Against Malaria Foundation — PMI-supported states in Nigeria, 2023 (January 2022)

Note: This page summarizes the rationale behind a GiveWell-recommended grant to the Against Malaria Foundation (AMF). AMF staff reviewed this page prior to publication.

Summary

In January 2022, GiveWell recommended an $8.2 million grant to the Against Malaria Foundation (AMF). $4.8 million of this grant was given by Effective Altruism Funds on GiveWell's recommendation, and the remaining $3.3 million was given by donors to GiveWell’s Maximum Impact Fund in the fourth quarter of 2021. This amount will enable AMF to purchase long-lasting insecticide-treated nets (LLINs) for campaigns that are scheduled to occur in 2023 in three Nigerian states, all of which primarily receive funding for malaria programs from the President's Malaria Initiative (PMI). We expect that if we did not make this grant, the campaigns in these states would be delayed, and therefore that the impact of this grant will be to cause people to receive an LLIN earlier than they otherwise would have.

We made this grant because we believe it will be highly cost-effective. After investigating the funding landscape for LLINs in Nigeria, we believe that we are at relatively low risk of crowding out other funders, primarily PMI. We also believe that this grant will fill a time-sensitive funding need.

Published: April 2022

Table of Contents

Planned activities and budget

This $8.2 million grant will enable AMF to purchase LLINs for campaigns that are scheduled to occur in 2023 in three Nigerian states: Benue, Plateau, and Zamfara.1 We expect AMF to use most of this grant to purchase the LLINs required for these campaigns2 and, consequently, for PMI to purchase fewer LLINs and instead spend that funding on delivering the LLINs that AMF purchases.3 A smaller portion of the funding will be used to collect post-distribution monitoring data.4

In Nigeria, most states are assigned to receive funding for malaria programs either from the Global Fund to Fight AIDS, Tuberculosis and Malaria ("the Global Fund"), from PMI, or through a loan from the World Bank and the Islamic Development Bank.5 The three states that we expect AMF to support with this grant are primarily supported by PMI.6 GiveWell made a previous grant to AMF to support campaigns in two other states that are supported by PMI, Akwa Ibom and Bauchi. We have heard from multiple sources that PMI has insufficient funding to support an LLIN campaign in each of its 11 supported states every three years.7 Consequently, prior to AMF's involvement, campaigns were occurring in these states every four or five years.8 We expect that the counterfactual to this grant is that campaigns in these 11 states will continue to be delayed,9 and therefore that the impact of this grant will be to cause people in all 11 states to receive an LLIN earlier than they otherwise would have. See here for a full discussion of how this counterfactual compares to the typical counterfactual we assume for LLIN grants.

We conduct "room for more funding" analysis 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. To determine the size of this grant, we updated our room for more funding analysis for AMF. In this section of our review of AMF's work, we describe how we typically analyze AMF's room for more funding; for this analysis, we deviated from our standard process in two ways:

  • In our room for more funding analyses, we typically include reserved funding as funding available to support program activities.10 In this analysis, we chose to exclude the roughly $6 million that AMF currently holds in reserves from our estimate of available funding. Our reason for doing so was that in the agreements AMF signs with national malaria programs, it commits to purchasing a certain number of nets, rather than allocating a certain amount of funding. This means that any fluctuations in net price will affect the total amount of funding it ultimately must allocate to a campaign. It therefore seems reasonable to hold some funding in reserve in order to respond to any increases in net price, especially given the substantial number of nets AMF is currently committed to purchase.11 We believe that this approach is consistent with the three-year funding runway we typically provide to other grantees, which enables them to use funding budgeted for future years to pay for any cost increases in an earlier year.
  • In our room for more funding analyses, we typically project the amount of additional funding that grantees will receive over the next three years and then add this projected funding to the amount available to allocate to grantee's unfunded spending opportunities. In this analysis, we did not include any projected revenue in our estimate of the funding AMF will have available to support its work, because both we and AMF believe that AMF should commit funding for these campaigns as soon as possible (more below). (This means that one effect of the funding we have granted to AMF is to free up AMF's future revenue for support to other campaigns. See further discussion below.)

Case for the grant

  • Cost-effectiveness. During this grant investigation, we used our existing cost-effectiveness model for LLIN campaigns and updated various parameters to match the specifics of this funding gap. We estimate that this grant is 12 times as cost-effective as GiveDirectly's program, which provides unconditional cash transfers to poor households in low-income countries. (More below)
  • Funding landscape for LLINs. We investigated the funding landscape for LLINs in Nigeria and believe that this funding gap is unlikely to be fully filled by other funders. We adjust our cost-effectiveness estimate to account for the extent to which we believe our funding may be crowding out funding that would otherwise have come from other sources. (More below)
  • Time-sensitivity. We believe that this grant will fill a time-sensitive funding need. (More below)

Cost-effectiveness

How we use cost-effectiveness estimates in our grantmaking

After assessing a potential grantee's room for more funding, we may then choose to investigate potential grants to support the spending opportunities that we do not expect to be funded with the grantee's available and expected funding, which we refer to as "funding gaps." The principles we follow in deciding whether or not to fill a funding gap are described on this page.

The first of those principles is to put significant weight on our cost-effectiveness estimates. We use GiveDirectly's unconditional cash transfers as a benchmark for comparing the cost-effectiveness of different funding gaps, which we describe in multiples of "cash." Thus, if we estimate that a funding gap is "10x cash," this means we estimate it to be ten times as cost-effective as unconditional cash transfers. As of this writing, we have typically funded opportunities that meet or exceed a relatively high bar: 8x cash, or eight (or more) times as cost-effective as GiveDirectly's unconditional cash transfers. We also consider funding opportunities that are between 5 and 8x cash.

Note that our cost-effectiveness analyses are simplified models that do not take into account a number of factors. There are limitations to this kind of cost-effectiveness analysis, and we believe that cost-effectiveness estimates such as these should not be taken literally due to the significant uncertainty around them. We provide these estimates (a) for comparative purposes to other grants we have made or considered making, and (b) because working on them helps us ensure that we are thinking through as many of the relevant issues as possible. Our process for estimating cost-effectiveness focuses on determining whether a program is cost-effective enough that it is above our bar to consider funding; it isn't primarily intended to differentiate between values that are above that threshold.

Cost-effectiveness of this grant

We estimate that the cost-effectiveness of this grant is 12x cash.12 To generate this estimate, we used our existing cost-effectiveness model for LLIN campaigns and updated various parameters to match the specifics of this funding gap.

When we made our previous grant to AMF to support campaigns in Akwa Ibom and Bauchi, we estimated that the cost-effectiveness of that grant was 15x cash.13 Since then, we have updated several parameters in our cost-effectiveness model. The key parameter updates we made included:

  • Efficacy reduction due to insecticide resistance.14 Our cost-effectiveness model for LLINs includes an adjustment to account for the efficacy lost due to resistance within mosquito populations to the insecticides used in LLINs (see our separate report on this topic for more details). We updated this adjustment to (a) incorporate more recent insecticide resistance data and (b) incorporate evidence on the efficacy of LLINs that have been treated with piperonyl butoxide (PBO) in addition to standard insecticide. See full details in changes 3 and 18 of our cost-effectiveness model changelog (Version 1).
  • Malaria-attributable deaths averted per 1,000 children per year targeted with seasonal malaria chemoprevention.15 We added an adjustment to account for deaths averted by seasonal malaria chemoprevention (SMC) in areas reached by both SMC and LLIN campaigns, which reduced our estimate of the deaths averted by LLINs. We believe this adjustment is needed, because we are using estimates of deaths as of 2019, and SMC has been scaled up in some of the states where AMF-funded nets will be used since 2019. See full details in change 15 in our cost-effectiveness model changelog (Version 1).
  • Malaria burden (multiple parameters). The impact of LLINs is moderated by rates of malaria incidence and mortality where they are distributed; we expect campaigns that target populations affected by higher malaria rates to have higher impact. We use data on malaria incidence and mortality in the locations where AMF works in our cost-effectiveness model to estimate the impact of LLINs on malaria rates in these locations. Previously, our cost-effectiveness model for LLINs in PMI-supported states in Nigeria used national-level malaria data. During this grant investigation, we updated the model to use state-level malaria data from the 11 PMI-supported states: Benue, Nasarawa, Plateau, Bauchi, Kebbi, Sokoto, Zamfara, Ebonyi, Akwa Ibom, Cross River, and Oyo.16 (We use data from all 11 PMI-supported states—rather than just Benue, Plateau, and Zamfara—because we believe that the impact of this grant will be to cause people in all 11 states to receive an LLIN earlier than they otherwise would have.) Because malaria burden is higher in these states than the national average, this change caused our cost-effectiveness estimate to increase slightly.17
  • Cost per LLIN. We reviewed recent information provided by AMF about its net purchase prices by country. This work did not lead to changes in our estimate of the cost per LLIN in Nigeria.
  • Adjustment for program impact being to move distributions closer together.18 We expect that the counterfactual to this grant is that campaigns in these 11 states would be delayed,19 and therefore that the impact of this grant will be to cause people to receive an LLIN earlier than they otherwise would have. This counterfactual differs from the typical counterfactual we assume for LLIN grants, which is that AMF will cause more people to receive an LLIN than otherwise would have. We have therefore chosen to retain the 35% downward adjustment, created for our prior grant to AMF for PMI-supported states, that captures this difference. We discuss the context behind this understanding and how we model the cost-effectiveness of reducing the time interval between distributions in this grant page and in our cost-effectiveness model changelog.
  • Likelihood that the Global Fund and/or PMI would replace Malaria Consortium's costs.20 See details below.

Funding landscape for LLINs

Prior to this grant investigation, we used a value of 20% for the proportion of AMF's funding that we believed may crowd out funding from PMI in Nigeria. This spreadsheet explains our reasoning for that value.

In Nigeria, most states are assigned to receive funding for malaria programs either from the Global Fund, from PMI, or through a loan from the World Bank and the Islamic Development Bank.21 The three states that we expect AMF to support with this grant are primarily supported by PMI.

We think it is unlikely that another funder will fill the gap for these campaigns. We have heard from multiple sources that PMI has insufficient funding to support an LLIN campaign in each of its 11 supported states every three years.22 Consequently, prior to AMF's involvement, campaigns were occurring in these states every four or five years.23 From our understanding, this is despite the fact that LLIN campaigns are a top priority for PMI in Nigeria. We aren't aware of a reason to expect PMI's funding for Nigeria to increase in the short term—in fact, PMI's budget for Nigeria decreased from $77 million24 in 2020 to $69 million25 in 2021 and $68 million26 in 2022.

We do not believe that this gap will be filled by either of the other major funding sources for LLINs in Nigeria: we are aware that the Global Fund has insufficient funding for LLIN campaigns in the states it supports (GiveWell made a separate grant to AMF to contribute LLIN funding to states that are supported by the Global Fund), and the World Bank and Islamic Development Bank loan funding is restricted to other states.

We have chosen to retain the value of 20% for the proportion of AMF's funding that we believe may crowd out funding from PMI in Nigeria. We have increased our confidence in this figure by reviewing information provided by AMF27 showing that in 2021-23, AMF will contribute $39.2 million28 to LLIN campaigns in PMI-supported states in Nigeria and that PMI will consequently spend $7.9 million29 —20% of $39.2 million—less on LLINs than it would have without AMF's contributions. We therefore believe that in this period, 20% of AMF's funding will crowd out funding that would have otherwise come from PMI.

Time-sensitivity

Making this grant when we did should enable AMF to order LLINs in time to avoid delaying campaigns. According to AMF, it can take over a year for LLINs to be ordered, manufactured, shipped to countries, and transported within countries. This means that AMF needs to commit funding to a campaign well in advance of when it is scheduled to occur. Recently, we have heard from multiple sources that LLIN manufacturing and shipping is experiencing longer-than-usual delays, which means that LLINs should ideally be ordered even further in advance of campaigns than they typically would.

​​Risks and reservations

  • Risk of future crowding out. It is possible that by filling this funding gap, we are setting the expectation that GiveWell funding will be available to fill future gaps for LLIN campaigns in Nigeria. This may lead the National Malaria Elimination Programme (NMEP) and other funders to reduce the funding they direct to those campaigns. (More)
  • Concerns about AMF as a partner. We have recently had conversations with partners in several countries, during which we explicitly asked for feedback on AMF as a partner. Broadly, we heard positive feedback about AMF, and we heard two main points of constructive feedback. We have shared this feedback with AMF and have started to discuss potential ways to reduce the challenges caused by AMF's operating model and requirements. (More)
  • Uncertainties in our cost-effectiveness model. We are uncertain about the values we use for several of the parameters included in our cost-effectiveness models. (More)
  • Uncertain use of future revenue. We don't know precisely how AMF will use the future revenue that is freed up by this grant. We are aware that AMF is in discussions with a set of countries about the possibility of filling gaps for LLIN campaigns that are scheduled to occur during the current Global Fund grant cycle. (More)
  • Limited track record in Nigeria. The campaigns in Akwa Ibom and Bauchi represent a new location and partnership model for AMF. Results from these campaigns are not yet available. (More)

Risk of future crowding out

The adjustment we describe above is primarily intended to account for the extent to which we believe our funding may be crowding out funding that would otherwise have come from other sources to fill this specific, immediate funding gap. It may not fully account for the effect that our grantmaking may have on other funders' behavior over the long term.

We think it is possible that by filling this funding gap, we are setting the expectation for the NMEP, PMI, and other malaria funders in Nigeria that GiveWell funding will be available to fill future gaps. This belief may, in turn, lead them to direct funding that they would have directed toward these future campaigns to other programs and services. On the other hand, the fact that we expect AMF's contributions to reduce the interval between LLIN campaigns during the 2021-23 period may establish a new norm in PMI-supported states, prompting the NMEP and PMI to aim to maintain that schedule in future years and thereby crowding in additional PMI and/or NMEP funding for LLINs.

In our conversations with national malaria programs and other funders, we have and will continue to communicate that to the extent possible, our goal is for the funding we direct to LLIN campaigns to add to the pool of funding available for those campaigns, rather than to replace funding that would otherwise have been in that pool.

Concerns about AMF as a partner

We have heard occasional feedback that AMF can be difficult for national malaria programs and other partners to work with, relative to other implementing organizations. We see this as a concern for two main reasons, both related to GiveWell's values. First, it could suggest that we are failing on our value of maximizing global wellbeing. If AMF is a lower-quality partner than other implementing organizations (for example, because it adds friction to the planning process that causes delays or otherwise lowers the quality of LLIN campaigns), this would reduce the impact that our grants to AMF can achieve. More broadly, if GiveWell's relationship with AMF as a grantee damages our relationships with other partners, this could reduce our organization-wide ability to make highly impactful grants (for example, by discouraging partners from sharing information with us about other funding gaps). Second, it could suggest that we are failing on our value of emphasizing considerateness, if we continue to support a grantee that creates challenges for other partners.

In investigating this grant and other recent grants to AMF, we had conversations with partners in several countries, during which we explicitly asked for feedback on AMF as a partner. Broadly, we heard positive feedback about AMF that reduced our concern about the risks described above. We heard two main points of constructive feedback. First, the fact that AMF only pays for LLINs and does not fund any of the costs of delivering those nets can cause coordination challenges, because partners must determine how to fund those delivery costs, which can then lead to delays. Second, AMF's requirement that 5% of households registered to receive LLINs be resurveyed can cause challenges, because AMF does not cover the costs of this procedure and because national malaria programs may have existing procedures that then must be replaced with a new methodology. We have shared this feedback with AMF and have started to discuss potential ways to reduce the challenges caused by AMF's operating model and requirements. We will continue to build relationships with program stakeholders to request feedback on AMF's work, as we do with all grantees.

Uncertainties in our cost-effectiveness model

We are uncertain about the values we use for several of the parameters included in our cost-effectiveness model. For this grant, the values we are particularly uncertain about include:

  • Child mortality rates in Nigeria. Our estimate for Nigeria of child mortality (adjusted to estimate mortality in the absence of LLINs) is one of the highest of all the countries where AMF works. While the value we use (an estimated 18 deaths per 1000 child-years) is not a major outlier (the value is comparable in Guinea and is 10-12 deaths in the DRC, Togo, and Uganda), we find it surprising because, according to the World Bank, Nigeria has higher per capita income than those other countries,30 and higher per capita income generally correlates with lower child mortality.31 This raises a concern that the estimates we use may not reflect reality.
  • Likelihood that the Global Fund and/or PMI would replace philanthropic costs.32 In evaluating grants that we make or recommend, we routinely ask: what would happen to this program if it did not receive this grant? Would another funder step in to support it, or would it go unfunded? Through this line of questioning, we develop a best guess of what would happen in a scenario without GiveWell-directed funding, which we refer to as "the counterfactual." Our best guesses about what would happen without GiveWell-directed funding can substantially affect our estimate of a grant's cost-effectiveness, but they are necessarily based on subjective guesses because we don't have the opportunity to witness the counterfactual. This is particularly true when we try to make predictions about the counterfactual behavior of other funders, as we can only speculate about their future priorities and decisions. As such, the adjustments we make to account for our crowding out of other funders (described above) are highly uncertain.

Uncertain use of future revenue

We don't know precisely how AMF will use the future revenue that is freed up by this grant. We roughly project that AMF will raise about $30 million33 over the next year, outside of grants made or recommended by GiveWell. As discussed above, we did not include this revenue in our estimate of the funding available to fill this funding gap because both we and AMF believe that AMF should commit the funding for these campaigns as soon as possible (see above). Consequently, one effect of this grant is to free up AMF's future revenue for support to other campaigns, and we don't know which campaigns AMF will choose to support.

We are aware that AMF is in discussions with a set of countries about the possibility of filling gaps for LLIN campaigns that are scheduled to occur during the current Global Fund grant cycle. Once AMF confirms that it is seeking funding to fill these gaps, we expect to add these countries to our cost-effectiveness model, communicate the results to AMF, and consider funding those that exceed our cost-effectiveness bar. While AMF seeks to fill funding gaps that it expects will be cost-effective, we cannot be certain that AMF will use the future revenue freed up by this grant on the most cost-effective opportunities according to our model, and AMF may choose to work in countries that we estimate to be below our cost-effectiveness bar.

In the next Global Fund grant cycle (2024-26), we expect AMF to consider filling gaps in DRC and Nigeria that are similar to those that it filled during this cycle. We don't yet know which other countries it will consider supporting in 2024-26.

Limited track record in Nigeria

The campaigns in Akwa Ibom and Bauchi will be the first time that AMF supports campaigns in Nigeria. They are also one of the few times in several years that AMF has supported campaigns without Global Fund involvement; our understanding is that while AMF has supported campaigns in the past that also received support from PMI,34 AMF has typically partnered financially with the Global Fund (i.e. with the Global Fund funding the distribution costs and AMF funding the LLINs).

Because this is a new location and partnership model for AMF, we would ideally like to see results from these first two campaigns before funding additional similar campaigns. However, the campaign in Akwa Ibom is scheduled to occur in June 2022,35 and the campaign in Bauchi in September-October 2022,36 so we would have to wait several months for this information to become available. Since we made the grant to AMF for Akwa Ibom and Bauchi:

  • AMF has signed an agreement with the NMEP to support these campaigns.37
  • The schedule for these campaigns was pushed back by a few months. According to AMF, this was due to logistical delays.38
  • AMF has not reported any other issues with the process. Our understanding is that AMF has been working on procuring LLINs and planning for the campaigns.

We expect the following information to become available during and after these campaigns:

  • Registration and backcheck data. AMF collects data on the number of LLINs households are registered to receive during campaigns and the number of people living within those households ("registration data"). It also requires that 5% of these households be revisited so that this data can be recollected ("backcheck data") and compared against the original registration data.39
  • Post-distribution monitoring. AMF contracts with independent organizations to conduct post-distribution monitoring, during which households in the areas targeted by a campaign are surveyed to assess the presence, usage, and condition of LLINs in those households. The first of these surveys will occur 9 months after the relevant campaign.

We could have waited for these results to become available before making this grant. However, we decided that the benefit of AMF ordering nets as soon as possible (see above) outweighed the benefit of waiting for more information, given our expectation that this information is unlikely to substantially decrease our estimate of the cost-effectiveness of this grant.

Plans for follow up

  • We will continue our monthly calls with AMF to discuss its work.
  • We will track whether campaigns occur on schedule or are delayed.
  • We will review the registration data and post-distribution monitoring data collected for these campaigns to understand what proportion of LLINs reach their intended recipients, are used by those recipients, and remain effective while they are in use.
  • We will track how the NMEP and other funders choose to allocate the funding available for future LLIN campaigns in Nigeria.
  • We will continue to build relationships with program stakeholders to request feedback on AMF's work.

Internal forecasts

Confidence Prediction By time
50% Conditional on the completion of a retrospective analysis to update parameters in the model such as costs, total number of people reached, and durability of nets distributed, we will conclude that this grant was at least 12x cash. End of 2026
60% In all three states, campaigns will occur <40 months after the previous campaign. End of 2023

Our process

We learned about this funding gap from AMF. Our grant investigation relied heavily on our prior work modeling the cost-effectiveness of LLIN 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 LLIN campaigns and updated various parameters to match the specifics of this funding gap. One Senior Researcher and two Program Officers at GiveWell who were not involved in the investigation reviewed and gave feedback on the grant prior to approval.

We aim to get feedback on our grantmaking from stakeholders other than our top charities, such as government officials, other implementers involved in delivering the program, or other organizations working in the relevant context. The goals of these conversations are to learn more about the context in which a program will be delivered, to confirm the need for additional support of the program, and to seek feedback on the activities that a potential grant to support the program would enable. The external conversations we had about this grant include:

  • Nigeria’s National Malaria Elimination Programme
  • The Global Fund
  • PMI
  • Malaria Consortium

We value the insights we gained by speaking with these organizations and appreciate the time they spent answering our questions. We note that the views expressed on this page, and any errors, are our own.

Sources

Document Source
AMF, "Akwa Ibom State 2022, Nigeria" Source (archive)
AMF, "Bauchi State, 2022, Nigeria" Source (archive)
AMF, Funds status, January 6, 2022 (unpublished) Unpublished
AMF, PMI Nigeria plan Source
Effective Altruism Funds Source (archive)
GiveWell, "2021 Cost-Effectiveness Analysis Changelog"
Source
GiveWell, "Against Malaria Foundation – Support for LLIN campaigns in Nigeria (2022) and Two Other Countries (2023)"
Source
GiveWell, "Against Malaria Foundation" Source
GiveWell, "Counterfactual net spacing adjustment calculations" (public) Source
GiveWell, "Estimating Equivalent Coverage Years for Long-Lasting Insecticide-Treated Nets (LLINs)," 2020
Source
GiveWell, "GiveDirectly" Source
GiveWell, "Grants and Funding Recommendations in January and February 2021" Source
GiveWell, "Malaria Consortium — Support for LLIN Distribution Campaigns in Ondo and Anambra States, Nigeria (March 2021)" Source
GiveWell, "Recommendation to Open Philanthropy for Grants to Top Charities," 2019 Source
GiveWell, "Why we can’t take expected value estimates literally (even when they’re unbiased)," 2016 Source
GiveWell, "Why we’re excited to fund charities’ work a few years in the future," 2020 Source
GiveWell, 2020 cost-effectiveness analysis — version 2 [change 18 archive]
Source
GiveWell, Likelihood of crowding out GFATM/PMI (updated January 2021) Source
GiveWell, "Maximum Impact Fund," 2022 Source
GiveWell, Room for more funding analysis for AMF [January 2022] (public) Source
Malaria Consortium, Malaria Consortium Net Target Project Report Nigeria 2020 Source
PMI, 2020 Nigeria Funding Tables Source (archive)
PMI, FY 2021 budget Source (archive)
PMI, Nigeria Planned Malaria Obligations for FY 2022 Source (archive)
Roser, Ritchie and Dadonaite, "Child and Infant Mortality," 2013 Source (archive)
World Bank, "GDP per capita (current US$) - Sub-Saharan Africa" Source (archive)
  • 1

    Our room for more funding analysis is here.

  • 2

    See section "Expected as of November 2021, assuming AMF purchases 2023 LLINs" of this spreadsheet.

  • 3

    See this spreadsheet: "PMI are taking on these costs pre end 2023…Plateau non-net costs…Zamfara non-net costs…Benue non-net costs."

  • 4

    AMF, Funds status, January 6, 2022 (unpublished)

  • 5

    For more details, see this page. The two states not covered by one of these funding sources are Ondo and Anambra.

  • 6

    Benue, Plateau and Zamfara are primarily supported by PMI. Malaria Consortium, Malaria Consortium Net Target Project Report Nigeria 2020, Pg 9. Table 2. ITN gaps based on campaign funding landscape.

  • 7

    Our understanding is that most countries aim to conduct mass distributions of LLINs every three years. This is based on evidence that LLIN efficacy declines three years after distribution, suggesting that they should be replaced after that interval. Our review of the evidence has similarly led us to conclude that LLINs provide strong protection from malaria for two to three years on average. See our page estimating equivalent coverage years for LLINs.

  • 8

    See columns L, Q, and V of this spreadsheet for the number of months between LLIN distribution cycles prior to AMF involvement.

  • 9

    We estimate that the counterfactual interval between campaigns would be 45 months. We calculated this figure by averaging the projected interval for campaigns in a no-AMF involvement scenario, from this spreadsheet provided by AMF.

  • 10

    Some of our top charities have a policy of holding funding reserves. In our room for more funding analyses, we typically include reserved funding as funding available to support program activities. We do this both to ensure consistency across top charities (as not all top charities hold reserves) and to understand the true effect of granting additional funding (i.e., whether additional funding would support undertaking additional program activities versus building or maintaining reserves).

  • 11

    AMF is currently committed to purchasing around 50 million nets for other campaigns (unpublished source). We expect it to commit to an additional approximately 25 million nets soon (unpublished source).

  • 12

    See our cost-effectiveness analysis here.

  • 13

    See this spreadsheet, "Cost-effectiveness by funding gap" sheet, column Cost-effectiveness in multiples of cash transfers, including all adjustments, row Against Malaria Foundation: Nigeria (PMI states).

  • 14

    See this parameter here.

  • 15

    See this parameter here.

  • 16

    Malaria Consortium, Malaria Consortium Net Target Project Report Nigeria 2020, Pg 9. Table 2. ITN gaps based on campaign funding landscape analysis.

  • 17

    See the change we made here.

  • 18

    See this parameter here.

  • 19

    We estimate that the counterfactual interval between campaigns would be 45 months. We calculated this figure by averaging the projected interval for campaigns in a no-AMF involvement scenario, from this spreadsheet provided by AMF.

  • 20

    See this parameter here.

  • 21

    For more details, see this page. The two states not covered by one of these funding sources are Ondo and Anambra.

  • 22

    Our understanding is that most countries aim to conduct mass distributions of LLINs every three years. This is based on evidence that LLIN efficacy declines three years after distribution, suggesting that they should be replaced after that interval. Our review of the evidence has similarly led us to conclude that LLINs provide strong protection from malaria for 2-3 years on average. See our page estimating equivalent coverage years for LLINs.

  • 23

    See columns L, Q, and V in this spreadsheet.

  • 24

    PMI, 2020 Nigeria Funding Tables, Table 1, “U.S. President's Malaria Initiative - NIGERIA Planned Malaria Obligations for FY 2020.”

  • 25

    PMI, FY 2021 budget, Table 1: Budget Breakdown by Mechanism U.S. President's Malaria Initiative - NIGERIA Planned Malaria Obligations for FY 2021.

  • 26

    PMI, Nigeria Planned Malaria Obligations for FY 2022

  • 27

    See this spreadsheet.

  • 28

    See this cell.

  • 29

    See this cell.

  • 30

    In 2020, Nigeria had a per capita income of $2,097.10, the DRC of $544.00, Togo of $915.00, and Uganda of $822.00. World Bank, "GDP per capita (current US$) - Sub-Saharan Africa".

  • 31

    “As one would expect, income level of the country is extremely correlated with child mortality rate. The poorest countries have the highest levels of child mortality, and the countries with the highest income have the lowest rates.” Roser, Ritchie and Dadonaite, "Child and Infant Mortality," 2013.

  • 32

    See this parameter in our cost-effectiveness analysis.

  • 33

    This estimate uses 2020 revenue; we have not updated this figure to use 2021 revenue.

  • 34

    According to AMF, PMI funded the non-net costs of approximately half of the nets AMF purchased for the 2019 campaign in Guinea. AMF, comments on a draft of this page, March 2022 (unpublished).

  • 35

    “When: Jun 22.” AMF, "Akwa Ibom State 2022, Nigeria"

  • 36

    “When: Sep-Oct 22.” AMF, "Bauchi State, 2022, Nigeria".

  • 37
    • "Agreement covering process for all five states signed by minister of health and NMEP." Email from AMF, August 11, 2021 (unpublished).
    • Signing agreements with countries can sometimes be a challenge because of the way AMF structures its support. It contributes to partially-funded campaigns, determines the size of the funding gap, and then uses that amount of funding to purchase LLINs. This requires other funders to shift around their resources to buy fewer LLINs than they had planned to and reallocate that funding to distributing AMF-purchased LLINs. In addition, AMF has a set of requirements that are intended to ensure that a high proportion of the LLINs it purchases reach their intended recipients. These requirements may compel AMF's partners to change how they conduct campaigns.
    • According to AMF, this campaign was delayed by several months due to challenges caused by the ongoing Covid-19 pandemic, including delays in net production and shipping. AMF, comments on a draft of this page, March 2022 (unpublished).

  • 38

    Call with AMF on August 12, 2021 (unpublished).

  • 39

    Because enumerators are aware that their work will be audited, this procedure may encourage accurate data collection. It also provides a check on the accuracy of results.