Against Malaria Foundation — Support for ITN Campaigns in DRC (June 2023)

Note: This page summarizes the rationale behind a GiveWell-recommended grant to the Against Malaria Foundation (AMF). The information below reflects our views at the time we made the grant decision and does not reflect any information we have learned or work we have done since that point. AMF staff reviewed this page prior to publication.

In 2023, we considered a grant to AMF to fund a large portion of the funding gap for ITNs in DRC in 2024-26 (~$50-100 million). As we investigated this grant, we realized that there were significant gaps in our understanding of key parameters, such as the proportion of nets that reach households and are not overallocated (more). However, given the time-sensitivity of a grant decision for a net campaign in 2024, we decided to make a smaller grant for this campaign only. In 2024, after conducting significant additional research, we recommended another grant to fund AMF to support ITN distribution in DRC for 2025-26. That grant page better represents our current views of this program.

Published: June 2025

Summary

Background

In June 2023, GiveWell made a $17.5 million grant to the Against Malaria Foundation (AMF) to purchase insecticide-treated nets (ITNs) that will be distributed in campaigns scheduled to occur in 2024 in the Democratic Republic of the Congo (DRC). AMF is one of GiveWell's top charities.

We recommended this grant because our best guess is that its cost-effectiveness will be greater than 10x as effective as unconditional cash transfers, our funding bar as of June 2023. We believe this grant will cause ITN campaigns to happen sooner than they otherwise would have, reducing the amount of time people are unprotected against malaria.

Our reservations about this grant are:

• We have substantial uncertainty about the level of burden of malaria in the areas this grant would fund, due to concerns about both the national and subnational data available to us.
• We have several concerns about the evidence we use to estimate the effect of reducing childhood malaria cases on income gains later in life.
• We don’t expect the grant itself to update our understanding of how much it costs to distribute an ITN in DRC or what portion of distributed ITNs reach people who were previously unprotected by nets. We may fund other work on those questions.
• Our estimate of how much AMF’s support will speed up ITN campaigns is speculative, as it is based on guesses about what will happen in the future under different funding scenarios.

What we think this grant will do

Malaria is a key driver of under-5 mortality in the DRC.2 Insecticide-treated nets (ITNs) are nets which have been treated with a durable insecticide to deter and kill the mosquitoes that transmit malaria. They are typically hung over beds to provide protection during sleep. (more)

With this grant, AMF will purchase ITNs in bulk, provide them to its distribution partners in DRC, and manage the monitoring of ITNs while in transit, during distribution, and after distribution. AMF has been regularly supporting ITN campaigns in DRC since 20193 , with ongoing funding from GiveWell.4 (more)

We anticipate the main impact of this grant will be reducing the amount of time that people are unprotected by ITNs, which leads to a reduction in deaths from malaria for children and adults. (more)

Why we made this grant

We estimate that the cost-effectiveness of this grant is above our funding bar. Our best guess is this grant is roughly 15 times as cost-effective as unconditional cash transfers, which is above our cost-effectiveness bar of 10x cash as of June 2023. Intuitively, this is because we think:

• ITNs are relatively inexpensive to provide. (more)
• AMF providing ITNs will increase the amount of time that people under age 5 are sleeping under ITNs that provide effective protection from malaria. (more)
• Malaria is a major driver of child mortality in DRC. (more)
• ITNs provide strong protection against malaria and deaths caused by malaria. (more)
• In addition to preventing childhood malaria deaths, we think ITNs provide additional benefits by protecting individuals above age 5 from malaria mortality and causing long-term income increases later in life. (more)

A sketch of our cost-effectiveness analysis is below:

	Best guess	25th-75th percentile range for key parameters	Cost-effectiveness over that range
Grant size	$17.5 million
Total amount spent on the program by all contributors	$34.7 million
Mortality benefits of the program
Cost per person under age five reached	$28	$21 – $36	13x – 18x
Number of children under 5 reached5	1.25 million
Years of effective coverage provided by ITNs	1.2	0.9 – 1.6	13x – 18x
Annual malaria mortality rate among children who do not receive ITNs	.80%	0.46% – 1.13%	11x – 18x
Reduction in malaria mortality rate from ITNs	56%	50% – 62%	14x – 16x
Number of deaths averted among people under age five (1.25 million x 1.2 x .8% x 56%)	6,600
Cost per under-five death averted ($34.7 million / 6,600)	$5,200
Moral weight for each death averted (we use moral weights to compare outcomes like deaths averted and increases in income)	116
Cost-effectiveness from mortality benefits only(times more cost-effective than providing unconditional cash transfers in the world’s poorest communities, “x cash”)	6.6x
We also incorporate other benefits. In the final assessment, % of benefits from…
Mortalities averted for people under age five	56%
Mortalities averted for people age five and older	8%	6% – 13%6	14x – 16x
Improved child development (increases in adult income)	35%	32% – 53%7	14x – 21x
To reach a final cost-effectiveness estimate, we incorporate additional adjustments for program effectiveness, including…
Additional program benefits and downsides	48%	37% – 61%	14x – 16x
Quality of program monitoring and evaluation	-4%	-20% – -2%	12x – 15x
Funding causing other entities to spend less on the program than they otherwise would have	-10%	-23% – -3%	13x – 16x
Overall cost-effectiveness (“x cash”)	~15x cash

You can see our full cost-effectiveness analysis for this grant here and a simple version here.

Main reservations

• How many deaths are caused by malaria in DRC? We estimate that without ITNs, a child under five in DRC has a 0.80%8 annual chance of dying from malaria. (more) This estimate, which we don’t expect to update based on this grant, comes with several caveats:
  • Reliable record-keeping on mortality causes in malaria-endemic countries, including DRC, is often lacking.9
  • Our analysis uses malaria mortality and net usage estimates from the Global Burden of Disease (GBD) project. GBD's estimates involve multiple modeling assumptions with wide confidence intervals. (more)
  • We make an additional assumption that for every 1 death directly attributed to malaria, we estimate an additional 0.75 deaths attributed to another cause by the GBD are indirectly caused by malaria. This figure is the result of rough empirical estimates and expert consultation. (more)
• How much do nets increase income later in life? Our best guess is that averting childhood malaria cases leads to small income gains in adulthood. We estimate that the impact that ITNs have on income gains in adulthood accounts for 35%10 of the benefits of AMF’s program in DRC. However, we have several uncertainties about the evidence on which we base these estimates, and this grant will not update our understanding of these. (more)
• How much does it cost to reach children with nets? We estimate that it costs roughly $2811 per additional child sleeping under a net in DRC. Our larger sources of uncertainty in this estimate are:
  • What is the total cost to procure and distribute an ITN in DRC? We estimate that the total cost to distribute an ITN in DRC is $5.8512 , which is higher than in other locations where AMF supports net campaigns. This is based on three main inputs: the cost to deliver an ITN to a household in DRC, AMF's projection of the cost to purchase each type of ITN, and what proportion of the nets AMF buys will be the more expensive pyrethroid-chlorfenapyr nets ("chlorfenapyr nets") type. This grant won't directly improve our knowledge of net delivery costs, as AMF doesn't cover these. However, we'll update our assumptions on net costs and types post-distribution, and may fund additional research to clarify delivery expenses. (more)
  • What proportion of ITNs reach households and are not overallocated? We have relied on AMF's implementation partners to report on the number of ITNs distributed. There is a significant risk that some distribution staff could overreport the number of ITNs distributed and/or that households could overreport the number of people in their household in order to receive more ITNs than they need. It is a high priority for us to find ways to triangulate these results, but we do not have specific plans to do so yet. (more)
• For how much additional time will people be protected by ITNs than they would have been without this grant? We estimate that each net provides roughly 1.213 years of effective protection over the course of its lifespan in DRC. The key source of uncertainty in this estimate is how often ITN campaigns will occur with AMF’s support, and what would have happened otherwise. We think that ITN campaigns will occur every 33 months with AMF support. We think that the interval would have been 42 months without AMF support. These estimates, which require us to make guesses about what would happen in the future in different funding scenarios, are by necessity speculative. We will monitor whether 2024 ITN campaigns occur on schedule or are delayed. We will not be able to directly observe what would have happened without this grant. (more)

Basics

What is the problem and intervention?

Malaria is caused by parasites that are transmitted to people through the bites of infected mosquitoes.14 Malaria can result in life-threatening symptoms and poses a significant health risk to children under five years old and others with low immunity.15 The World Health Organization (WHO) recommends insecticide-treated nets (ITNs) as a main strategy for malaria vector control.16 ITNs are primarily distributed via mass distribution campaigns, in which nets are delivered door-to-door to households or through central distribution sites in a community. Based on current WHO guidance,17 most countries aim to deliver these campaigns every 36 months. For more information about malaria and ITN campaigns, see our intervention report.

In DRC, ITN campaigns occur at the province level on a rolling basis. DRC's Programme National de Lutte Contre le Paludisme (PNLP), or National Malaria Control Program, believes that ITNs should be delivered to each province every 30 months18 , even more frequently than the WHO-recommended 36-month interval. This is based on evidence that ITN durability is worse in DRC than in other locations.19

The Global Fund to Fight AIDS, Tuberculosis, and Malaria ("the Global Fund") and the President’s Malaria Initiative (PMI) have historically been the primary funders of ITN campaigns in DRC. The Global Fund provides funding in three-year grant cycles. The current Global Fund grant cycle runs from 2021-2023, and the next grant cycle will run from 2024-2026. In the past, the Global Fund and PMI have together lacked sufficient funding to deliver an ITN campaign to each of DRC’s provinces during a given grant cycle. This caused ITN campaigns to be delayed beyond the WHO-recommended 36-month interval (and the PNLP-targeted 30-month interval), as the country waited for more funding to become available in the subsequent Global Fund grant cycle.20 Because we estimate that ITNs distributed in DRC confer less than two years of effective protection on average,21 we believe that these delays result in more people using or discarding ineffective ITNs, which means they go without the protection from malaria provided by effective ITNs.

Planned activities and budget

AMF provides ITNs in bulk to other partners, including the Global Fund and PMI, or government agencies, which then distribute the nets in low- and middle-income countries with continued support from AMF on monitoring.22 AMF will use the majority of this grant to purchase ITNs that will be distributed in campaigns scheduled to occur in 2024 in DRC. The other major funders of ITNs in DRC—the Global Fund and PMI—will pay the costs of delivering ITNs to households, in part through reallocating funding that they would have spent on buying nets in the absence of this grant.23

AMF has been regularly supporting ITN campaigns in DRC since 2019,24 with ongoing support from GiveWell.25 For those past grants, we believed that the impact of the funding would be to reduce campaign delays and cause people to receive an ITN earlier than they otherwise would have, thereby increasing the number of people using nets that protect them from malaria.26 We believe that this grant will have a similar impact on ITN campaigns in DRC in 2024, in that AMF's funding will cause them to occur sooner than they otherwise would have.

To determine the size of this $17.5 million grant, we updated our room for more funding analysis for AMF.27 AMF expected there to be a $47.6 million funding gap28 for ITN campaigns in DRC in 2024. From this amount, we subtracted $15 million in previous GiveWell grants that AMF held but had not committed to specific campaigns.29 We then subtracted an additional $15 million of funding held by AMF that it had raised from revenue sources other than GiveWell grants, which AMF had agreed to allocate to DRC (beyond this $15 million, AMF holds an additional $24 million that it plans to allocate to other campaigns in other countries). This left a $17.5 million funding gap for campaigns in DRC in 2024.

The case for the grant

• Cost-effectiveness: We estimate that the cost-effectiveness of this grant is above our funding bar of 10 times as cost-effective as unconditional cash transfers, which we use as our benchmark for comparing the cost-effectiveness of different interventions. We estimate that this grant will be 15 times as cost-effective as unconditional cash transfers. (more).
• Funding landscape: There has historically been insufficient funding to support an ITN campaign in every province during a given three-year Global Fund grant cycle. We expect this situation to persist even beyond this grant to AMF. (more).
• Time-sensitivity: There is an immediate funding need to prevent ITN campaign delays in 2024. (more).
• Feedback from AMF's key partners in DRC: AMF works closely with DRC’s National Malaria Control Program (PNLP) and Global Fund’s DRC country team on ITN campaigns. We’ve heard positive feedback about AMF’s role in the process from both partners. (more)

Cost-effectiveness

We estimate this grant will avert the deaths of approximately 6,600 children under the age of five in 2024. We also think this grant will have a positive impact on children's future incomes by protecting them from illness at a crucial developmental stage.30 We estimate that this program is nearly 15 times as cost-effective as unconditional cash transfers to households living in some of the world's poorest communities,31 the benchmark we use to compare programs. As of 2023, we expect to direct funding to programs that are 10 or more times as cost-effective as cash transfers.

We discuss our model of the general cost-effectiveness of ITNs on this page and of AMF’s program on this page. In considering this grant, we made the following updates to that model for DRC:

• Cost per ITN estimate: Our estimate of the total cost of ITNs distributed by AMF is based on AMF’s ITN purchase costs, organizational and logistical costs associated with ITN campaigns that are borne by AMF and other organizations (non-net costs), and in-kind government costs.32 We updated our estimate of the cost per ITN distributed by AMF in DRC using information AMF shared about (a) the amount the Global Fund had budgeted to spend on non-net costs per ITN33 and (b) the proportions of different types of ITNs that AMF expected to purchase with this grant. Because AMF expects that around half of the ITNs it will procure will be chlorfenapyr ITNs—a new type of ITN that is more effective at preventing malaria but also more expensive34 —our estimate of the cost per ITN distributed by AMF in DRC increased from $5.51 to $5.85 per ITN.35 For more details about this update, see this cost-effectiveness model changelog.
• ITN efficacy reduction due to insecticide resistance: Our cost-effectiveness model includes an adjustment to account for reduced ITN efficacy due to insecticide resistance within mosquito populations.36 AMF expects that around half of the ITNs it will procure will be chlorfenapyr ITNs, which we expect to reduce the risk of net ineffectiveness due to insecticide resistance relative to standard ITNs.37 We updated our “efficacy reduction due to insecticide resistance” adjustment for DRC using an assumption that there is no insecticide resistance to chlorfenapyr in DRC, and therefore that these nets will maintain full efficacy. This update reduced the downward adjustment we use to account for insecticide resistance and therefore increased our cost-effectiveness estimate of ITN campaigns in DRC.38
• Adjustment for program impact being to move distributions closer together: Our cost-effectiveness analysis models the impact of ITN distributions taking place at 36-month intervals. This model implicitly assumes that, without funding from AMF, distributions would still happen on 36-month intervals but fewer ITNs would be distributed. However, in DRC, we think additional funding is more likely to reduce the amount of time between distributions.39 We also think that the cost per additional year of protection from moving distributions closer together is higher than the cost per additional year of protection from protecting people who would otherwise not receive a net at all. To account for this, we use an adjustment to reduce the overall number of years of coverage provided by nets in DRC (-30%),40 which decreases our estimate of the cost-effectiveness of this grant. For more details about this update, see this cost-effectiveness model changelog.
• Probability that other funders would fill these funding gaps if we did not: Part of our cost-effectiveness analysis involves asking what impact funding a program has on other actors’ spending. By funding ITNs, we may lead other organizations or governments to spend more (we refer to this as "leveraging" or “crowding in” funding) or less (we refer to this as "funging," from “fungibility,”or “crowding out”) on ITNs than they otherwise would. We include a “leverage and funging” adjustment in our cost-effectiveness analysis to account for this. We believe there is a 20% risk that this grant may crowd out funding from other sources, namely the Global Fund and PMI. This adjustment decreases our estimate of the cost-effectiveness of this grant. More details below.

At the time we made this grant, AMF had an estimated ~$39m of non-GiveWell revenue available to support net distributions. One reservation we had about making a grant to DRC was that it could have effectively displaced AMF revenue that would have gone to net distributions in DRC into distributions in other locations that GiveWell believed were probably less cost-effective than DRC on average. During our discussions with AMF about this grant opportunity on this issue, AMF agreed to allocate $15m of its non-GiveWell funding to DRC. We also estimated cost-effectiveness in the countries that we thought non-GiveWell funding might be allocated to (Chad, South Sudan, and Zambia) and conducted some internal (unpublished) sensitivity analyses suggesting that the grant would remain above our 10x cost-effectiveness bar under reasonably likely scenarios.

Funding landscape

In previous grant cycles, the Global Fund and PMI have together lacked sufficient funding to deliver an ITN campaign to each of DRC’s provinces during a given grant cycle. As discussed above, this has caused ITN campaigns in some provinces to be delayed into subsequent grant cycles until more funding is available to pay for them. Based on this track record, and the fact that the Global Fund's malaria grant to DRC for the next cycle is roughly equal in size to its current grant,41 we think it is very unlikely that these funders will provide enough funding to support ITN campaigns in each province during the 2024-26 cycle. This assumption has been corroborated by our review of the Global Fund's and PMI's forecasted spending on net campaigns in 2024-26 and our conversations with these and other program stakeholders.42

Our best guess is that there is a 20% risk that this grant may be crowding out funding that would otherwise have come from other sources, namely the Global Fund and PMI. PMI’s and the Global Fund’s ITN budgets for DRC in 2024-2026 suggest that both will shift funding away from ITN campaigns to routine net procurement relative to 2021-2023.43 We think it’s likely that these funding shifts were made in anticipation of AMF support for ITN campaigns in DRC in 2024-2026, and we view the increase in funding allocated to routine net procurement as money crowded out from the Global Fund and PMI by AMF’s spending on ITN campaigns in DRC. To reach this estimate, we calculated the annual amount of funding that we think PMI and the Global Fund have shifted from ITN campaigns to routine net procurement as a proportion of AMF’s proposed funding contribution in 2024.

Time-sensitivity

According to AMF, it can take over a year for ITNs to be ordered, manufactured, shipped to countries, and transported within countries. This is a time-sensitive grant that should allow AMF to order ITNs in time to avoid campaign delays in DRC in 2024.

Feedback from AMF's key partners in DRC

The Global Fund's DRC country team and DRC's PNLP have both indicated that AMF is an integral partner in DRC ITN campaigns. Our discussions with both suggest that AMF plays an important role in ensuring quality and accountability in distribution and reporting processes and that it may be able to procure ITNs at a lower cost per net than other organizations in DRC. We plan to continue developing our understanding of AMF's role through additional stakeholder conversations in the future.

Risks and reservations

How many deaths are caused by malaria in DRC?

We estimate that the annual malaria mortality rate among children who do not receive ITNs in DRC is 0.80%.This is based on:

• Estimates from the Institute for Health Metrics and Evaluation (IHME)'s 2019 Global Burden of Disease (GBD) model. Our estimates of annual malaria mortality for children under five are drawn from the IHME GBD project.44 For this grant, we used the 2019 GBD national-level estimate for malaria mortality among 1-59-month-olds in DRC. These estimates are a source of significant uncertainty in our analysis. Our understanding is that the GBD estimates rely on a number of modeling assumptions,45 in part because raw data on malaria from health surveillance systems is relatively unreliable in many low-income countries.46 We have not investigated all the modeling assumptions underlying these estimates in detail and we’re not sure how accurately GBD can attribute deaths to specific causes.
• Indirect malaria mortality: Malaria control interventions often have a larger effect on all-cause mortality than would be expected exclusively from declines in malaria-specific mortality.47 Deaths may have several causes, while only being attributed to one cause. For example, malaria may increase the likelihood of death from malnutrition or other infectious diseases.48 We account for this with an estimate that for each death directly caused by malaria, an additional 0.75 deaths are indirectly caused by malaria. We are highly uncertain about what the exact value for this effect should be. Our estimate is based on triangulating results from a meta-analysis of the effects of nets on all-cause mortality, conversations with malaria experts, and the effects that other health interventions have on averting indirect deaths.
• An adjustment for higher mortality among children who don’t use nets: The GBD malaria mortality estimates that we rely on in our cost-effectiveness analysis already incorporate the expected benefits of ITN distributions because some people in DRC are already protected by ITNs and therefore have lower mortality.49 Because we are interested in measuring the impact that increased access to nets has on malaria mortality for children not already protected by ITNs, we apply an adjustment to estimate the mortality risk for children who would not otherwise use nets. Our adjustment uses (i) GBD estimates of the proportion of children under five who slept under a net the previous night and (ii) the estimated protective effect of using a net in each country.50 This adjustment increases mortality risk in DRC from 0.53% for all children to 0.80% for those who don’t use nets.51 However, we have several reservations about this adjustment, including:
  • We have not carefully vetted the IHME usage estimates we use. We are uncertain about how representative the estimates are of net usage in each country, and we have not investigated the methodology used to estimate them.
  • The calculation we use does not take into account the community-level protective effect of using ITNs and only considers the benefit to the individual user.52
  • In effect, this adjustment is attempting to "undo" the incorporation of previous ITN distributions into the GBD 2019 estimates. It is possible that we have done so incorrectly.

How much do nets increase income later in life?

Our best guess is that averting childhood malaria cases leads to small income gains in adulthood, and we estimate that these benefits account for approximately 35% of the benefits of ITN distributions in DRC. To create our best guess on the effect of reductions in malaria on later-life income, we rely on evidence from two historical quasi-experiments, Bleakley 2010 and Cutler et al. 2010, that measure the effect of eradicating malaria on later-life income in the Americas and India. However, we have several uncertainties about this evidence, including:

• The increases in income these studies found may not necessarily be caused by decreases in malaria mortality. The studies also use imprecise historical data to measure past income and disease burden, and may be subject to publication bias.
• Both studies are based on early-to-mid 20th century malaria programs outside of Sub-Saharan Africa, and we are uncertain about how well the effects they estimate translate to today's contexts.
• We've only done a partial literature review for the long-term income effects from averting malaria, and it's possible that we'd update our effect size if we incorporated more evidence.

What is the total cost to procure and distribute an ITN in DRC?

We estimate that the total cost per ITN distributed in DRC will be $5.85, which is a higher total cost per ITN distributed estimate than all other countries in our model.53 This estimate relies on the following uncertain inputs:

• “Non-net costs” of distributed ITNs. For most ITN campaigns, AMF only pays for nets and monitoring activities; it partners with organizations—often the Global Fund—to pay for the other costs associated with ITN distributions (or “non-net" costs), including international shipping of ITNs, in-country transport, pre-distribution activities, and delivery to local communities.54 However, we have not seen data on the Global Fund's past net delivery expenditures in DRC. Our estimate of the cost per ITN distributed by AMF in DRC therefore relies on information AMF has shared about the amount the Global Fund has budgeted to spend on non-net costs per ITN during the 2024-26 grant cycle. Because this figure is a budgetary best guess, we are uncertain how accurate it is.
• The costs and proportion of each type of ITN that AMF will distribute. Different types of ITNs are priced differently. Our estimate of the cost per ITN distributed by AMF in DRC relies on AMF’s projections of the future prices of different types of ITNs and its projections of how many nets of various types it will buy (AMF expects that roughly half of the ITNs it plans to purchase for DRC will be chlorfenapyr nets,55 which it estimates are about 20% more expensive than other ITNs). These inputs reflect AMF's best guesses about the future and are inherently uncertain.

What proportion of ITNs reach households and are not overallocated?

A key input for our estimate of the total cost per distributed net is the total number of ITNs that AMF purchases that are ultimately distributed.56 The information that AMF provides to us about the number of ITNs distributed is recorded by AMF’s distribution partners (either national health agencies or in-country non-profit organizations) at the point of distribution.

We think there are two key ways that the distribution data we receive from AMF may be flawed or incomplete. AMF determines the number of ITNs to purchase based on population estimates,57 but ITNs are distributed only to registered households, which may only represent 70-80% of the total population.58 However, because of our limited investigation into AMF’s distribution process, we are unsure what happens to ITNs that were purchased for unregistered households. We think it’s possible that these ITNs are distributed instead to registered households, meaning those registered households would receive more ITNs than they need. We also think It’s plausible that distribution staff may be incentivized to overreport the number of ITNs distributed, meaning fewer ITNs are distributed than AMF’s distribution data suggests. This implies that we could be overestimating cost-effectiveness by as much as 20-30%, though this is likely an upper bound. Due to this uncertainty, we made a smaller grant with the intention of investigating this further in 2024 (see our current understanding of this issue on the page for the grant we made to AMF in DRC for 2025-26).

For how much additional time will people be protected by ITNs than they would have been without this grant?

In geographies where we think the impact of additional funding for ITN distributions is to reduce the amount of time between distributions (e.g., moving from a four-year spacing to the recommended three-year spacing) rather than increasing coverage for campaigns that occur every three years, we include an "adjustment for program impact being to move distributions closer together,” described above. This adjustment uses our best guesses about how often ITN campaigns will occur with AMF’s support, and what would have happened otherwise. We think that ITN campaigns will occur every 33 months with AMF support, and that the interval would have been 42 months without AMF support.59 These estimates are based on our understanding of the funding landscape for ITN campaigns in DRC, AMF’s expectations about the impact of its funding, and the historical timing of the country's past campaigns. However, because they are predicated on guesses about what would happen in the future in different funding scenarios, they are by necessity speculative.

Plans for follow up

• We have monthly calls with AMF to discuss its work.
• We will review the information AMF collects during campaigns on how many nets were distributed and, after campaigns, on how many nets are present and in use in registered households.
• We will request information on whether ITN campaigns occur on schedule or are delayed.
• We will follow AMF's decision-making about how it uses its revenue from sources other than GiveWell grants, and we may estimate the cost-effectiveness of each of the funding gaps it chooses to fill with this revenue.

Our process

We anticipated a funding gap in DRC based on previous work we’ve done to support AMF in filling this gap. Our grant investigation relied heavily on our prior work modeling the cost-effectiveness of ITN campaigns supported by AMF and our relationship with AMF and knowledge of its work. To generate a grant-specific cost-effectiveness estimate, we used our existing cost-effectiveness model for ITN campaigns and updated various parameters to match the specifics of this funding gap. We also had conversations with the Global Fund's DRC country team and with the head of DRC's national malaria control program (PNLP).

For internal review, a Senior Researcher and a Senior Program Associate who were not otherwise involved in the grant investigation gave feedback on the plan for investigating the grant.

Sources

Document	Source
AMF - Net distributions - Congo (Dem. Rep.)	Source (archive)
Bhatt et al. 2015	Source
Bleakley 2010	Source
Cutler et al. 2010	Source
De Beyl 2016	Source
GiveWell, 2023 AMF DRC grant cost-effectiveness analysis	Source
GiveWell, 2023 Cost-Effectiveness Analysis Changelog	Source (archive)
GiveWell, Against Malaria Foundation	Source (archive)
GiveWell, Against Malaria Foundation - Support for ITN Campaigns in DRC, 2025-26	Source
GiveWell, Against Malaria Foundation – Support for LLIN Campaigns in Nigeria (2022), Uganda (2023), and Togo (2023)	Source (archive)
GiveWell, Against Malaria Foundation — Support for LLIN Campaign in South Sudan	Source (archive)
GiveWell, CEA of insecticide-treated net (ITN) distributions	Source
GiveWell, CEA of insecticide-treated net (ITN) distributions – version 24.2 (grant for DRC 2025-26)	Source
GiveWell, Conversation notes with Christian Lengeler	Source
GiveWell, DRC nets durability	Source
GiveWell, GiveWell's 2020 moral weights	Source
GiveWell, GiveWell's Cost-Effectiveness Analyses	Source (archive)
GiveWell, Grants and Funding Recommendations in January and February 2021	Source (archive)
GiveWell, Insecticide resistance adjustment [March 2023]	Source
GiveWell, Insecticide Resistance and Malaria Control	Source (archive)
GiveWell, Mass Distribution of Insecticide-Treated Nets (ITNs)	Source (archive)
GiveWell, Our Top Charities	Source (archive)
GiveWell, Summary of AMF distributions [through 2021]	Source
GiveWell, Updated Nets Baseline 1-59 Month Mortality [outdated as of Dec 2023]	Source
GiveWell, Weighted average cost-effectiveness estimates for Jan/Feb 2021 funding allocations	Source
Institute for Health Metrics and Evaluation, Global Burden of Disease Project	Source (archive)
Jamison et al. 2006	Source (archive)
Mosha et al. 2022	Source
Nkengasong et al 2020	Source
PMI, Durability Monitoring of LLINs in Democratic Republic of Congo, Final report After 36 months follow-up	Source
U.S. PRESIDENT’S MALARIA INITIATIVE Democratic Republic of the Congo Malaria Operational Plan FY 2024	Source
World Health Organization, Country Disease Outlook, Democratic Republic of the Congo - 2023	Source
World Health Organization, Guidelines for Malaria Vector Control, 2019	Source
World Health Organization, Malaria Factsheet, December 8th 2022	Source (archive)

• 1

  $16.8 million of this grant was funded by donations to GiveWell's Top Charities Fund. The remaining $750,000 was funded by donations to our All Grants Fund.

• 2

  “The DRC was second only to Nigeria in the number of malaria cases reported in 2021 (> 30.5 million) in the African region comprising of 12.3% of the total global malaria cases. The 78,847 number of reported deaths also represent a similar proportion of global deaths attributed to malaria. DRC is one of the 10 High Burden High Impact countries in the Africa region” Country Disease Outlook, Democratic Republic of the Congo - WHO 2023

• 3

  Source. Note that AMF provided irregular support prior to 2019.

• 4

  See our list of previous grants to AMF here.

• 5

  $34.7 million (the total amount spent by all contributors) / $28

• 6

  For ease of modeling, we quantify our uncertainty ranges for benefits other than mortalities averted among people under age 5 as percentage adjustments applied to other modeled benefits of the program. For DRC, our 25th to 75th percentile range for mortalities averted among people over age 5 spans from a +10% adjustment to a +25% adjustment to under-5 mortality benefits, which roughly translates to between 6% and 13% of the total benefits of the program, as shown in the table above. This conversion is imperfect because varying the proportion of the program's total impact that is contributed by one type of benefit will also affect the proportion of impact contributed by other types of benefits, but we think the values presented in the table are a reasonably good approximation of our uncertainty level for this parameter.

• 7

  For ease of modeling, we quantify our uncertainty ranges for benefits other than mortalities averted among people under age 5 as percentage adjustments applied to other modeled benefits of the program. For DRC, our 25th to 75th percentile range for increases in adult income spans from a +47% adjustment to a +114% adjustment to total mortality benefits, which roughly translates to between 32% and 53% of the total benefits of the program, as shown in the table above. This conversion is imperfect because varying the proportion of the program's total impact that is contributed by one type of benefit will also affect the proportion of impact contributed by other types of benefits, but we think the values presented in the table are a reasonably good approximation of our uncertainty level for this parameter.

• 8

  Our 25th - 75th percentile confidence interval for child mortality is 0.46% – 1.13%, which implies that net distributions are 11x - 18x as cost-effective as direct cash transfers.

• 9

  “The scarcity of current, complete, and accurate primary data on causes of death in most of sub-Saharan Africa restricts the ability of countries to measure progress against many of the Sustainable Development Goal targets, measure the impact of programmatic interventions, prioritise and plan to address their health needs, and achieve the goals of the Africa Agenda 2063….The 2016 Global Burden of Disease study found that 38 of 55 countries in Africa did not produce any reliable data on cause of death from 2010 to 2016.” Nkengasong et al 2020

• 10

  Our 25th - 75th confidence interval is that this accounts for 32%-53% of program benefits, which implies that net distributions are 14x-21x as cost effective as direct cash transfers.

• 11

  Our 25th - 75th percentile confidence interval for cost per child under age five reached is $21 - $36, which implies that net distributions are 13x - 18x as cost-effective as direct cash transfers.

• 12

  Our 25th - 75th percentile confidence interval for this estimate is $4.82-$6.63.

• 13

  Our 25th - 75th percentile confidence interval for years of effective coverage is 0.9 – 1.6 years, which implies that net distributions are 13x – 18x as cost-effective as direct cash transfers.

• 14

  World Health Organization, Malaria Factsheet, December 8th 2022. Available here.

• 15

  World Health Organization, Malaria Factsheet, December 8th 2022. Available here.

• 16

  “Core interventions for malaria vector control are applicable for all populations at risk of malaria in most epidemiological and ecological settings, namely: i) deployment of insecticide-treated nets (ITNs) that are prequalified by WHO, which in many settings are long-lasting insecticidal nets (LLINs); and ii) indoor residual spraying (IRS) with a product prequalified by WHO. Once high coverage with one core intervention has been achieved, supplementary interventions – namely the deployment of chemical or biological larvicides – can be used in addition to the core interventions in specific settings and circumstances.” World Health Organization, Guidelines for Malaria Vector Control, 2019, xiv.

• 17

  “Campaigns should also normally be repeated every three years, unless available empirical evidence justifies the use of a longer or shorter interval between campaigns.” World Health Organization, Guidelines for Malaria Vector Control, 2019, pp. 39-40

• 18

  “In previous years, and in partnership with the Global Fund, PMI supported mass distribution of ITNs every three years. This distribution cycle has been revised to 30 months based on PMI-supported durability studies.” U.S. PRESIDENT’S MALARIA INITIATIVE Democratic Republic of the Congo Malaria Operational Plan FY 2024

• 19

  In our cost-effectiveness model, we assume that net durability in DRC is 17% lower than in other locations. This adjustment is based on data we have seen from Against Malaria Foundation’s post-distribution monitoring surveys, which track usage and condition over time. We also incorporate data from a durability study conducted by PMI in DRC, which finds worse durability in DRC compared to our analysis of durability in other locations. (PMI, Durability Monitoring of LLINs in Democratic Republic of Congo, Final report After 36 months follow-up, July 2019. Our analysis of the PMI data is available in this sheet.)
  This adjustment reduces our estimate of equivalent coverage-years for an ITN distribution from 2.11 in other locations to 1.75 in DRC. See this spreadsheet for our calculations.

• 20

  For example, the average interval between campaigns in the 2015-2017 grant cycle and those in the 2018-2020 grant cycle was 45 months. See this cell.

• 21

  In our cost-effectiveness model, we assume that net durability in DRC is 17% lower than in other locations. This adjustment is based on data we have seen from Against Malaria Foundation’s post-distribution monitoring surveys, which track usage and condition over time. We also incorporate data from a durability study conducted by PMI in DRC, which finds worse durability in DRC compared to our analysis of durability in other locations. (PMI, Durability Monitoring of LLINs in Democratic Republic of Congo, Final report After 36 months follow-up, July 2019)
  This adjustment reduces our estimate of equivalent coverage-years for an ITN distribution from 2.11 in other locations to 1.75 in DRC. See this spreadsheet for our calculations.

• 22

  For more on AMF's role in ITN distributions, see here.

• 23

  This does not involve AMF leveraging new funding from the Global Fund or PMI for ITNs. A stylized example of how this works:

  • An ITN distribution campaign costs $15 million: $7.5 million to buy ITNs and $7.5m to deliver them.
  • The Global Fund pledges $10 million to the campaign. About $5 million of this will be spent to buy ITNs and $5 million to deliver ITNs.
  • AMF pledges $5 million to fill the remaining gap in funding, but will only contribute by buying ITNs.
  • The Global Fund alters its funding so that it spends $2.5 million to buy ITNs and $7.5 million to deliver them (still $10 million total).
  • This results in $7.5 million to buy ITNs and $7.5m to deliver them.

• 24

  Against Malaria Foundation, “Net distributions - Congo (Dem. Rep.)” Note: AMF provided support to distributions prior to 2019 but this support was somewhat irregular.

• 25

  For example, in 2021, we made a $27.4 million grant to AMF to fill the remainder of its funding gap for DRC in 2022 and partially fund its work in DRC in 2023. See here for more discussion of that grant.

• 26

  In 2021, we directed $27.4 million to AMF to fill the remainder of its funding gap for DRC in 2022 and to partially fund its work in DRC in 2023. We estimated the cost-effectiveness of this grant to be 12x cash overall; see here for more discussion of this grant.

• 27

  We conduct a "room for more funding" analysis as part of each grant investigation to understand what portion of a grantee's ideal future budget it will be unable to support with the funding it has or should expect to have available. We may then choose to either make or recommend grants to support those unfunded activities. For more about how we typically analyze room for more funding, see here.

• 28

  This was relayed to GiveWell staff by AMF.

• 29

  In 2021, we made a $7 million grant to AMF to support 2022 ITN campaigns in Global Fund-supported states in Nigeria. AMF did not end up committing funds to these campaigns (confirmed by AMF in a draft of this page). In 2022, we made an $8 million grant to AMF to support 2023 ITN campaigns in South Sudan. However, we requested that AMF hold this grant for an alternative opportunity after we learned new information that caused us to negatively update our cost-effectiveness estimate. More information about each grant can be found here and here.

• 30
  • “Relative to non-malarious areas, cohorts born after eradication [in malarious areas] had higher income as adults than the preceding generation. These cross-cohort changes coincided with childhood exposure to the campaigns rather than to pre-existing trends. Estimates suggest a substantial, though not predominant, role for malaria in explaining cross-region differences in income.” Bleakley 2010, abstract.
  • See our estimate of development effects in this section of our cost-effectiveness analysis here.

• 31

  Note that a) our cost-effectiveness analyses are simplified models that are highly uncertain, and b) our cost-effectiveness threshold for directing funding to particular programs changes periodically. See GiveWell’s Cost-Effectiveness Analyses webpage for more information about how we use cost-effectiveness estimates in our grantmaking.

• 32

  For more information about how we calculate cost per net, see here.

• 33

  The Global Fund’s non-net costs are only available to GiveWell staff because we do not have permission to report costs covered by the Global Fund.

• 34
  • Current evidence suggests that chlorfenapyr nets may be much more effective at preventing malaria than standard ITNs and ITNs treated with the synergist piperonyl butoxide (PBO) in areas where a large proportion of mosquitoes are resistant to commonly used insecticides. AMF has shared with us that it plans to purchase ~45% Dual-AI chlorfenapyr nets for ITN campaigns in the DRC, which cost more than standard ITNs or ITNs with the additive piperonyl butoxide (PBO nets). See here for our discussion of the effectiveness of ITNs for protection against malaria.
  • “Malaria infection prevalence at 24 months was 549 (45·8%) of 1199 children in the pyrethroid-only reference group, 472 (37·5%) of 1258 in the pyriproxyfen group (adjusted odds ratio 0·79 [95% CI 0·54-1·17], p=0·2354), 512 (40·7%) of 1259 in the piperonyl butoxide group (0·99 [0·67-1·45], p=0·9607), and 326 [25·6%] of 1272 in the chlorfenapyr group (0·45 [0·30-0·67], p=0·0001)...After 2 years, chlorfenapyr LLINs provided significantly better protection than pyrethroid-only LLINs against malaria in an area with pyrethroid-resistant mosquitoes.” Mosha et al. 2022, pp. 1-2.

• 35

  See our new cost per net estimates here, and our previous estimates here.

• 36

  See our report on this topic for more details.

• 37

  See GiveWell's analysis of the efficacy reduction due to insecticide resistance here.

• 38

  See the impact this change had on our cost-effectiveness estimates for AMF’s program in DRC here.

• 39

  This is based on an unpublished GiveWell analysis of different spacing and funding scenarios.

• 40

  We calculate this adjustment using the following method:

  • First, we estimate the average number of years of effective coverage provided by nets at different possible intervals (up to six years).
    • We use 0.98 effective years of coverage in year one, 0.77 years in year two, and 0.52 years in year three. We have not reviewed data from field monitoring on net durability over years 4-6, so we extrapolate based on the data we have reviewed in years 1-3 and some rough guesses (see this cell note for more information).
    • We apply adjustments of -7% to account for reduced coverage from generic ITNs and for lower durability in DRC.
    • Overall, we estimate that the number of years of effective coverage per net falls from 0.81 in year one to 0.00 in year six after a distribution in DRC.
    • We also estimate the level of effective coverage remaining at each month post-distribution by extrapolating from our estimates above and assuming linear decay over each successive month. For example, this method suggests that nets distributed at 36-month intervals in DRC provide an average of 0.58 years of effective coverage per year over the course of their 3-year lifespan.
  • We roughly estimate that the impact of AMF’s funding will be to shorten the average interval between campaigns from 42 months to 33 months in the provinces it supports.
  • We use the estimates above to calculate the cost per year of effective coverage provided for campaigns at 36-month intervals (which our main cost-effectiveness analysis is modeling) and compare it to the cost per year of effective coverage from shortening the interval between campaigns. This calculation implies that the cost per year of effective coverage from shortening the interval between campaigns is 29% lower in DRC.
  • Intuitively, the reason this is a significant downward adjustment is that we think nets still provide some protection on average after three years. This means that shortening the interval between campaigns (and causing people to receive a new net earlier than they would have otherwise) is not as cost-effective as increasing the proportion of people who receive a net in a given campaign.

• 41

  The Global Fund’s 2021-2023 and 2024-2026 ITN budgets have been provided to us by AMF. We do not have permission to publish this information.

• 42

  The Global Fund’s and PMI’s ITN budgets have been provided to us by AMF. We do not have permission to publish this information.

• 43

  The Global Fund’s and PMI’s ITN budgets have been provided to us by AMF. We do not have permission to publish this information.

• 44

  See our summary of this data here.

• 45

  This understanding is based on multiple conversations with IHME researchers. Detailed modeling assumptions for the GBD estimates are available in the GBD 2019 methods appendix.

• 46

  "Despite its importance, current knowledge on the nature and drivers of changing endemicity in sub-Saharan Africa is remarkably weak. National health records in 32 highly endemic countries (together accounting for about 90% of the global malaria burden) are considered inadequate to assess trends in malaria cases. This stems from low care-seeking rates (many malaria cases are not seen at formal health facilities), incomplete record keeping and curation (many recorded cases are never captured in surveillance databases), and historically poor access to parasitological diagnosis (malaria cases were often diagnosed presumptively with poor specificity).” Bhatt et al. 2015, p. 2.

• 47

  From Jamison et al. 2006:

  • "During randomized controlled intervention trials aimed at reducing the incidence of infection (but not 100 percent protective), the all-cause mortality of children is often reduced more than would be attributed by VA diagnosis of malaria. For example, in Kilifi the proportion of deaths of children under five years attributed to malaria by VA was 34 percent (R. W. Snow, unpublished data). During a randomized controlled trial of insecticide-treated bednets in the same area, the incidence of malaria infection was reduced by 50 percent (Snow et al. 1996), which was sufficient to reduce all-cause mortality by 33 percent (Nevill et al. 1996). More dramatically, in The Gambia, insecticide-treated bednets reduced all-cause mortality by over 60 percent, and yet the VA-diagnosed contribution of malaria to all-cause mortality among control populations was only 16 percent (Alonso et al. 1993). This has led some to speculate that malaria infection is a contributor to broad causes of mortality beyond the direct fatal consequences of infection (Molineaux 1997)." Jamison et al. 2006, p. 204.
  • "Data on all-cause mortality of children under five from DSS studies undertaken across a broad range of malaria transmission settings in Sub-Saharan Africa were analyzed against the prevalence of P. falciparum infection at each site. Weighted least-squares regression was used to model the contiguous relationships between all-cause mortality and parasite prevalence rates, allowing for the square of parasite prevalence (for possible saturation of parasite prevalence), timing, location, and the sampling precision of each study (Snow, Korenromp, and Gouws 2004). The unadjusted median all-cause child mortality rate for low prevalence areas of childhood infection (less than 25 percent) was 10.9 per year per 1,000 children under five (IQR 7.8–17.6). This rose dramatically to 39.1 per year per 1,000 children (IQR 32.8–52.2) among populations exposed to childhood parasite prevalence risks greater than or equal to 25 percent. In the regression model, mortality increased significantly with parasite prevalence, but this effect leveled off at higher prevalence rates. The model suggested that, in rural DSS sites throughout Sub-Saharan Africa, all-cause mortality increases by more than twofold (25–30 deaths per 1,000 children under five years old) over the prevalences of malaria infection covered by the DSS sites, and parasite prevalence explained 64 percent of the variation between sites in all-cause under-five mortality. By contrast, the direct estimation of malaria-specific mortality presented earlier for children living under stable endemic conditions was only 28.2 percent." Jamison et al. 2006, p. 206.

• 48

  “Indirect consequences of P. falciparum infection include anemia (unless anemia is linked to acute high-density parasitemia as a direct cause), low birthweight, growth retardation, or undernutrition. In addition, malaria infection can increase the severity of other comorbid infectious diseases through immune suppression or enhanced invasive capacities across physical barriers to infection (for example, blood and tissue). Previous approaches to the global burden of disease have assumed that each death must be attributed to a single cause and can be fitted into the fixed disease-mix matrix of all causes (Murray and Lopez 1997).” Jamison et al. 2006, p. 206

• 49

  IHME, email to GiveWell, July 21, 2021 (unpublished).

• 50

  See this row for the estimated % of children sleeping under ITNs and this row for the estimated reduction in malaria mortality in our cost-effectiveness analysis.

• 51

  This calculation uses the following formula:

  • Mortality overall = (Mortality among those not using nets x % not using nets) + (Mortality among those using nets x % using nets). This is equal to:
  • (Mortality among those not using nets x % not using nets) + (Mortality among those not using nets x relative risk of mortality from using nets x % using nets). This implies:
  • Mortality among those not using nets = Mortality overall / (relative risk of mortality from using nets x % using nets + % not using nets).

  See these rows in our cost-effectiveness analysis.

• 52
  • People who do not use nets may nonetheless gain some protection from others in the community using them, because the overall number of mosquitoes and level of malaria in the community is lower. We have previously heard from malaria researchers that community effects are likely to be some portion of the protection provided by nets, but that the level of protection provided by these effects has not been well quantified.
  • "When you're moving from protecting only children to protecting everybody, you multiply your costs by a factor of five, but you also get at least twice as much effect and we know that from both modeling and empirical impact assessments … I don't think we will ever really have the reply to that question [about the relative magnitude of community-level effects]." Christian Lengeler, author of Cochrane Review of insecticide-treated bed nets, phone conversation with GiveWell, November 2, 2011. See our call notes here.

• 53

  See this row of the CEA. While we think this estimate for DRC may be somewhat imprecise, we think “non-net costs” will be higher there due to poor road infrastructure and other factors that make it a relatively challenging operating environment.

• 54

  See this spreadsheet, “Detailed Overview” sheet, for details on what costs AMF has paid for past distributions.

• 55

  This is based on the DRC estimated distribution schedule provided to GiveWell by AMF (unpublished)

• 56

  We calculate the total cost per net distributed as the sum of AMF’s average net purchase costs and non-net costs, The Global Fund’s non-net costs, and in-kind government costs per net. We calculate AMF’s average cost per net distributed by subtracting the proportion of purchased nets that go undelivered from the average cost per ITN purchased. We do not have AMF’s permission to publish these calculations.

• 57

  This understanding is informed by having conversations with and reviewing information shared by AMF over our years of collaboration.

• 58
  • The ITN registration process, during which national health system staff or volunteers travel door-to-door to determine the number of nets required for each household, is summarized in our Against Malaria Foundation review.
  • De Beyl 2016 examines results from 14 post-campaign surveys in five African countries to assess whether the campaign strategy used had any effect on distribution outcome. It finds that the average household registration rate in these campaigns was between 70% and 80%. See: De Beyl 2016, Figure 1.

• 59
  • We assume that the average interval between campaigns in each province will be 33 months with AMF funding. This is based on the PNLP’s goal of conducting campaigns at 30 month intervals. Our best guess that this target will be slightly missed.
  • We assume that the average interval between campaigns in the absence of AMF funding will be 42 months, based on our unpublished analysis that suggests that AMF’s funding in 2021-23 brought forward campaigns by an average of 9 months when compared to previously projected start dates.