, as the mortality rate will be slower in the first few months after the pause. This gives a ratio of 5.77 compared with just taking the year-one figures.21 For adjustments modeling compensation for lost funding, see footnote here.22
Conclusion
Based on these adjustments, I arrive at my final best guess topline figures: 18,000 to 39,000 excess deaths in the next 90 days, 43,000 to 90,000 excess deaths in the next 12 months, and 250,000 to 410,000 deaths in the next five years.23
These figures probably err conservative (i.e., on the low end), given the information I currently have.24
In the worst-case scenarios, in which this money had not been resumed, we might have seen 94,000 to 200,000 deaths in the next 12 months, and 540,000 to 920,000 deaths in the next five years.
Overall, the USAID funding cut represents a significant setback to global efforts to control malaria. If affected programs on the ground don’t restart in a meaningful way, death tolls could return to levels we haven’t seen in over a decade. For the sake of saving 0.02% of federal spending,25 we risk unraveling years of hard-won progress against one of the most difficult diseases humanity has faced. And with every passing week, thousands — predominantly children — pay the price.
Bruce Tsai is an independent researcher working across global health, futures studies, and AI governance. He has consulted for organizations spanning health, philanthropy, and technology, including Fortify Health, Weiss Asset Management Foundation, and OpenAI. He previously worked at Rethink Priorities and collaborated with the Future of Humanity Institute as an independent contractor. He holds a medical degree from the University of Auckland.
COVID-19 disruptions in 2020 led to an additional 69,000 malaria deaths (a 12% increase vs. 2019) due to interrupted services — more than two-thirds (47,000) of which were linked to “disruptions in the provision of malaria prevention, diagnosis and treatment during the pandemic.”
If malaria care ceased as a result of the Ebola epidemic, untreated cases of malaria would have increased by 45% (95% credible interval 43-49) in Guinea, 88% (83-93) in Sierra Leone, and 140% (135-147) in Liberia in 2014. This increase is equivalent to 3.5 million (95% credible interval 2.6 million to 4.9 million) additional untreated cases, with 10,900 (5,700-21,400) additional malaria-attributable deaths.
ACTs combine an artemisinin derivative with another longer-acting antimalarial drug. The rapid action of the artemisinin component quickly reduces parasite levels, while the partner drug eliminates any remaining parasites and reduces the risk of artemisinin resistance.
Global Fund claims to cover ~62% of all malaria funding, which would be about 2.5 billion in recent years and 19.1 billion throughout its existence.
Through the Global Fund and PMI, malaria financing in endemic countries increased 10x between 1998 and 2006.
Based on discussions with sources, the administration seems to be indicating that the President's Emergency Plan for AIDS Relief (PEPFAR) funding will make up the bulk of what will continue under the reduced budget. As this funding came from the State Department, this implies that USAID-funded programming (where malaria sits) would likely require a larger cut to get to the overall figure of 62%. A leaked memo also outlines a redesigned successor to USAID, though it contains no funding specifics.
The PMI is an interagency initiative that includes representatives from USAID, the CDC, and the Department of State, among others. It is overseen by the US Global Malaria Coordinator, which is housed within USAID.
See more in Method 1. For brevity, where I refer to “Global Fund” in these calculations, I am referring to the one-third that is US-funded.
Two final separation dates are July and September 2025.
I weigh them at a ratio of 2:2:1:1, as methods 3 and 4 are very similar, and I don’t want to treat them as independent approaches.
~$750 million year.
Here I assume US contributions are fairly similar across all Global Fund activities.
This doesn’t account for other countries funding more, though it’s not obvious this will happen. For example, the UK (currently the third-largest donor) is considering downsizing its foreign aid budget.
I decided to use the average ratio for the lower bound rather than the lowest figure. The lower range of ~5% increase mortality per 10% disruption in services is based on one paper that models 100% reduction, so I think using that as the lower bound would be putting too much weight on that calculation (and associated assumptions). For the upper estimate, I still use the upper bound of ~10% increase per 10% disruption.
597,000 * 0.1 = 59,700
597,000 * 0.4 = 238,800
I considered removing this method given the methodological issues described and how surprisingly convergent the first two methods were, but ultimately decided to preserve this to guard against the risks of post-hoc justification.
WHO malaria report 2024 page 8, table 2.1.
WHO malaria report 2024 page 24, figure 2.10. Their methodology compares “the current annual estimated burden of malaria with the malaria case incidence and mortality rate from 2000, assuming that, as a comparison, they remained constant throughout the same period.”
((107000-43200)*2*4 + 107000) / (107000*5) * 5 = 5.77009346
I include a more conservative estimate of malaria mortality based on the assumption that other countries or actors might compensate for lost funding. It’s unreasonably pessimistic to expect 100% cuts, especially over longer time frames. For my best-guess figure, I discount by the average of the CGDev estimates (29%), and a forecasting report commissioned by GiveWell and Open Philanthropy (44%), and the recently released President’s FY2026 discretionary budget request (62%). This comes to an average cut size of ~45%.
I apply a further 25% discount, based on the extent to which original COVID-19 projections were overestimated. This discount essentially assumes that both the original final excess death estimates were reasonable, and the difference is explained by countries responding better than expected, and that something similar will also happen with malaria, to the same extent. For ease of modeling, I assume this happens on day one for both one- and five-year periods, but only for the last month of the 90-day version. I assume that the Global Fund replenishment cycle is affected entirely for the remainder of the current implementation period (2024-2026), given the fundraising period is 2023-2025, but restored or covered by other countries for the next implementation period. Given that inflation-adjusted global fund money has stayed rather stagnant over the last three replenishment cycles, I assume this remains true. I then combine the two compensation approaches (i.e., the 25% discount for the first two years), and then assume the Global Fund replenishment returns for the last three. This applies only to the upper bound figure, as the lower bound figure already assumes Global Fund money is unaffected. Of course, in practice we should expect neither 100% return nor 0% return. [more]
To arrive here, I assume only a ~45% cut to total USAID funding rather than a 100% cut, and include another 25% discount to model some kind of compensation (e.g., due to contributions from other countries, redistributions, or stopgap measures taken by the government, or other reasons that may have contributed to the discrepancy between early excess mortality estimates and actual deaths due to COVID-19-related disruptions that might generalize to this context). These numbers also assume that Global Fund cycles will be at ~0 for the remainder of the current cycle (likely pessimistic) and returns back to normal for the next cycle (likely optimistic).
The most likely way this estimate is wrong is due to funding changes that are quite different from the estimates used, or specific facts about malaria transmission, or the impacts of other interventions (IRS, IPTp, injectable artesunate, etc.) that I haven’t accounted for. There are also other variables of interest I haven’t accounted for, like increased immunity to malaria or increased drug resistance or excess mortality due to overworked health systems, or other deaths due to redistribution, societal effects such as impacts on civil conflict, crop yields, and so on. Lastly, another reason would be if there were reasons to think that the population at risk due to disruptions is significantly different than the estimates I use.