Cost-effectiveness Analysis Comparing 
Integrated and Malaria-only 
Social and Behavior Change 
Programming in Nigeria: 
Final report
TECHNICAL REPORT
MAY 2023
Acknowledgments
We would like to thank the Breakthrough ACTION partners for contributing their time and data for this report and our Breakthrough RESEARCH USAID 
management team and colleagues at the U.S. President’s Malaria Initiative who provided suggestions and guidance throughout.
Breakthrough RESEARCH is funded by the U.S. Agency for International 
Development (USAID) and U.S. President’s Malaria Initiative under the 
terms of Cooperative Agreement No. AID-OAA-A-17-00018. The contents 
of this document are the sole responsibility of Breakthrough RESEARCH 
and Population Council and do not necessarily reflect the views of USAID 
or the United States Government.
Breakthrough RESEARCH catalyzes social and behavior change (SBC) 
by conducting state-of-the-art research and evaluation and promoting 
evidence-based solutions to improve health and development programs 
around the world. Breakthrough RESEARCH is a consortium led by the 
Population Council in partnership with Avenir Health, ideas42, Institute 
for Reproductive Health at Georgetown University, Population Reference 
Bureau, and Tulane University.
The Population Council confronts critical health and development 
issues—from stopping the spread of HIV to improving reproductive 
health and ensuring that young people lead full and productive lives. 
Through biomedical, social science and public health research in about 
50 countries, the Council works with our partners to deliver solutions 
that lead to more effective policies, programs, and technologies to 
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international board of trustees. 
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works to enhance social and economic development by providing tools 
and technical assistance in policy, planning, resource allocation and 
evaluation. Its focus is on developing and implementing demographic, 
epidemiological and costing models for long-range planning to assist with 
setting goals, strategies, and objectives. Avenir Health assists in both 
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©2023 The Population Council. All rights reserved.
Cover photo USG works
Suggested Citation
Avenir Health. 2023. "Cost-effectiveness analysis comparing 
integrated and malaria-only social and behavior change 
programming in Nigeria: Final report," Breakthrough RESEARCH 
Technical Report. Washington, DC: Population Council.
Contact
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breakthroughactionandresearch.org
Cost-effectiveness Analysis Comparing 
Integrated and Malaria-only Social and 
Behavior Change Programming in Nigeria: 
Final report
TECHNICAL REPORT MAY 2023
Avenir Health
List of Acronyms
ACT artemisinin-based combination therapy
ANC antenatal care
BSS behavioral sentinel surveillance 
CCP Johns Hopkins Center for Communication Programs
COVID-19 coronavirus disease 2019
DALY disability-adjusted live year 
DPT3 diptheria-pertussis-tetanus series
GDP gross domestic product
GHSA Global Health Security Agenda
ICER incremental cost-effectiveness ratio
IHP Integrated Health Program
IPTp intermittent preventive treatment in pregnancy
ITN insecticide treated net
LiST Lives Saved Tool
ORS oral rehydration salts
SBC social and behavior change
TB tuberculosis
USAID United States Agency for International Development
US$ United States Dollar
WHO World Health Organization
YLD years of life lost to death
YLL years of life lived with disability
ii COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
Table of Contents
List of Acronyms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Estimating impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Estimating expenditures/costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Calculating cost-effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
RESULTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Cost-effectiveness.................................................................................... 14
DISCUSSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Question 1—What are the total program expenditures incurred during the total study time period from program 
initiation (April 2018) through October 2022? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Question 2—Are the expenditures required for an integrated SBC program, compared to malaria-only SBC 
program, a cost-effective investment? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Question 3—How do malaria-specific outcomes perform within an integrated SBC program compared to a 
malaria-only program? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
APPENDICES
Appendix A: Population data on Breakthrough ACTION intervention coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Appendix B: State-specific results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Appendix C: Further SBC expenditures details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Appendix D: Examining ICER with varying levels of impact attribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
BREAKTHROUGH RESEARCH | MAY 2023 iii
iv COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
Executive Summary
In Nigeria, the Breakthrough ACTION project, funded by the United States Agency for 
International Development (USAID)/Nigeria, is working closely with the Nigerian government 
to improve the practice of priority health behaviors, with a focus on maternal, newborn and 
child health and nutrition, family planning and reproductive health, malaria, and tuberculosis. 
Within the broader program, Breakthrough ACTION uses different social and behavior change 
(SBC) approaches in different states. In northern Nigeria, Breakthrough RESEARCH compared the 
cost-effectiveness of the integrated SBC approach addressing multiple health areas in Kebbi and 
Sokoto states to a malaria-only approach in Zamfara. This cost-effectiveness study examined 
whether the additional cost required for an integrated SBC approach (as compared to a malaria￾only approach) is a cost-effective investment. Additionally, this study examined malaria-specific 
impacts within an integrated SBC program compared to a malaria-only program.
Methods
There are three fundamental steps for estimating the 
relative cost-effectiveness of the two different SBC 
approaches: 1) estimate the impact, 2) estimate the 
costs, and 3) calculate the relative incremental cost￾effectiveness ratio (ICER) using a difference-in-difference 
approach. The foundation for the impact analysis is the 
Breakthrough RESEARCH baseline (2019) and endline 
(2022) behavioral sentinel surveillance (BSS) surveys, 
which include 16 health behavioral outcomes related 
to Breakthrough ACTION’s SBC programming that are 
available for modeling in the Lives Saved Tool (LiST). LiST 
is a linear deterministic causal model that calculates how 
changes in population coverage of specific interventions 
result in lives saved over a specified time period. 
Two scenarios were generated: one that used all 16 
outcomes, and another that only used the outcomes that 
showed a statistically significant difference between the 
integrated state(s) and malaria-only state from baseline 
to endline, based on a difference-in-differences analysis. 
The number of lives saved from the LiST scenarios were 
then translated into disability-adjusted life years (DALYs) 
averted using data obtained from the Global Burden of 
Disease (GBD) Results Tool for Nigeria. 
Program and personnel expenditure data were provided 
by Breakthrough ACTION. SBC expenditures were 
summarized for each of the three study states, examining 
all SBC expenditures and malaria-only expenditures. 
In addition to SBC expenditures, service delivery costs 
associated with changes in the behavioral health 
outcomes were estimated using default values from the 
LiST costing module and were also included. All costs 
were adjusted to 2022 US dollars (US$) using the U.S. 
gross domestic product (GDP) deflator.
Once the impacts and costs were obtained, the ICER was 
calculated as the cost per DALY averted, measuring the 
additional cost needed to achieve the additional impact 
from the integrated states vs. the malaria-only state. The 
cost per DALY averted was then compared to the GDP 
per capita to assess cost-effectiveness, where health 
interventions with a cost per DALY averted that are less 
than the GDP per capita are considered “highly cost￾effective” and those between one- and three-times GDP 
per capita are “cost-effective”.1
 The most recent GDP per 
capita estimates were used and adjusted to 2022 US$, 
resulting in a national threshold of $2,252 and a three￾state GDP average of $860.
Results
The results of the scenario using all health outcomes 
measured by the BSS resulted in a net of 967 lives saved 
in the integrated SBC states and 555 lives lost in the 
malaria-only SBC state. When looking at the outcome￾specific results, one of the biggest changes is from a 
reduction in insecticide treated net (ITN) ownership from 
baseline to endline in the integrated states, resulting in a 
loss of 1,631 lives in the integrated states. This contrasts 
a gain of 403 lives in Zamfara, where there was an 
increase in ITN ownership. Antibiotic use for respiratory 
illness also showed substantial gains and losses, with a 
gain of 1,590 lives in the integrated states and a loss of 
1,211 lives in the malaria-only state. The change in the 
use of oral rehydration salts (ORS) and zinc for diarrhea 
BR E A K THROUGH R ESE A RCH | M AY 2023 1 
from baseline to endline results in lives lost in a gain of 
443 lives in the integrated states and a loss of 762 in the 
malaria-only state. When translating the number of lives 
saved to the additional DALYs averted in the integrated 
SBC states, compared to the malaria-only state, the 
scenarios in Kebbi and Sokoto yielded 47,605 more DALYs 
averted than the malaria-only scenario in Zamfara. For 
malaria-specific DALYs, however, the malaria-only SBC 
approach in Zamfara yielded a net DALY advantage of 
over 66,000 DALYs compared to integrated SBC, due to a 
drop in ITN ownership in the integrated SBC states from 
baseline to endline. 
The SBC expenditures during the study timeframe totaled 
$8.1 million in Kebbi (integrated SBC), $7.2 million in 
Sokoto (integrated SBC), and $3.0 million in Zamfara 
(malaria-only SBC). The SBC expenditures are then 
combined with the service delivery costs associated 
with changes in the behavioral outcomes to get total 
costs. When combined with impact, the ICER (meaning 
the cost per additional DALY averted in the integrated 
states compared to the malaria-only state) is $278 for the 
scaled-up scenario and $426 for the limited scaled-up 
scenario. When compared to the national GDP per capita 
of $2,252 and the three-state average GDP per capita of 
$860, both results are below the “highly cost-effective” 
threshold. 
Because the SBC interventions are not delivered in a 
vacuum and it is likely that some of the impact captured 
by the BSS is attributable to factors other than SBC, 
further analysis examined the proportion of the impact 
(the additional DALYs averted in the integrated SBC areas) 
that would need to be attributed to SBC interventions 
for the investment in integrated SBC states to be cost￾effective. The most difficult threshold to reach is that for 
the three-state average highly cost-effective at $860. 
Using this threshold in the scaled-up scenario, 33% of 
the impact seen in the BSS from baseline to endline 
would need to be due to SBC to be considered highly 
cost-effective. This increases to 50% using the limited 
scaled-up scenario. To be considered cost-effective, 
however, based on the three-state average threshold, 
only 11% of impact needs to be attributed to SBC in 
the scaled-up scenario or 17% in the limited scaled-up 
scenario. Reaching cost-effectiveness is easier using the 
national thresholds, where only 13% of impact needs 
to be attributed to SBC to be considered highly cost￾effective in the scaled-up scenario; 19% is required in 
the limited scaled-up scenario. Finally, using the national 
threshold for cost-effectiveness, only 5% of impact must 
be attributed to SBC under the scaled-up scenario, which 
increases to 7% in the limited scaled-up scenario. 
Discussion
The overall ICER calculations indicate that the additional 
investments for integrated SBC relative to malaria-only 
SBC are highly cost-effective based on both national and 
regional thresholds. The primary drivers of the positive 
results are the increased use of antibiotics for respiratory 
infections and the use of ORS and zinc for diarrhea in the 
integrated states versus the drop in use in the malaria￾only state. While these priority health behaviors are 
addressed in Breakthrough ACTION’s SBC programming 
in the integrated states in both community activities 
(household visits, community dialogues, and community 
meetings) and mass media programming, in addition to 
Breakthrough ACTION programming, there are other 
differences between the integrated and malaria-only 
states that are likely contributing to these impacts. These 
include antibiotic stockouts in the malaria-only state 
of Zamfara and the presence of the Integrated Health 
Program (IHP), which is working in Kebbi and Sokoto on 
a complementary project to improve these outcomes 
through improved primary care services. 
In contrast to the overall findings, the malaria-specific 
outcomes do not appear to be well served by integrated 
SBC. However, there is also an important caveat to 
consider when interpreting these results, as an ITN 
distribution campaign was conducted in the malaria￾only state during the study time frame but not in the 
integrated SBC states. It is notable, that while there was a 
drop in ITN ownership, ITN use among pregnant women 
and young children in the integrated states remained 
stable from baseline to endline, while increasing 
substantially in Zamfara. Unfortunately, the ITN use 
figures cannot be used in LiST due to the underlying 
parameters operating in the model. Still, while a change 
to ITN use instead of ownership would be more favorable 
to the integrated states, it would not change the 
conclusions that the integrated SBC investments were 
deemed highly cost-effective but malaria-only results 
fared better in Zamfara.
The primary limitation of this study is that Zamfara 
does not appear to be a good comparator district for 
Kebbi and Sokoto, due to the stockouts of antibiotics in 
Zamfara, the IHP program presence in Kebbi and Sokoto, 
and the distribution of ITNs in Zamfara but not in Kebbi 
and Sokoto during the study period. However, despite 
2 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
this and other limitations, the findings indicate that 
even if only a relatively small proportion of the overall 
impact modeled is attributed to the SBC activities, the 
SBC investments would be cost-effective. As such, these 
findings are promising for the cost-effectiveness of 
integrated SBC, but not definitive. Future research should 
continue to explore the cost-effectiveness of integrated 
SBC. 
BR E A K THROUGH R ESE A RCH | M AY 2023 3 
Background
In the last decade, many social and behavior change (SBC) programs in health have shifted from 
working in a single health area to a more integrated approach that includes multiple health 
areas and communication channels.2
 While it is hypothesized that integrated SBC will result in 
programs that are more reflective of clients’ needs and thus more cost-effective, these claims are 
largely unproven given the lack of robust studies of integrated SBC approaches.3,4 Additionally, 
while some studies have examined the costs of integrated SBC programs, no studies were 
identified that compared the costs of an integrated SBC approach to a stand-alone approach.5
 To 
address these knowledge gaps, Breakthrough RESEARCH compared the cost-effectiveness of the 
integrated SBC approach versus malaria-only SBC approach in three states (Kebbi, Sokoto and 
Zamfara) of northwestern Nigeria.
In Nigeria, the Breakthrough ACTION project, funded by 
the United States Agency for International Development 
(USAID)/Nigeria, is working closely with the Nigerian 
government to improve the practice of priority health 
behaviors, with a focus on maternal, newborn and child 
health and nutrition, family planning and reproductive 
health, malaria, and tuberculosis (TB). Breakthrough 
ACTION began implementation in April 2018, led by 
Johns Hopkins Center for Communication Programs 
(CCP) with partners Save the Children International, 
ThinkPlace, Ideas42, and Viamo.a
 Breakthrough ACTION 
uses different SBC approaches in different states. In 
northern Nigeria, an integrated SBC approach started 
in Bauchi, Kebbi, and Sokoto, where SBC activities focus 
on multiple health behaviors (malaria, family planning, 
maternal and child health, and nutrition) for women of 
reproductive age who are either currently pregnant or 
are within the 1,000-day window following childbirth.b
In contrast, a malaria-only SBC approach is being used in 
Zamfara state. Some of the SBC interventions that have 
been conducted by Breakthrough ACTION in Nigeria 
include advocacy efforts involving opinion leaders and 
community influencers, community health dialogues with 
individual and group interpersonal communication, radio 
programming, mobile digital interventions, and provider 
behavior change focused on addressing barriers to 
malaria diagnosis and treatment, family planning uptake, 
positive maternal and child health seeking behavior, as 
well as nutrition. 
a
Additionally, the Centre for Communication and Social Impact is a 
Nigerian non-governmental organization that is a subaward under CCP 
and oversees community activities in malaria-only intervention states.
b
Integrated programming extended to Ebonyi state and the Federal 
Capital Territory starting in late 2020.
Breakthrough RESEARCH led an evaluation of 
Breakthrough ACTION’s integrated (malaria, family 
planning, maternal and child health, and nutrition) and 
vertical (malaria-only) SBC programming in northern 
Nigeria, including a study that explored the relative 
cost-effectiveness of the two approaches. The cost￾effectiveness activity consists of three consecutive 
reports. First, the initial phase costing report examined 
expenditures from the program inception in April 2018 
through December 2019, differentiating between 
start-up and implementation expenditures during the 
initial phase of the program.6
 A midline report was 
aligned to the midline behavioral sentinel surveillance 
(BSS) survey and reported SBC expenditures at midline 
(December 2020) and an analysis of the impact of 
the COVID-19 pandemic on SBC expenditures.7
 This 
third and final report is focused on calculating the 
cost-effectiveness of the integrated SBC approach vs. 
malaria-only SBC approach interventions from April 2018 
through October 2022, when the endline BSS survey was 
conducted. Note that the Breakthrough ACTION program 
has been extended beyond the Breakthrough RESEARCH 
evaluation timeframe to 2025; however, no further BSS is 
planned at this time. Figure 1 details the timeline for the 
cost data collection and BSS surveys.
The overall study period includes the beginning of the 
coronavirus disease 2019 (COVID-19) global pandemic, 
which disrupted Breakthrough ACTION Nigeria’s 
community SBC activities for several months starting 
February 2020 through January 2021.6
 Additionally, 
local unrest and security concerns in northwest Nigeria 
escalated in 2021, resulting in a temporary cessation of 
program implementation in parts of Sokoto and Zamfara 
states. Despite these program disruptions, the continued 
4 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
collection of SBC-related expenditures and data from 
the endline BSS allow for an examination of the relative 
cost-effectiveness of the programming between the 
integrated (Kebbi and Sokoto) and malaria-only (Zamfara) 
states as of October 2022.
There are three primary research questions addressed in 
this report:
1. What are the total program expenditures incurred 
during the total study time period from program 
initiation (April 2018) through October 2022? 
2. Are the investments needed for an integrated SBC 
program cost-effective, compared to a malaria-only 
approach? 
3. How do malaria-specific investments perform within 
an integrated SBC program compared to a malaria￾only program?
FIGURE 1 EVALUATION TIMELINE
Initial costing 
phase
April 2018–
December 2019
Only design￾related 
expenditures are 
included in this 
period Baseline BSS
Midline costing 
phase
January 2020–
December 2021
Midline BSS
Final costing
phase
January–
October 2022 Final BSS
Impact timeframe
Costing timeframe
BR E A K THROUGH R ESE A RCH | M AY 2023 5 
Methods
There are three fundamental steps for estimating 
the relative cost-effectiveness of the two different 
SBC approaches: 1) estimate the impact of each, 2) 
estimate the costs of each, and 3) calculate the relative 
incremental cost-effectiveness ratio (ICER) using a 
difference-in-difference approach.
Estimating Impact
The foundation for the impact analysis is the 
Breakthrough RESEARCH Nigeria BSS study, which is 
a multi-round quasi-experimental study designed to 
assess the impact of Breakthrough ACTION programming 
implemented in two integrated SBC states (Kebbi and 
Sokoto) compared to a malaria-only SBC approach in 
Zamfara. The baseline, midline, and endline BSS involve 
interviews with women with a child under two years of 
age in Breakthrough ACTION programming areas and 
assess the ideational factors, behaviors, and outcomes 
associated with key health areas. This analysis relies 
on the behavioral health outcome findings from the 
women’s sample, with 3,020 women interviewed among 
the three states at baseline in December 2019 and 3,144 
in the endline BSS in October 2022.8
 Further details on 
the Breakthrough RESEARCH Nigeria study and the BSS 
methodology can be found at: [insert link to endline 
report on website].
To examine the relative cost-effectiveness of an 
integrated vs. malaria-only SBC approach, a common 
impact measure is needed that can be compared 
across multiple health areas. To achieve this, we used 
the health behavioral outcomes from the BSS as 
inputs into the Lives Saved Tool (LiST). LiST is a linear 
deterministic causal model that was initially developed 
in 2003 to estimate the impact of clinical, hospital, and 
community-based interventions on mortality for children 
under five years and expanded to include maternal 
mortality.9
 LiST is widely used by donors, policy makers, 
academics, and health system stakeholders to examine 
the impact associated with scaling-up key maternal 
and child health, nutrition, and water, sanitation and 
hygiene interventions, including the Bill & Melinda Gates 
Foundation, Gavi, the World Bank Group, Johns Hopkins, 
and UNICEF (www.livessavedtool.org/projects). 
The tool examines how changes in population-level 
coverage of specific interventions translate into the 
number of lives saved over a specified time period. For 
example, Figure 2 shows how the ownership and use of 
insecticide treated nets (ITNs) results in decreased deaths 
among children and mothers. Underlying parameters 
in the tool use validated research studies that capture 
the impact of ITN ownership, which is then translated to 
ITN use through an efficacy factor, to malaria deaths for 
children and maternal deaths from hemorrhage due to 
maternal anemia.10
Table 1 details the 16 behavioral health outcomes 
assessed by the baseline and endline surveys in each 
state that are available to be used in LiST modeling 
and the percentage point change for each outcome in 
each state. Three outcomes are specific to malaria—
ownership of an ITN, at least two doses of intermittent 
preventive treatment in pregnancy (IPTp), and the use of 
artemisinin-based combination therapy (ACT) for fever 
FIGURE 2 MAPPING IMPROVEMENTS IN ITN OWNERSHIP TO REDUCED DEATHS IN LIST 
Source: www.Listvisualizer.org
6 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
in children under two years old. Other reproductive, 
maternal, and child health behavioral outcomes include 
the use of modern contraception among married/
in-union women, attending at least one antenatal (ANC) 
visit and/or at least four ANC visits during the most 
recent pregnancy, breastfeeding behaviors, completing 
the diptheria-pertussis-tetanus series (DPT3) and measles 
vaccines, the use of oral antibiotics for child respiratory 
infections, and the use of oral rehydration salts (ORS) and 
zinc for childhood diarrhea. 
While several changes occurred between the baseline 
and endline BSS, only four of the behavioral health 
outcomes had statistically significant changes (p<0.05) 
when comparing the integrated SBC states to the 
malaria-only SBC state using a difference-in-differences 
analysis, with one of the indicators having a negative 
significant change.8
 As the name implies, difference-in￾differences analyses examine two sets of differences at 
the same time. The first difference is the change in an 
indicator (e.g., current modern family planning use) from 
baseline to endline in an integrated state. This difference 
is then compared with the difference from baseline to 
endline in the same indicator in the comparison state. 
In looking at the statistically significant results from the 
difference-in-differences analyses, first, ITN ownership 
declined substantially in the integrated states of Kebbi 
and Sokoto (32 and 19 percentage points, respectively), 
while it increased by 13 percentage points in the 
malaria-only state of Zamfara. Conversely, the use of oral 
antibiotics increased in Sokoto by 13 percentage points 
and decreased in Zamfara by 22 percentage points. The 
use of ORS also increased in Sokoto by 9 percentage 
points and decreased in Zamfara by 14 percentage 
points. Finally, the use of zinc increased in all three states, 
but more so in Sokoto (16 percentage points) compared 
to Zamfara (5 percentage points). These changes are 
shown in Figure 3. 
TABLE 1 BEHAVIORAL HEALTH OUTCOME CHANGES FROM BASELINE TO ENDLINE BSS AVAILABLE
 FOR USE IN LIST
BEHAVIORAL HEALTH 
OUTCOMES
KEBBI SOKOTO ZAMFARA
BASELINE ENDLINE
% PT 
CHANGE BASELINE ENDLINE
% PT 
CHANGE BASELINE ENDLINE
% PT 
CHANGE
Owns at least one ITN 77.9 45.6 -32.3* 79.7 61.2 -18.5* 74.4 87.7 13.3
IPTp among pregnant 
women (at least 2) 33.5 47.0 13.5 25.6 33.1 7.5 38.3 42.3 4
ACT for children under 2 28.8 23.9 -4.9 17.9 27 9.1 26.1 34.5 8.4
Modern contraceptive 
prevalence 8.6 15.0 6.4 10.7 8.7 -2 14.7 18.1 3.4
At least 1 ANC visit 42.1 45.9 3.8 24.6 31.9 7.3 38.2 48.5 10.3
At least 4 ANC visits 23.6 32.0 8.4 17 21.9 4.9 26.1 37.7 11.6
Facility-based birth 14.8 22.7 7.9 13.8 13.6 -0.2 16.3 26.6 10.3
Early initiation of 
breastfeeding 41.6 39.2 -2.4 31.6 24.2 -7.4 46.1 43.2 -2.9
Exclusive breastfeeding 
(under 1 month) 8.9 19.8 10.9 27.3 9.2 -18.1 43.6 22.3 -21.3
Exclusive breastfeeding 
(under 6 months) 20.3 16.6 -3.7 29.3 11 -18.3 45.9 37.4 -8.5
Any breastfeeding (6+ 
months) 97.9 96.3 -1.6 97.1 98.6 1.5 94.9 96.6 1.7
DPT vaccine 5.7 12.2 6.5 9.6 6.5 -3.1 10.7 18.1 7.4
Measles vaccine 15.9 18.9 3.0 16.5 12 -4.5 19.2 22.5 3.3
Oral antibiotics for 
respiratory illnesses 38.3 58.7 20.4 20.7 33.3 12.6* 45.1 22.9 -22.2
ORS for diarrhea 51.8 47.7 -4.1 27.2 37 9.8* 56 42.4 -13.6
Zinc for diarrhea 30.4 45.0 14.6 18.7 34.8 16.1* 36.8 41.4 4.6
*Indicates a statistically significant difference (p<0.05) when compared to changes in Zamfara using a difference-in-differences analysis.
BR E A K THROUGH R ESE A RCH | M AY 2023 7 
Other outcomes related to ITNs that are not available 
in LiST but are of interest in terms of the effectiveness 
of malaria SBC interventions are shown in Table 2. Note 
that while ITN ownership declined substantially in Kebbi 
and Sokoto from baseline to endline as shown in Table 1, 
the actual use of ITNs by pregnant women and children 
did not decline substantially from baseline to endline, 
but rather made small improvements, albeit a very slight 
reduction (0.4 percentage points) for children under 
two years in Kebbi. These small changes, however, still 
contrast with the substantial gains in net use in Zamfara. 
While it would be preferred to use the proportion of 
pregnant women and young children sleeping under 
an ITN as reported in the BSS for the LiST modeling, 
unfortunately, this is not feasible due to the underlying 
parameters that link the behaviors to the impacts, as 
shown in Figure 2. 
The percentage change values shown in Table 1 were 
used to populate a LiST file for each of the three 
states. Each state-specific file uses inputs that have 
been previously validated by stakeholders at the state￾level. To begin, the default population data from LiST 
were adjusted to reflect the population of those living 
in the Breakthrough ACTION intervention wards for 
community-level interventions at midline, as provided 
by Breakthrough ACTION. Appendix A details the 
intervention wards and population estimates used for 
each state. The proportion of the state population living 
in the intervention wards amounted to 60% in Kebbi, 53% 
in Sokoto, and 25% in Zamfara, which translates into over 
6 million living in the intervention wards in the integrated 
states versus approximately 1.3 million in malaria-only 
state at midline. Next, three LiST scenarios were run for 
each state:
1. A “baseline” scenario that uses the baseline BSS 
values for each of the 16 behavioral health outcomes 
and keeps these values constant from 2019 through 
2022.
2. A “scaled-up” scenario that uses the baseline BSS 
values for 2019, the endline BSS values for 2022, and 
uses linear interpolation between 2019 (baseline) 
and 2022 (endline) to estimate outcome values for 
FIGURE 3 PERCENTAGE POINT CHANGES FROM BASELINE TO ENDLINE FOR HEALTH OUTCOMES
 THAT WERE STATISTICALLY SIGNIFICANTLY DIFFERENT WHEN COMPARING KEBBI AND/
 OR SOKOTO TO ZAMFARA
ORS for diarrhea
-32.3
Zinc for 
diarrhea
ORS for 
diarrhea
Oral antibiotics 
for respiratory infections
Owns at least 
1 ITN
-18.5
Kebbi
Percentage point change from baseline to endline
Sokoto
Zamfara
13.3
20.4
12.6
-22.2
-4.1
9.8
-13.6
14.6 16.1
4.6
TABLE 2 ADDITIONAL INDICATORS RELATED TO 
 ITNS NOT AVAILABLE IN THE LIST
MALARIA 
INDICATOR
KEBBI SOKOTO ZAMFARA
Pregnant women 
sleeping under 
a long-lasting 
insecticide 
treated net (LLIN)
22.7%–27.0%
(+4.3)
24.0%–26.4%
(+2.4)
30.5%–70.5%
(+40.0%)
Children under 
2 sleeping under 
an LLIN
31.0%–30.6%
(-0.4)
37.1%–39.8%
(+2.7)
40.1%–78.5%
(+38.4%)
8 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
2020 and 2021, when BSS data were not collected 
for all the behavioral health outcomes measured in 
the BSS. 
3. A “limited scaled-up” scenario similar to the 
scaled-up file, but this scenario only uses values for 
the behavioral health outcomes that had statistically 
significant changes from baseline to endline in the 
BSS.
The number of lives saved was estimated for each state 
based on comparing both the scaled-up and limited 
scaled-up scenarios to the baseline scenario. Due to 
underlying population dynamics, the best approach for 
calculating the number of lives saved based on changes 
in the behavioral health outcomes differs for mothers 
and children.c,11 To calculate maternal lives saved, the 
number of deaths from the two scaled-up scenarios 
measuring program impact was subtracted from the 
baseline scenario for each cause of death. For children, 
the number of lives saved were estimated for each 
intervention in the scaled-up scenarios. 
The number of lives saved from LiST were then translated 
into disability-adjusted life years (DALYs) averted using 
data obtained from the Global Burden of Disease (GBD) 
Results Tool for Nigeria. Total DALYs averted are the 
years of life lost to death (YLL) and the years of life lived 
with disability (YLD). Their value lies in being able to 
aggregate outcomes along a common metric versus using 
a variety of disparate outcomes across different health 
c
Increases in contraception averts maternal deaths, which are best 
captured when subtracting the deaths from the scaled-up scenario from 
the deaths in the baseline scenario. Using this approach for children 
however, results in an overestimate of deaths averted because it includes 
the prevention of deaths of children who were never born due to 
contraception increases. As such, using the “lives saved” estimates from 
LiST is preferable when examining impacts on children.
domains, such as the number of new users of modern 
contraception, the number of fully vaccinated children, 
or the number of health facility visits for treatment of 
fever. Using DALYS also permits the aggregation of both 
mortality and morbidity from health causes. Figure 4
shows an illustrative example of how changes in health 
behaviors map to DALYs averted.12
To estimate the number of DALYs averted due to changes 
in behavioral health outcomes in Nigeria, we calculated 
the number of DALYs per death for each relevant cause 
of death and applied it to the estimated number of 
lives saved from LiST. The resulting DALYs averted were 
then discounted at 3%, following standard practices for 
cost-effectiveness evaluation.13 The DALYs averted for 
Kebbi and Sokoto states were aggregated to compare 
integrated SBC to the malaria-only approach in Zamfara. 
See Appendix B for state-specific results. 
Estimating expenditures/costs
What follows is a brief synopsis of the methods 
employed to arrive at estimates of expenditures for the 
cost-effectiveness analysis of Breakthrough ACTION’s 
integrated and malaria-only SBC programs. For a more 
detailed and in-depth examination of the methodology 
and results, please refer to Appendix C. SBC program 
implementation and personnel expenditured
 data were 
provided through Breakthrough ACTION’s financial 
and accounting system for the three costing phases of 
the evaluation timeline as outlined in Figure 1: initial 
d
Program implementation expenditures include all funding expended 
on training, equipment, supplies, travel, utilities, and other overheads, 
etc., for the implementation of each program area. Personnel costs were 
isolated from these other program expenditures due to the way in which 
they were captured and presented in the data provided by Breakthrough 
ACTION.
FIGURE 3 PERCENTAGE POINT CHANGES FROM BASELINE TO ENDLINE FOR HEALTH OUTCOMES
 THAT WERE STATISTICALLY SIGNIFICANTLY DIFFERENT WHEN COMPARING KEBBI AND/
 OR SOKOTO TO ZAMFARA
ORS for diarrhea
FIGURE 4 ILLUSTRATIVE EXAMPLE OF AGGREGATING HEALTH IMPACTS INTO DALYS AVERTED
SPECIFIC HEALTH IMPACTS
malaria infections
maternity complications
vaccine-preventable 
diseases
COMMON HEALTH IMPACT
disability-adjusted life years 
averted (DALY)
HEALTH BEHAVIORS
use of insecticide-treated 
bed nets and preventive 
treatment for pregnant 
women
modern contraception
child vaccinations
} #
BR E A K THROUGH R ESE A RCH | M AY 2023 9 
costing phase (April 2018 to December 2019); midline 
costing phase (January 2020 to December 2021); and the 
endline costing phase (January 2022 to October 2022). 
Once expenditure data for each phase were received, 
they were evaluated and validated through direct 
communication with Breakthrough ACTION. Expenditure 
analyses for the initial and midline costing reports were 
each discussed with Breakthrough ACTION to agree on 
the approach and findings.
SBC program expenditures were aggregated across 
all three time periods. Since the radio program was 
delivered state-wide and the impacts are being 
assessed among the intervention areas, the mass media 
expenditures were adjusted by multiplying the total mass 
media expenditures to the percent of the population 
living in the community SBC program intervention 
wards in each state as compared to the total population. 
Malaria-only SBC expenditures in each state were also 
examined, using the same approach for allocating mass 
media expenditures. 
Expenditures for personnel at site-level (the point 
of implementation) and above-site (Abuja and 
organizational headquarters) were aggregated, along 
with partner expenditures to arrive at a total expenditure 
for personnel for each of the study states. Program 
design expenditures were included as an important 
investment throughout the life of the project. Design 
expenditures were aggregated for each of the initial, 
midline, and endline costing phases. These were then 
allocated across the life of the project starting from the 
year the investment was first made, to the end year of 
the project in 2025. 
In addition to SBC-related program and personnel 
expenditures, we included additional service delivery 
expenditures that could be associated with the desired 
changes in behavioral health outcomes. Using the LiST 
costing module, we estimated the potential change in 
total intervention service delivery expenditure based 
on the two modeled scenarios: scaled-up and limited 
scaled-up. These service delivery expenditures were then 
added to all other SBC-related expenditures to present an 
aggregated total.
Finally, all costs were adjusted to 2022 US dollars (US$) 
using the GDP deflator as published by the Federal 
Reserve Bank of St. Louis, on the FRED Economic Data 
website (https://fred.stlouisfed.org/series/GDPDEF#).
Calculating cost-effectiveness
Using the total costs and total impact described above, 
the incremental cost-effectiveness ratio (ICER) was 
calculated by examining the additional costs of integrated 
SBC relative to malaria-only SBC needed to achieve an 
additional DALY averted.12 This was calculated by dividing 
the additional costs by the additional impacts:
The resulting ICER is the cost per DALY averted 
for integrated SBC relative to malaria-only SBC. To 
determine if the cost per DALY averted falls within 
ranges considered cost-effective by the World Health 
Organization, the ICER is compared to both the national 
gross domestic product (GDP) per capita and the average 
GDP per capita across the three study states. According 
to World Health Organization’s guidelines, health 
interventions with a cost per DALY averted that are less 
than one-times GDP per capita are considered “highly 
cost-effective” and those with a cost per DALY averted 
between one- and three-times GDP per capita are 
“cost-effective”.1
For Nigeria, the most recent estimate for GDP per capita 
is $2,066 in 2021.14 Because this study is conducted in 
three specific states in northern Nigeria with lower GDPs 
per capita than the national GDP per capita, an average 
of the three state-level GDP per capita values were also 
included as a regional threshold for cost-effectiveness.e
To ensure comparability with the costs, the GDPs 
per capita were adjusted to 2022 US$; the resulting 
thresholds are shown in Table 3. 
A comparison of the ICER with the thresholds in Table 
3 was used to determine whether the additional 
e
Kingmakers - State of States - GDP Size Ranking
TABLE 3 THRESHOLDS FOR COST-
 EFFECTIVENESS
THREE STATE 
AVERAGE
NATIONAL
Cost-effective $2,580 $6,755
Highly cost-effective $ 860 $2,252
Incremental cost￾effectiveness 
ratio (ICER) 
=
Integrated costs – Malaria only costs
Integrated DALYs averted – 
Malaria only DALYs averted
10 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGR AMMING IN NIGERIA: FINAL REPORT
investments needed for integrated SBC are cost-effective 
based on the health outcomes captured at baseline and 
endline in the BSS. 
Further analyses were conducted to see what proportion 
of the overall impact from baseline to endline would 
need to be attributed to SBC differences for the 
additional investments in integrated SBC to be cost￾effective. To estimate these proportions, the ICER was 
calculated keeping the costs constant but multiplying the 
total DALYs averted by each percentage point between 1 
and 100 and compared to the thresholds.
BR E A K THROUGH R ESE A RCH | M AY 2023 11 
RESULTS
Impact
Breakthrough ACTION-Nigeria’s SBC programming aims 
to improve health behaviors and thus improve the health 
and wellbeing of the people in northern Nigeria. As 
such, positive impact in the key health behaviors would 
facilitate progress toward the Sustainable Development 
Goals by reducing maternal mortality and preventable 
deaths in newborns and children under five years.15
The number of lives saved based on the changes in 
behavior between the baseline and endline BSS in 
each state as modeled in LiST are shown in Table 4, 
disaggregated by reproductive, maternal, and child 
interventions. The number of lives saved in Table 4 
corresponds to Table 1, so that increases in coverage of 
outcomes generate positive lives saved and decreases 
in coverage result in lives lost (expressed as negative 
numbers). For the scaled-up scenario, the changes 
from baseline to endline yield a net of 967 lives saved 
in the integrated SBC states, and 555 lives lost in the 
malaria-only SBC state. When looking at the outcome￾specific results, some of the biggest changes are from 
ITN coverage, resulting in a loss of 1,631 lives in the 
integrated SBC states where ITN coverage decreased 
from baseline to endline, respectively, and a gain of 403 
lives in Zamfara. Antibiotic use for respiratory illness is 
another outcome where there are substantial gains and 
losses in life estimated, resulting in 1,590 lives saved in 
the integrated SBC states and a loss of 1,211 lives in the 
malaria-only SBC state. The change in the use of ORS and 
zinc for diarrhea from baseline to endline results in lives 
lost in a gain of 443 lives in the integrated SBC states and 
a loss of 762 in the malaria-only SBC state. 
The limited scaled-up scenario uses only values for 
the behavioral health outcomes where there was a 
statistically significant difference in changes between 
an integrated SBC and malaria-only SBC state. These 
include changes in ITN ownership, changes in antibiotics 
for respiratory infections, ORS/zinc for diarrhea.f
 In this 
scenario, there is a net loss of 571 lives in the integrated 
SBC states due to the elimination of the non-statistically 
f
The difference-in-difference analyses found statistically significant 
(p<0.05) changes in ITN ownership when comparing both Kebbi and 
Sokoto states to Zamfara; however, only the Sokoto changes were 
statistically significant for changes in antibiotics for respiratory infections, 
ORS use, and zinc use.
TABLE 4 LIVES SAVED FROM INTEGRATED SBC AND MALARIA-ONLY SBC SCENARIOS (2020–2022)
SCALED-UP LIMITED SCALED-UP
INTEGRATED MALARIA-ONLY INTEGRATED MALARIA-ONLY
Maternal
Pregnancy 23 15 0 0
Childbirth 75 101 0 0
Contraception 117 103 0 0
Subtotal 215 219 0 0
Child
Prenatal care 140 44 0 0
ITN coverage -1631 403 -1654 408
Childbirth 313 420 0 0
Breastfeeding -265 -19 0 0
Vaccines (DPT and measles) 3 25 0 0
ACT use 159 326 0 0
ORS and zinc for diarrhea 443 -762 521 -768
Antibiotics for respiratory illness 1590 -1211 562 -1226
Subtotal 752 -774 -571 -1586
12 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGR AMMING IN NIGERIA: FINAL REPORT
significant outcome variables. The malaria-only SBC state 
saw an increase in lives lost, resulting in 1,586 lives lost.
When converting the number of lives saved in the 
scaled-up scenarios to the additional DALYs averted in 
the integrated SBC states relative to the malaria-only 
SBC state, the integrated states yielded 47,605 more 
DALYs averted than the malaria-only state (Figure 
5). The limited scaled-up scenario that considers just 
the statistically significant outcomes results in fewer 
DALYs averted, 31,814. Figure 5 also shows the number 
of malaria-specific DALYs averted in the integrated 
states compared to the malaria-only state, where the 
difference between the integrated and malaria-only 
states is negative because there were substantially more 
DALYs averted in the malaria-only state than in the two 
integrated states. The negative DALYs averted—or DALYs 
lost—was 66,474 for the scaled-up scenario and 64,626 
for the limited scaled-up scenario.
Expenditures
The total expenditure for all SBC programming for the 
total evaluation period, by component, for the integrated 
and malaria-only program study states is shown in 
Figures 6 and 7.
Over the total evaluation period, more than $18 million 
was spent in the study states. Looking at the individual 
study states, the integrated program in Kebbi had the 
largest expenditure over the total evaluation period at 
around $8.1 million. Sokoto’s integrated program had the 
next largest total expenditure at just over $7.2 million, 
and Zamfara, with its stand-alone malaria program, had 
the lowest expenditure overall with just under $3 million. 
Table 5 shows the total SBC expenditures and the 
expenditures per person in the intervention areas for 
each of the integrated and malaria-only study states. In 
FIGURE 5 ADDITIONAL DALYS AVERTED IN
 THE INTEGRATED SBC STATES
 COMPARED TO MALARIA-ONLY
 STATES (2020–2022)
All DALYs averted Malaria DALYs averted
(66,474) (64,626)
Scaled-up scenario Limited scaled-up scenario
(47,649)
(31,814)
FIGURE 6 EXPENDITURES FOR ALL SBC
 PROGRAMMING BY COMPONENT FOR
 INTEGRATED STUDY STATES
Program Personnel Partner
Program
$5,466,824
Design
Personnel
$5,255,448
Partner
$1,915,435
Design
$2,687,801
FIGURE 7 EXPENDITURES FOR ALL SBC
 PROGRAMMING BY COMPONENT FOR
 MALARIA-ONLY STUDY STATES
Program
$638,987
Personnel
$1,150,324
Partner
$775,947
Design
$419.190
BR E A K THROUGH R ESE A RCH | M AY 2023 13 
total, the two study states implementing an integrated 
SBC program (Kebbi and Sokoto) expended over $15.3 
million, of which, about 14% ($2.1 million) on average 
was allocated for malaria-focused SBC and the remaining 
86% ($13.2 million) went to all other SBC programs. In 
the malaria-only study state (Zamfara), around $3 million 
was spent on all SBC with 71% ($2.1 million) of this being 
for malaria focused programming. The other 29% of 
expenditures were for TB and the Global Health Security 
Agenda (GHSA) and their associated personnel expenses 
as well as above-site costs. The expenditure per person 
for all SBC programs was $2.51 per person in integrated 
program areas, and $2.25 per person in the malaria￾only program areas in Zamfara. The malaria-specific 
expenditures per person living in the integrated areas 
was $0.35 and $1.59 per person living in the malaria-only 
intervention areas.
To estimate the total cost of the SBC interventions, 
we calculated the additional service delivery costs 
using default values from the LiST costing module 
associated with the anticipated expanded coverage 
and then added them to the SBC expenditures in each 
state. The differences between the scaled-up scenarios 
and the baseline scenario were then used in the cost￾effectiveness analysis. Table 6 shows the effect of the 
additional service delivery costs when added to the 
malaria-only SBC costs and all other SBC costs for each 
of the three study states. Note that service delivery costs 
are negative in some instances due to a reduction in 
health services. More state-specific details on the SBC 
expenditures can be found in Appendix C. 
Cost-effectiveness
The impact and cost findings combine to calculate the 
ICER as the additional costs for integrated SBC in Kebbi 
and Sokoto relative to the additional costs for malaria￾only programming in Zamfara divided by the additional 
impact for integrated SBC relative to the additional 
impact for malaria-only programming (see Equation 
above). Figure 8 displays the ICER results compared to 
the national and three state average GDP per capita 
benchmarks. The scaled-up scenarios resulted in an ICER 
of $278 per DALY averted, while the scaled-up scenario 
yielded $426 per DALY averted, both of which are “highly 
cost-effective” using either the national GDP per capita 
threshold of $2,252 or the three-state average GDP per 
capita threshold of $860. 
As described in the methods section, further analysis 
examined what proportion of the impact (additional 
DALYs averted in the integrated SBC areas) would need 
to be attributed to SBC, given other concurrent factors in 
each state that could be affecting the results during the 
study period, for the investments in integrated SBC to be 
considered cost-effective. Appendix D shows the cost 
TABLE 5 EXPENDITURE PER PERSON REACHED
 FOR INTEGRATED AND MALARIA-ONLY
 SBC STUDY STATES
INTEGRATED MALARIA ONLY
Total expenditure all SBC $15,325,508 $2,984,448
Total expenditure 
malaria SBC
$2,120,488 $2,112,597
Total population 10,757553 5,066,557
Target population 6,123,722 1,327,297
Target population as % 
of total population
56.3% 25.0%
Expenditure per person 
all SBC
$2.51 $2.25
Expenditure per person 
malaria SBC
$0.35 $1.59
TABLE 6 ADDITIONAL SERVICE DELIVERY EXPENDITURES FOR INTEGRATED & MALARIA ONLY
 STATES FOR THE SCALED-UP AND LIMITED SCALED-UP SCENARIOS
INTEGRATED MALARIA ONLY
SCALED-UP 
SCENARIO
LIMITED 
SCALED-UP 
SCENARIO
SCALED-UP 
SCENARIO
LIMITED 
SCALED-UP 
SCENARIO
Total SBC expenditures $15,325,508 $15,325,508 $2,984,448 $2,984,448
Added service delivery expenditures $1,192,883 $339,859 $425,864 -$873,565
Total expenditures (2022) $16,518,391 $15,665,366 $3,410,312 $2,110,883
Malaria SBC expenditures $2,120,488 $2,120,488 $2,112,597 $2,112,597
Added service delivery expenditures -$592,455 -$909,129 $425,864 $108,377
Total malaria expenditures (2022) $1,528,033 $1,211,359 $2,538,461 $2,220,973
14 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGR AMMING IN NIGERIA: FINAL REPORT
per DALY averted when multiplying the DALYs averted 
to each percentage point possible, from 1 to 100%, that 
could be attributed to the SBC activities. 
Table 7 displays the comparison of those values to the 
four cost-effectiveness thresholds under the scaled-up 
and limited scaled-up scenarios. The most difficult 
threshold to reach is the three-state average highly 
cost-effective threshold at $860. Using this threshold in 
the scaled-up scenario, 33% of the impact seen in the 
BSS from baseline to endline would need to be due to 
SBC to be considered highly cost-effective. This increases 
to 50% using the limited scaled-up scenario. To be 
considered cost-effective, however, based on the three￾state average threshold, only 11% of impact needs to be 
attributed to SBC in the scaled-up scenario or 17% in the 
limited scaled-up scenario. Reaching cost-effectiveness 
is easier using the national thresholds, where only 13% 
of impact needs to be attributed to SBC to be considered 
highly cost-effective in the scaled-up scenario, and 19% 
is required in the limited scaled-up scenario. Finally, using 
the national threshold for cost-effectiveness, only 5% of 
impact must be attributed to SBC under the scaled-up 
scenario, which increases to 7% in the limited scaled-up 
scenario. 
TABLE 7 PROPORTION OF IMPACT ATTRIBUTED TO SBC NEEDED TO REACH COST-EFFECTIVENESS
 THRESHOLDS
THREE STATE AVERAGE NATIONAL
SCALED-UP
SCENARIO
LIMITED 
SCALED-UP SCENARIO
SCALED-UP
SCENARIO
LIMITED 
SCALED-UP SCENARIO
Cost-effective 11% 17% 5% 7%
Highly cost-effective 33% 50% 13% 19%
FIGURE 8 COST-EFFECTIVENESS RESULTS FOR ADDITIONAL COST PER DALY 
 AVERTED FOR INTEGRATED SBC (2020–2022)
$0
$1000
$2000
$3000
$4000
$5000
$6000
$7000
Scaled-up scenario
$6,755—National; cost-effective
Limited scaled-up scenario
$2,580—Three state average; cost-effective
$2,252—Three state average; highly cost-effective
$ 860—National; highly cost-effective
$ 278 $ 426
BR E A K THROUGH R ESE A RCH | M AY 2023 15 
DISCUSSION
To answer the three primary research questions, we 
explored SBC program expenditures, the relative cost￾effectiveness of integrated SBC, and how malaria-specific 
outcomes fared within integrated SBC.
Question 1—What are the total program 
expenditures incurred during the total 
study time period from program initiation 
(April 2018) through October 2022? 
Among the study states, the total SBC expenditures in 
the integrated SBC states were higher when compared 
to the malaria-only SBC state, approximately US$15 
million versus US$3 million. However, the expenditure 
per target population was similar across both approaches 
with integrated SBC at $2.53 per person and $2.36 per 
person in the malaria-only state. When SBC expenditures 
focused only on malaria were examined, $0.35 per 
person was spent in the integrated states vs. $1.67 in the 
malaria-only state. 
Question 2—Are the expenditures required 
for an integrated SBC program, compared 
to malaria-only SBC program, a cost￾effective investment? 
The ICER calculation indicates that the investments for 
integrated SBC, as compared to malaria-only SBC, are 
highly cost-effective based on both the national and the 
three-state average thresholds. The primary driver of this 
result is the increased use of antibiotics for respiratory 
infections in the integrated states versus the drop in use 
in the malaria-only state, resulting in a net difference 
between the integrated and malaria-only programs 
of 2,801 lives in the scaled-up scenarios. Similarly, the 
changes in use patterns for ORS and zinc for childhood 
diarrhea result in a net difference of 1,205 lives in favor 
of integrated programming (scaled-up applications). 
Improving these health behaviors are priority objectives 
addressed in Breakthrough ACTION’s SBC programming 
in the integrated states in both community activities 
(household visits, community dialogues, and community 
meetings) and mass media programming. 
In addition to Breakthrough ACTION programming, 
however, there are other differences between the 
integrated and malaria-only states that could be 
contributing to these behavioral outcomes. Specifically, 
a recent report noted that Zamfara experienced 
antibiotic stockouts during the study period that likely 
contributed to the drop in antibiotic use for respiratory 
infections.16 Additionally, the USAID-funded Integrated 
Health Program (IHP) is working in Kebbi and Sokoto on 
a complementary project to reduce maternal and child 
mortality by working at the health system and health 
facility level to improve the provision of essential primary 
care services.17
For these reasons, the results from Table 6 on the 
proportion of the impact that would need to be 
generated by SBC interventions to be considered 
cost-effective are informative. Based on the national 
benchmark, a modest 5% to 7% of the total impact 
seen from baseline to endline in the BSS needs to be 
attributed to the SBC interventions to be cost-effective 
and 13% to 19% to be highly cost-effective. The three￾state average threshold increases the proportion 
required to be considered highly cost-effective but still 
only 11% (scaled-up) to 17% (limited scaled-up) of the 
total impact is needed to be considered cost-effective. 
These results indicate that while it is unlikely that the 
different approaches in SBC is the primary driver in the 
different outcomes between the integrated and malaria￾only states, the SBC contributions from the intervention 
activities to improving antibiotic use for respiratory 
infections and ORS/zinc for childhood diarrhea are likely 
cost-effective.
Question 3—How do malaria-specific 
outcomes perform within an integrated 
SBC program compared to a malaria-only 
program?
In contrast to the overall findings, malaria-specific 
outcomes do not appear to be well served by integrated 
SBC. However, there are important caveats to consider 
when interpreting these results. The malaria-specific 
lives saved/lost calculated in the LiST model are primarily 
due to ITN ownership, where ownership increased in the 
malaria-only SBC state of Zamfara and decreased in the 
16 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGR AMMING IN NIGERIA: FINAL REPORT
integrated SBC states of Kebbi and Sokoto. These changes 
in ownership result in a net gain of 2,034 lives for the 
malaria-only SBC approach relative to the integrated SBC 
approach. This substantial impact likely has much more 
to do with the fact that an ITN distribution campaign 
was conducted in Zamfara during the study period and 
not in Kebbi and Sokoto, although an ITN campaign in 
Kebbi state coincided partly with the endline BSS.g
 SBC 
accompanying ITN distribution has been found to be 
effective in increasing the use of ITNs, but ownership 
itself is closely tied to distribution campaigns and steady 
declines are typically seen thereafter.18
For this reason, it would be very appealing to use the ITN 
use measures in Table 2 instead of the ITN ownership 
measures in Table 1. However, for reasons explained 
previously, the underlying modeling structure does not 
allow for that option. Still, it should be noted that if such 
a change were possible, it would not alter the overall 
conclusions that the malaria-only SBC state fared better 
in terms of malaria lives saved and DALYs averted due 
to ITN use since the improvements were much greater 
in the malaria-only areas. In contrast, if ITN distribution 
campaigns had fully occurred in the integrated SBC states 
during this time period, it is likely the ITN ownership 
results would be comparable across all three states 
like the other two malaria-related outcomes, IPTp use 
and ACT use. Although the changes from baseline to 
endline in the BSS were not statistically significant, the 
percentage of women receiving at least two doses of 
IPTp increased in all three states, with higher increases 
in the integrated states (14 and 7 percentage points) 
than in the malaria-only state (4 percentage points). 
ACT use dropped in Kebbi by 5 percentage points but 
increased in Sokoto and Zamfara by 9 and 8 percentage 
points, respectively, although these changes were 
also not statistically significant. Note that, since SBC 
expenditures are not allocated specifically to outcomes, 
it is not possible to calculate ICERs for these two specific 
outcomes, but instead the ICERs need to be calculated 
for SBC investments in malaria. 
Limitations
As noted in the discussion above, the primary limitation 
of this study is that Zamfara does not appear to be 
a good comparator for Kebbi and Sokoto due to the 
stockouts of antibiotics in Zamfara, the IHP program 
presence in Kebbi and Sokoto, and the distribution 
g
At the time of the endline BSS, ITN distribution had begun in Kebbi state.
campaign of ITNs in Zamfara only during the study 
period. In addition, as with all modeling exercises, the 
results are based on numerous inputs and assumptions. 
Among other things, the expenditure data for the initial 
evaluation period and those for both the midline and 
endline periods differed slightly in terms of form and 
content. While each of the reports presented rational 
estimations of cost, calculating these estimations 
required assumptions on the allocation of above-site 
costs and the distribution of personnel costs. 
On the impact side, while the DALYs-averted metric 
used in this analysis does allow for comparison across 
different health areas, it does not fully capture the 
entire impact of the Breakthrough ACTION’s integrated 
SBC program, which also influences social norms and 
attitudes as well as building local SBC capacity that 
may not have yet translated into measurable health 
behavior change during the study time period. Where 
there were observable changes, few were noted to be 
statistically significant. The LiST modeling also does not 
allow for the changes in the number of people living in 
the intervention areas over time, but rather takes the 
midpoint population as the best proxy for the program. 
Another clear limitation previously discussed is the use 
of the ITN ownership variable for this particular study 
due to the focus on malaria-related outcomes and the 
different results seen in terms of ownership and use. 
Conclusions
This study is one of the first to examine the cost￾effectiveness of integrated SBC. Overall, the findings 
indicate that even if only a relatively small proportion 
of the overall impact modeled is attributed to SBC, the 
SBC investments would be considered cost-effective. 
As such, these findings are promising, but not definitive 
given the challenges of using Zamfara as a comparator to 
the integrated states during this time period. Leveraging 
further Breakthrough ACTION work could potentially 
address some of the challenges in this analysis; future 
work should continue to explore the cost-effectiveness of 
integrated SBC programs.
BR E A K THROUGH R ESE A RCH | M AY 2023 17 
REFERENCES
1. WHO Commission on Macroeconomics and Health & World 
Health Organization. 2001. “Macroeconomics and health: 
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Health.” Geneva: World Health Organization. https://apps. 
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2. Compass. 2017. Integrated SBC. Accessed February 11, 2023 
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3. FHI 360. 2014. “Integration of global health and other devel￾opment sectors: A review of the evidence.” Washington, DC: 
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Accessed March 19, 2021. 
4. Velu, S. et al. 2016. “Social and behavior change communi￾cation in integrated health programs: A scoping and rapid 
review.” HC3 Project and UNICEF.
5. Breakthrough RESEARCH. 2022. SBC cost data repository. 
Accessed March 28, 2023 at: https://breakthroughactionan￾dresearch.org/creating-sbc-cost-repository/.
6. Initial costing report
7. Avenir Health. 2023. “Cost-effectiveness analysis compar￾ing integrated and malaria-only social and behavior change 
programming in Nigeria: Midline analysis,” Breakthrough 
RESEARCH Technical Report. Washington, DC: Population 
Council.
8. Hutchinson, P. L. et al. (forthcoming). «Behavioral sentinel 
surveillance survey in Nigeria: Endline technical report,» 
Breakthrough RESEARCH Technical Report. Washington, DC: 
Population Council.
9. Walker N, Tam Y, Friberg IK. 2013. “Overview of the Lives 
Saved Tool (LiST),” BMC Public Health 13(Suppl 3): S1. doi: 
10.1186/1471-2458-13-S3-S1
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of interventions for preventing malaria mortality in children 
in Plasmodium falciparum endemic areas,” Int J Epidemiol.
39(Suppl 1): i88-101. doi: 10.1093/ije/dyq026.
11. Winfrey, W. Personal communication with William Winfrey, 
January 13, 2023.
12. Breakthrough RESEARCH. 2022. “Breakthrough RESEARCH—
Social and Behavior Change Costing Community of Practice 
Series Brief #4: Are integrated social and behavior change 
interventions cost-effective? A methodological approach,” 
Programmatic Research Brief. Washington, D.C.: Population 
Council.
13. Vassall, A. et al. 2018. “Reference case for estimating the 
costs of global health services and interventions.” Accessed 
February 28, 2023 at: GHCC | Global Heath Cost Consortium 
(ghcosting.org)
14. World Bank. 2021. GDP per capita (current US$) – Nigeria. 
Accessed February 11, 2023 at: GDP per capita (current US$) 
- Nigeria | Data (worldbank.org).
15. United Nations. 2022. The sustainable development goals 
report. Accessed March 28, 2023 at: https://unstats.
un.org/sdgs/report/2022/The-Sustainable-Develop￾ment-Goals-Report-2022.pdf.
16. USAID. Personal communication during quarterly meetings. 
February 13, 2023.
17. Integrated Health Program (IHP). 2022. “Feature: PHC exten￾sion services bring integrated healthcare closer to women, 
children, and communities in Sokoto.” Accessed February 14, 
2023 at: https://medium.com/@NigeriaIHP_/bringing-inte￾grated-healthcare-closer-to-communities-to-reach-wom￾en-and-children-facing-preventable-89cbe650684c.
18. Kilian, A., N. Wijayanandana, and J. Ssekitoleeko. 2010. “Re￾view of delivery strategies for insecticide treated mosquito 
nets: are we ready for the next phase of malaria control 
efforts?” TropIKA. Net. 1(1).
19. Bollinger, L.A. et al. 2017. “Lives Saved Tool (LiST) costing: a 
module to examine costs and prioritize interventions,” BMC 
Public Health 17(Suppl 4): 782. doi: 10.1186/s12889-017-
4738-1.
18 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGR AMMING IN NIGERIA: FINAL REPORT
APPENDIX A
POPULATION DATA ON BREAKTHROUGH ACTION 
INTERVENTION COVERAGE
To estimate the population for the LiST applications, the proportion of the total state population living in the 
intervention areas at midline was used. Table A1 details the 2020 population estimates for each Breakthrough 
ACTION intervention ward included in the analysis. Next, the percentage of the state population represented in the 
Breakthrough ACTION areas was applied to the 2022 population estimates in each state, as provided by the Spectrum 
models, which were previously validated under another program. Table A2 details the population numbers included in 
the LiST applications. 
TABLE A1 INTERVENTION STATES, LGAS, WARDS, AND 2020 POPULATION ESTIMATES
STATE LGA WARD 2020 
POPULATION
Kebbi Arewa Bachaka 32,489
Kebbi Arewa Chibike 16,898
Kebbi Arewa Falde 9,479
Kebbi Arewa Feske/Jefeji 22,941
Kebbi Arewa Gorun Dikko 10,967
Kebbi Arewa Lema/Jan Tullu 37,961
Kebbi Arewa Sarka 22,513
Kebbi Arewa Bui 31,706
Kebbi Arewa Gumundai 27,811
Kebbi Arewa Kangiwa 28,270
Kebbi Arewa Yeldu 24,422
Kebbi Bagudo Bani Tsamiya 38,976
Kebbi Bagudo Lafagu Gante 24,836
Kebbi Bagudo Matsinkai Geza 18,995
Kebbi Bagudo Kende Kurgu 23,294
Kebbi Bagudo Zagga Kwasara 27,153
Kebbi Bagudo Kaoje Gwamba 65,501
Kebbi Bagudo Bagudo Tuga 37,220
Kebbi Bagudo Bahindi Khaliel 25,265
Kebbi Bagudo Illo Sabon Gari 28,801
Kebbi Bagudo Lolo Giris 40,749
Kebbi Bagudo Sharabi 
Kwanguwai 21,336
Kebbi Birnin Kebbi Gawasu Damana 16,228
Kebbi Birnin Kebbi Gulumbe 17,572
Kebbi Birnin Kebbi Kardi 34,877
Kebbi Birnin Kebbi Lagga Randali 15,716
Kebbi Birnin Kebbi Makera 19,743
Kebbi Birnin Kebbi Karyo 25,134
STATE LGA WARD 2020 
POPULATION
Kebbi Birnin Kebbi Asarara 18,345
Kebbi Birnin Kebbi Zauro 15,031
Kebbi Birnin Kebbi Ambursa 21,970
Kebbi Birnin Kebbi Dangaladima 37,023
Kebbi Birnin Kebbi Gwadangwaji 30,099
Kebbi Birnin Kebbi Kola Tarasa 19,141
Kebbi Birnin Kebbi Marafa 31,304
Kebbi Birnin Kebbi Nassarawa I 45,121
Kebbi Birnin Kebbi Nassarawa II 54,018
Kebbi Fakai Bangu 21,792
Kebbi Fakai Fakai Kukah 16,073
Kebbi Fakai Gulbin Kukah 15,475
Kebbi Fakai Kangi 15,780
Kebbi Fakai Marafa 19,460
Kebbi Fakai Penipeni 14,326
Kebbi Fakai Bajida 18,765
Kebbi Fakai Birnin Tudu 11,239
Kebbi Fakai Mahuta 21,091
Kebbi Fakai Maikende 20,843
Kebbi Gwandu Cheberu 28,048
Kebbi Gwandu Dalijan 27,298
Kebbi Gwandu Gwandu Marafa 21,048
Kebbi Gwandu Masama 20,949
Kebbi Gwandu Gulmare 23,413
Kebbi Gwandu Dodoru 20,044
Kebbi Gwandu Gwandu 
Dangaladima 20,660
Kebbi Gwandu Kambaza 17,440
Kebbi Gwandu Malisa 20,298
BR E A K THROUGH R ESE A RCH | M AY 2023 19 
STATE LGA WARD 2020 
POPULATION
Kebbi Koko Besse Dada Alelu 12,133
Kebbi Koko Besse Zaria 16,094
Kebbi Koko Besse Takware 21,048
Kebbi Koko Besse Damba Bakoshi 17,536
Kebbi Koko Besse Jadadi 14,711
Kebbi Koko Besse Koko Firchin 22,769
Kebbi Koko Besse Hirini Madacci 13,284
Kebbi Koko Besse Illela Sabon Gari 22,868
Kebbi Koko Besse Besse 19,867
Kebbi Koko Besse Dutsi Mari 25,000
Kebbi Koko Besse Koko Magaji 19,980
Kebbi Koko Besse Lani Shiba 17,720
Kebbi Maiyama Gidiga 23,266
Kebbi Maiyama Giwatazo 21,406
Kebbi Maiyama Kawara 25,182
Kebbi Maiyama Karaye 25,533
Kebbi Maiyama Andarai 23,570
Kebbi Maiyama Liba 23,475
Kebbi Maiyama Gubunkure 23,450
Kebbi Maiyama Maiyama 18,363
Kebbi Maiyama Mungadi 26,628
Kebbi Maiyama Sambawa Mayalo 24,594
Kebbi Maiyama Sarandosa 24,941
Kebbi Wasagu/Danko Dan Umaru 35,739
Kebbi Wasagu/Danko Gwanfi Kele 19,680
Kebbi Wasagu/Danko Kyanbu Kandu 27,705
Kebbi Wasagu/Danko Wasagu 36,719
Kebbi Wasagu/Danko Yalmo Shindy 
Wari 16,001
Kebbi Wasagu/Danko Ayu 25,305
Kebbi Wasagu/Danko Bena 45,410
Kebbi Wasagu/Danko Danko Maga 25,329
Kebbi Wasagu/Danko Kanya 52,483
Kebbi Wasagu/Danko Ribah Machika 44,885
Kebbi Wasagu/Danko Waje 67,229
Kebbi Shanga Dugu Tsoho 21,016
Kebbi Shanga Kawara 20,863
Kebbi Shanga Rafin Kirya 13,419
Kebbi Shanga Atuwo 15,905
Kebbi Shanga Yarbesse 11,746
Kebbi Shanga Gebbe 22,633
Kebbi Shanga Sakace 27,744
Kebbi Shanga Sawashi 18,508
Kebbi Shanga Shanga 16,484
Kebbi Shanga Takware 15,086
STATE LGA WARD 2020 
POPULATION
Kebbi Suru Aljannare 31,082
Kebbi Suru Bandan 22,470
Kebbi Suru Ginga 13,712
Kebbi Suru Dandane 16,120
Kebbi Suru Barbarejo 19,191
Kebbi Suru Kwaifa 14,533
Kebbi Suru Bakuwai 24,979
Kebbi Suru Dakin Gari 29,841
Kebbi Suru Dandiya Shema 8,536
Kebbi Suru Giro 9,723
Kebbi Suru Suru 32,784
Kebbi Zuru Daben Seme 18,080
Kebbi Zuru Zodi 15,215
Kebbi Zuru Manga Ushe 32,680
Kebbi Zuru Rikoto 33,017
Kebbi Zuru Senchi 21,294
Kebbi Zuru Bedi 26,085
Kebbi Zuru Dabai 22,187
Kebbi Zuru Isgogo Dago 22,758
Kebbi Zuru Rafin Zuru 31,352
Kebbi Zuru Tadurga 23,587
KEBBI TOTAL 2,950,235
Sokoto Binji Jamali 13,074
Sokoto Binji Tudun Kose 11,352
Sokoto Binji Gawazai 14,233
Sokoto Binji Bunkari 16,757
Sokoto Binji Soro Gabas 16,354
Sokoto Binji Binji 33,823
Sokoto Binji Inname 10,233
Sokoto Binji Maikulki 17,910
Sokoto Binji Samama 12,175
Sokoto Binji Soron Yamma 15,479
Sokoto Bodinga Bagarawa 14,215
Sokoto Bodinga Bangi/Dabaga 33,334
Sokoto Bodinga Dingyadi 28,255
Sokoto Bodinga Sifawa Lukuyawa 17,118
Sokoto Bodinga Tulluwa 20,031
Sokoto Bodinga Badau 10,550
Sokoto Bodinga Bodinga 33,539
Sokoto Bodinga Danchadi 38,970
Sokoto Bodinga Kauramiyo￾Mazan Gari 32,065
Sokoto Bodinga Kwacciyo Lalle 14,050
Sokoto Bodinga Takatuku 28,590
20 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
STATE LGA WARD 2020 
POPULATION
Sokoto Dange/Shuni Bodai 32,365
Sokoto Dange/Shuni Dange 36,205
Sokoto Dange/Shuni Fajaladu 18,915
Sokoto Dange/Shuni Gere-Gajere 18,915
Sokoto Dange/Shuni Rikina 36,345
Sokoto Dange/Shuni Rudu/ Amanawa 36,205
Sokoto Dange/Shuni Ruggar Gidado 17,810
Sokoto Dange/Shuni Shuni 31,085
Sokoto Dange/Shuni Tsafanade S 16,670
Sokoto Dange/Shuni Tuntube Tsefe 65,555
Sokoto Dange/Shuni Wababe 26,820
Sokoto Gada Kadadi 27,433
Sokoto Gada Kiri 33,194
Sokoto Gada Kwarma 27,414
Sokoto Gada Gilbadi 34,965
Sokoto Gada Tsitse 22,642
Sokoto Gada Dukamaje 17,057
Sokoto Gada Gada 35,546
Sokoto Gada Kadassaka 24,260
Sokoto Gada Kaddi 24,839
Sokoto Gada Kaffe 9,794
Sokoto Gada Kyadawa/Holai 39,326
Sokoto Gwadabawa Asara 40,300
Sokoto Gwadabawa Atakwanyo 22,975
Sokoto Gwadabawa Chimmola 35,395
Sokoto Gwadabawa Gidan Kaya 24,945
Sokoto Gwadabawa Gigane 53,400
Sokoto Gwadabawa Gwadabawa 42,460
Sokoto Gwadabawa Huchi 16,995
Sokoto Gwadabawa Mamman Suka 32,470
Sokoto Gwadabawa Mammande 59,065
Sokoto Gwadabawa Salame 63,280
Sokoto Gwadabawa Tambagarka 11,211
Sokoto Illela Araba 20,935
Sokoto Illela Darna Sabon Gari 21,260
Sokoto Illela Garu 12,798
Sokoto Illela Rungumawar 
Gatti 17,674
Sokoto Illela Tozai 15,855
Sokoto Illela Darna Tsolawo 45,191
Sokoto Illela Gidan Hamma 73,535
Sokoto Illela Gidan Katta 26,060
Sokoto Illela Damba 72,623
Sokoto Illela Kalmalo 27,500
Sokoto Illela Illela 35,960
STATE LGA WARD 2020 
POPULATION
Sokoto Kebbe Fakku 59,065
Sokoto Kebbe Girkau 32,325
Sokoto Kebbe Kebbe east 22,410
Sokoto Kebbe Kebbe west 18,790
Sokoto Kebbe Kuchi 31,635
Sokoto Kebbe Margai east 52,790
Sokoto Kebbe Margai west 19,892
Sokoto Kebbe Nasagudu 30,765
Sokoto Kebbe Sangi 25,150
Sokoto Kebbe Ungushi 19,690
Sokoto Kware Basansan 16,854
Sokoto Kware Durbawa 15,418
Sokoto Kware Gandu Modibbo 16,472
Sokoto Kware More Gidan 
Rugga 17,799
Sokoto Kware Sabon Birni 17,083
Sokoto Kware Bankanu 10,060
Sokoto Kware Hamma Ali 41,095
Sokoto Kware Kabanga 14,095
Sokoto Kware Kware 27,875
Sokoto Kware Tsaki-Walaka’e 26,363
Sokoto Kware Tunga￾Mallamawa
22,834
Sokoto Shagari Dandin/Mahe 32,040
Sokoto Shagari Horo 17,227
Sokoto Shagari Kambama 20,144
Sokoto Shagari Jaredi 19,033
Sokoto Shagari Lambara 26,279
Sokoto Shagari Kajiji 26,685
Sokoto Shagari Mandera 11,576
Sokoto Shagari Sanyin Lawal 29,510
Sokoto Shagari Shagari 21,357
Sokoto Shagari Gangam 18,307
Sokoto Wamakko Arkilla/Gwiwa 43,415
Sokoto Wamakko Bado/Kasarawa 15,965
Sokoto Wamakko Dundaye/
Gumburawa 24,607
Sokoto Wamakko Gidan Bubu 22,770
Sokoto Wamakko Gidan Hamidu 19,450
Sokoto Wamakko Gumbi/Wajake 16,755
Sokoto Wamakko Gwamatse 32,345
Sokoto Wamakko Kalambaina/
Girafshi 27,400
Sokoto Wamakko Kammata 21,431
Sokoto Wamakko Kaurar Gedawa 25,870
Sokoto Wamakko Wamakko 25,870
BR E A K THROUGH R ESE A RCH | M AY 2023 21 
STATE LGA WARD 2020 
POPULATION
Sokoto Wurno Achida 20,257
Sokoto Wurno Kwasare Sissawa 23,198
Sokoto Wurno Tunga 15,983
Sokoto Wurno Dinawa 24,428
Sokoto Wurno Magarya 25,387
Sokoto Wurno Chacho/Marnona 25,387
Sokoto Wurno Dimbiso 24,428
Sokoto Wurno Alkamu 20,390
Sokoto Wurno Kwargaba 14,911
Sokoto Wurno Lahodu 27,790
Sokoto Wurno Marafa 13,803
SOKOTO TOTAL 3,109,812
Zamfara Bakura Dankado 34,547
Zamfara Bakura Yargida 17,818
Zamfara Bakura Yarkofoji 39,358
Zamfara Bakura Rini 27,500
Zamfara Bakura Danmannau 32,050
Zamfara Bukkuyum Bukkuyum 30,074
Zamfara Bukkuyum Kyaram 60,802
Zamfara Bukkuyum Nasarawa 37,125
Zamfara Bukkuyum Yashi 18,704
Zamfara Bukkuyum Zarumai 28,292
Zamfara Bukkuyum Zauma 18,243
Zamfara Gunmi Magaji 54,839
Zamfara Gunmi Gayari 29,614
Zamfara Gunmi Gyalange 27,830
Zamfara Gunmi Birnin Magaji 23,220
Zamfara Gunmi Birnin Tudu 53,952
Zamfara Gunmi Falale 16,071
Zamfara Gusau Galadima 114,078
Zamfara Gusau Madawaki 48,781
Zamfara Gusau Mayana 78,542
Zamfara Gusau Sabon Gari 45,049
Zamfara Gusau Tudun Wada 150,936
Zamfara Gusau Wanke 48,385
Zamfara Maradun Dosara Birnin 
Kaya 40,209
Zamfara Maradun Faru Magami 70,316
Zamfara Maradun Goran Namaye 23,998
Zamfara Maradun Janbako 26,620
Zamfara Maradun Maradun North 31,544
Zamfara Maradun Maradun South 36,093
ZAMFARA TOTAL 1,264,590
22 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
TABLE A2 AGE-SPECIFIC POPULATION ESTIMATES FOR THE LIST APPLICATIONS
KEBBI SOKOTO ZAMFARA
MALE FEMALE MALE FEMALE MALE FEMALE
0 to 4 281,004 285,746 291,264 292,463 122,559 124,188
5 to 9 231,101 237,797 258,419 262,528 118,316 120,788
10 to 14 197,353 200,058 229,952 230,709 91,058 91,445
15 to 19 177,484 172,783 173,936 166,700 74,482 71,705
20 to 24 133,795 125,339 132,307 120,015 56,079 51,898
25 to 29 96,673 91,016 95,838 86,379 40,358 37,754
30 to 34 75,378 89,296 73,279 85,985 31,059 37,782
35 to 39 60,616 92,167 57,323 90,424 24,590 39,561
40 to 44 52,975 71,159 50,497 71,512 21,987 30,393
45 to 49 47,282 49,704 45,887 51,804 20,221 21,009
50 to 54 38,219 36,887 38,075 38,543 16,292 15,421
55 to 59 29,593 25,942 30,572 26,863 12,491 10,648
60 to 64 22,412 18,405 23,671 19,379 9,534 7,572
65 to 69 15,865 12,450 17,106 13,415 6,821 5,176
70 to 74 10,513 8,261 11,282 8,768 4,456 3,333
75 to 79 6,094 5,021 6,410 5,159 2,519 1,933
80+ 4,938 4,383 5,083 4,469 2,117 1,751
TOTAL 1,481,293 1,526,413 1,540,900 1,575,116 654,939 672,359
BR E A K THROUGH R ESE A RCH | M AY 2023 23 
APPENDIX B 
STATE-SPECIFIC RESULTS
While the primary objective of the cost-effectiveness 
analysis is to compare the results from the integrated 
states (Kebbi and Sokoto) to the malaria-only state 
(Zamfara), there are some additional interesting patterns 
to examine when looking at the individual state results. 
Using the scaled-up scenarios, the number of lives saved 
in each state is shown in Table B1. As discussed in the 
overall report, the are two primary drivers of the cost￾effectiveness results: 1) the loss of lives in the integrated 
states due to ITN coverage compared to gains in Zamfara 
and 2) the loss of lives in Zamfara due to reduced use of 
antibiotics for respiratory infections compared to gains in 
the integrated states. These results do not change when 
looking state-specific results, however, there are some 
interesting differences between Kebbi and Sokoto to 
consider. 
First, Kebbi shows a net 269 maternal lives saved in 
mothers, primarily due to improvements in modern 
contraceptive use and more facility-based births whereas 
Sokoto has a net loss of 54 lives. Zamfara results were 
more in line with Kebbi, seeing an overall gain of 219 
lives due to improvements in contraception and facility￾based birth. Facility-based birth results are also reflected 
among the child lives saved, showing 317 lives saved for 
Kebbi and 420 for Zamfara, but a loss of 4 lives in Sokoto. 
In contrast, Sokoto performed better for other outcomes, 
with many lives saved due to ACT use and ORS and zinc 
in Sokoto (429 and 536, respectively) but losses in Kebbi 
(-270, and -93, respectively). It is unclear to what extent 
these differences in commodities use are being driven by 
differential SBC successes in each state or rather external 
supply chain issues or program disruptions. 
On the cost side, Table B2 shows a detailed breakdown 
of the SBC expenditures per person living in the 
Breakthrough ACTION community SBC intervention areas 
for each of the study states. Among the study states, 
the highest expenditures occurred in the two integrated 
programs, Kebbi (US$8.1 million) and Sokoto (US$7.2 
million), while the stand-alone malaria SBC program in 
Zamfara spent approximately US$3 million. When adding 
the additional service delivery costs associated with 
improvements in health behaviors, the total program 
costs were $9.2m for Kebbi, $7.3m for Sokoto, and $3.4m 
for Zamfara. 
When combining the impact and costs to examine cost￾effectiveness, it is possible to make two comparisons: 
1) Kebbi vs. Zamfara and 2) Sokoto vs. Zamfara. Box B1
TABLE B1 NUMBER OF LIVES SAVED USING THE
 SCALED-UP SCENARIOS FROM
 BASELINE (2019) TO ENDLINE (2022)
INTEGRATED
MALARIA￾ONLY
KEBBI SOKOTO ZAMFARA
Maternal
Pregnancy 14 9 15
Childbirth 75 0 101
Contraception 180 -63 103
TOTAL maternal lives 
saved 269 -54 219
Child
Prenatal care 82 58 44
ITN coverage -1006 -625 403
Childbirth 317 -4 420
Breastfeeding -78 -187 -19
Vaccines (DPT and measles) 22 -19 25
ACT use -270 429 326
ORS and zinc for diarrhea -93 536 -726
Antibiotics for respiratory 
illness 1014 576 -1211
TOTAL child lives saved -12 764 -774
TOTAL maternal & child 
lives saved 257 710 -555
TABLE B2 ALL SBC EXPENDITURE PER PERSON
 REACHED IN ALL THREE STUDY
 STATES 
KEBBI
$
SOKOTO
$
ZAMFARA
$
SBC expenditures 8,117,297 7,208,211 2,984,448
Additional service 
delivery costs 1,103,633 89.251 425,864
TOTAL 9,220,929 7,297,462 3,410,312
24 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
shows the two separate cost per DALY averted estimates 
comparing the integrated state to the malaria-only state. 
Both results are far below the thresholds to be deemed 
highly cost-effective, using either the national threshold 
of $2,066 or the two-state average thresholds of $767 
for Kebbi/Zamfara and $980 for Sokoto/Zamfara. For the 
Kebbi vs. Zamfara comparison, the cost per DALY averted 
is $229.82, while the cost per DALY averted is even lower 
in the Sokoto vs. Zamfara comparison at $96.63.
Interestingly, both estimates are less than what is found 
when we combined Kebbi and Sokoto, which generates 
a cost per DALY averted of $278. Due to the differences￾in-differences approach, some of the gains in one state 
are cancelled out by the losses in another and thus 
the overall results are more favorable using a single 
integrated state as a comparison. 
Still, the primary conclusions, as well as study limitations, 
remain the same whether examining the relative cost￾effectiveness by state or analyzing them together as the 
“integrated program”, as originally proposed. Future 
work in this area can continue to explore these dynamics 
in cost-effectiveness studies.
BOX B1 COST PER DALY AVERTED FOR
 INTEGRATED VS. MALARIA-ONLY
 STATES
KEBBI VS. ZAMFARA
Maternal DALYs averted (Kebbi - Zamfara) 1,419
Child DALYs averted (Kebbi - Zamfara) 23,864
Additional impact for Kebbi 25,283
Additional costs for Kebbi $ 5,810,618.00
ICER = (Additional cost/Additional impact) $ 229.82
SOKOTO VS. ZAMFARA
Maternal DALYs averted (Sokoto - Zamfara) (7,881)
Child DALYs averted (Sokoto - Zamfara) 48,110
Additional impact for Sokoto 40,229
Additional costs for Sokoto $ 3,887,150.00
ICER = (Additional cost/Additional impact) $ 96.63
BR E A K THROUGH R ESE A RCH | M AY 2023 25 
APPENDIX C
FURTHER SBC EXPENDITURES DETAILS
SBC program implementation and personnel expenditure 
data were provided by Breakthrough ACTION for the 
three costing phases of the evaluation timeline as 
outlined in Figure 1: initial costing phase (April 2018 to 
December 2019); midline costing phase (January 2020 to 
December 2021); and the endline costing phase (January 
2022 to October 2022).
To calculate total SBC expenditures for each phase, 
we extracted all programmatic expenditures for each 
of the study states except for mass media. Program 
expenditures are comprised of all funding expended 
on the implementation of each program area including 
direct costs such as those for personnel, training, 
consulting services, supplies, travel, and indirect costs 
such as equipment and furniture, vehicles, maintenance, 
rent, utilities, management/oversight, and other 
overheads. Given the that the radio programming 
was conducted statewide while the cost-effectiveness 
analysis is focused on the Breakthrough RESEARCH 
intervention wards, we assessed a proportion of mass 
media expenditures based on the population living 
in the intervention areas for the study relative to the 
population of the entire state (Kebbi: 60.1%; Sokoto: 
53.1%; Zamfara: 25%). For example, in Kebbi, 60.1% of 
all expenditure on mass media programs were allocated 
based on the Breakthrough ACTION intervention wards 
for community SBC. The same principle was used for 
mass media expenditure in Sokoto and Zamfara. These 
state proportions of mass media expenditure were then 
added to all other SBC expenditures by state, resulting in 
total program expenditures by state. 
A similar approach was used to determine malaria￾only expenditures for each state. The SBC program 
expenditures focused on malaria for each of the 
study states were extracted from the expenditure 
data. Expenditures for the mass media component 
were treated in the same way as mass media for total 
SBC expenditures, i.e., using the proportion of the 
intervention area population to the population of the 
overall state to determine the share of mass media costs 
to apply in each state. These were then added to all other 
malaria SBC costs to arrive at malaria-only program costs 
by state.
Personnel expenditures for site-level and above-site 
(Abuja and organizational headquarters) and partners 
for each study state were extracted from the data for 
each costing period. For the initial reporting period 
(April 2018–December 2019) personnel expenditures 
are documented in the initial costing report.6
 Personnel 
expenditures for the midline and endline costing periods 
were estimated based on the proportions of total 
personnel expenditures borne by each state as provided 
in the Breakthrough ACTION expenditure data. The total 
site level and above-site level personnel and partner 
expenditures, for each state were added to the total 
SBC program implementation expenditures, to arrive 
at total program and personnel expenditures by state 
for each costing period. To determine the proportion 
of personnel and partner expenditures for the malaria￾only programming in each of the study states, it was 
first determined what proportion of total program 
implementation expenditures was made up of malaria￾only programming. This proportion was then used to 
allocate a percentage of total personnel and partner 
expenditures per state to malaria-only programming for 
each period. These expenditures were then added to the 
malaria-only program implementation expenditures to 
provide an estimate of total malaria-only program and 
personnel expenditures by state.
To add program design expenditures to the total 
expenditures for each study state, we extracted what 
was spent on program design in each of the years of 
the project. Program design expenditures were largely 
frontloaded, constituting a significant investment in 
the initial costing period, but then declining in the 
subsequent midline and endline periods. Expenditures 
made on program design have an impact over the 
lifetime of the project (anticipated end in 2025). 
Therefore, design expenditures made during the initial 
costing period were spread from 2018 through 2025. 
Similarly, design expenditures made over the midline and 
endline costing periods were spread from 2020 and 2022, 
respectively, to the end of the project. The investment 
26 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
made in program design was then added to the total SBC 
program and personnel expenditures already calculated 
for each of the study states. To estimate the design cost 
for the malaria-only program, the same approach used to 
derive personnel and partner costs was employed. Using 
the proportion of total program costs attributable to 
malaria-only programming, we allocated a percentage of 
total design costs per state to malaria-only programming 
for each period.
In addition to the SBC expenditures, there are service 
delivery costs associated with changes in the behavioral 
health outcomes. For example, increases in modern 
contraceptive prevalence will result in additional 
commodity costs. LiST contains a costing module with 
default values that estimate the total intervention 
costs associated with health behavior outcomes 
modeled in the scenarios.19 For each scenario, the 
total intervention costs relevant to the included health 
behavior outcomes were examined and the difference 
between the scaled-up scenarios and the limited 
scaled-up scenario were used to calculate the changes 
in service delivery costs associated with the changes in 
the outcome variables. These changes were added to 
the SBC expenditures to generate the total costs for each 
application. 
All expenditures on COVID-19, such as those for 
advocacy, community SBC, capacity strengthening, 
mass media, and operational costs, among others, were 
excluded from our analysis.
Finally, all costs were adjusted to 2022 US$ using the GDP 
deflator as published by the Federal Reserve Bank of St. 
Louis, on the FRED Economic Data website (https://fred.
stlouisfed.org/series/GDPDEF#).
Expenditure Analysis Results
The total cost for all SBC programming for the three 
evaluation periods, by component, in the three study 
states is shown in Figure C1.
Of the states included in the study, Kebbi had the 
highest expenditures over the three evaluation 
periods and, with only a stand-alone malaria program, 
Zamfara had the lowest expenditures overall. Program 
implementation expenditures as a proportion of total 
expenditures in each state was fairly consistent, making 
up 34% and 37% in Kebbi and Sokoto respectively, 
and around 21% in Zamfara. Interestingly, personnel 
expenditures were higher in Zamfara (39%) compared 
with either Kebbi (33%) or Sokoto (36%). Similarly, 
partner expenditures, which include both personnel 
and programmatic expenses, in Zamfara were 26% of 
total expenditures, which was significantly higher than 
in Kebbi, where partner expenditures were 14% of total 
costs or in Sokoto, where they were only 11%. Design 
expenditures were highest in Kebbi, comprising 20% of 
total expenditures, declining to only 15% of total costs in 
Sokoto and 14% in Zamfara.
Figure C2 displays malaria-only expenditures for each of 
the three study states disaggregated by cost component. 
Zamfara, with its stand-alone malaria program, had 
the highest expenditures for malaria-only SBC over the 
three evaluation periods; 1.5 times more than Kebbi 
and nearly three times more than Sokoto. Expenditures 
on design for all three states were very similar, ranging 
FIGURE C1 EXPENDITURES FOR ALL SBC
 PROGRAMMING BY STATE AND
 COMPONENT
Program Personnel Partner
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
$5,000,000
$6,000,000
$7,000,000
$8,000,000
$9,000,000
Kebbi Sokoto Zamfara
Design
BR E A K THROUGH R ESE A RCH | M AY 2023 27 
from 16% in Sokoto to 18% in Kebbi. Of the total malaria 
SBC expenditures, the allocation of the expenditures 
varied by state. In Sokoto only 7% of total malaria 
SBC expenditures were expended by partners, which 
increased to 13% in Kebbi and to over 30% in Zamfara. 
All other personnel costs consumed about a third of total 
expenditures in each of the three study states. 
Figure C3 examines the proportion of overall 
expenditures for malaria-only SBC programming 
versus all other SBC programming in the two states 
with integrated programs (Kebbi and Sokoto), and the 
stand-alone malaria program in Zamfara. The integrated 
program in Kebbi expended 83% of all resources on 
all other SBC programs with 17% going to malaria SBC. 
Sokoto was more skewed with just over 90% of all 
expenditure going towards all other SBC programs and 
only 10% going to malaria programs. In Zamfara there 
were only a few program implementation expenditures 
that were not malaria-related, such as small interventions 
for TB and GHSA. The bulk of all other non-malaria 
expenditures were program design and above-site 
personnel costs. 
FIGURE C2 EXPENDITURES FOR MALARIA-ONLY
 SBC PROGRAMMING BY STATE AND
 COMPONENT
Program Personnel Partner
$0
$500,000
$100000
$1,500,000
$2,000,000
$2,500,000
Kebbi Sokoto Zamfara
Design
FIGURE C3 PROPORTION OF ALL EXPENDITURE
 FOR MALARIA-ONLY AND ALL
 OTHER SBC PROGRAMMING BY
 STATE
Malaria only SBC All other SBC programs
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
$5,000,000
$6,000,000
$7,000,000
$8,000,000
$9,000,000
Kebbi Sokoto Zamfara
28 COST-EFFECTIVENESS ANALYSIS COMPARING SBC PROGRAMMING IN NIGERIA: FINAL REPORT
APPENDIX D
EXAMINING ICER WITH VARYING LEVELS OF IMPACT 
ATTRIBUTION
PERCENT IMPACT 
ATTRIBUTED TO 
SBC
COST PER DALY AVERTED
SCALED-UP LIMITED
1% $ 27,802 $ 42,605 
2% $ 13,901 $ 21,303 
3% $ 9,267 $ 14,202 
4% $ 6,951 $ 10,651 
5% $ 5,560 $ 8,521 
6% $ 4,634 $ 7,101 
7% $ 3,972 $ 6,086 
8% $ 3,475 $ 5,326 
9% $ 3,089 $ 4,734 
10% $ 2,780 $ 4,261 
11% $ 2,527 $ 3,873 
12% $ 2,317 $ 3,550 
13% $ 2,139 $ 3,277 
14% $ 1,986 $ 3,043 
15% $ 1,853 $ 2,840 
16% $ 1,738 $ 2,663 
17% $ 1,635 $ 2,506 
18% $ 1,545 $ 2,367 
19% $ 1,463 $ 2,242 
20% $ 1,390 $ 2,130 
21% $ 1,324 $ 2,029 
22% $ 1,264 $ 1,937 
23% $ 1,209 $ 1,852 
24% $ 1,158 $ 1,775 
25% $ 1,112 $ 1,704 
26% $ 1,069 $ 1,639 
27% $ 1,030 $ 1,578 
28% $ 993 $ 1,522 
29% $ 959 $ 1,469 
30% $ 927 $ 1,420 
31% $ 897 $ 1,374 
32% $ 869 $ 1,331 
33% $ 842 $ 1,291 
34% $ 818 $ 1,253 
35% $ 794 $ 1,217 
36% $ 772 $ 1,183 
37% $ 751 $ 1,151 
38% $ 732 $ 1,121 
PERCENT IMPACT 
ATTRIBUTED TO 
SBC
COST PER DALY AVERTED
SCALED-UP LIMITED
39% $ 713 $ 1,092 
40% $ 695 $ 1,065 
41% $ 678 $ 1,039 
42% $ 662 $ 1,014 
43% $ 647 $ 991 
44% $ 632 $ 968 
45% $ 618 $ 947 
46% $ 604 $ 926 
47% $ 592 $ 906 
48% $ 579 $ 888 
49% $ 567 $ 869 
50% $ 556 $ 852 
51% $ 545 $ 835 
52% $ 535 $ 819 
53% $ 525 $ 804 
54% $ 515 $ 789 
55% $ 505 $ 775 
56% $ 496 $ 761 
57% $ 488 $ 747 
58% $ 479 $ 735 
59% $ 471 $ 722 
60% $ 463 $ 710 
61% $ 456 $ 698 
62% $ 448 $ 687 
63% $ 441 $ 676 
64% $ 434 $ 666 
65% $ 428 $ 655 
66% $ 421 $ 646 
67% $ 415 $ 636 
68% $ 409 $ 627 
69% $ 403 $ 617 
70% $ 397 $ 609 
71% $ 392 $ 600 
72% $ 386 $ 592 
73% $ 381 $ 584 
74% $ 376 $ 576 
75% $ 371 $ 568 
76% $ 366 $ 561 
PERCENT IMPACT 
ATTRIBUTED TO 
SBC
COST PER DALY AVERTED
SCALED-UP LIMITED
77% $ 361 $ 553 
78% $ 356 $ 546 
79% $ 352 $ 539 
80% $ 348 $ 533 
81% $ 343 $ 526 
82% $ 339 $ 520 
83% $ 335 $ 513 
84% $ 331 $ 507 
85% $ 327 $ 501 
86% $ 323 $ 495 
87% $ 320 $ 490 
88% $ 316 $ 484 
89% $ 312 $ 479 
90% $ 309 $ 473 
91% $ 306 $ 468 
92% $ 302 $ 463 
93% $ 299 $ 458 
94% $ 296 $ 453 
95% $ 293 $ 448 
96% $ 290 $ 444 
97% $ 287 $ 439 
98% $ 284 $ 435 
99% $ 281 $ 430 
100% $ 278 $ 426 
BR E A K THROUGH R ESE A RCH | M AY 2023 29 
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