Assessing the use of geospatial data for immunization program implementation and associated effects on coverage and equity in the Democratic Republic of Congo

Abstract

Background
The National Expanded Program on Immunization in the Democratic Republic of the Congo implemented a program in 9 Provinces to generate georeferenced immunization microplans to strengthen the planning and implementation of vaccination services. The intervention aimed to improve identification and immunization of zero-dose children and overall immunization coverage.

Methods
This study applies a mixed-methods design including survey tools, in-depth interviews and direct observation to document the uptake, use, and acceptance of the immunization microplans developed with geospatial data in two intervention provinces and one control province from February to June 2023. A total of 113 health facilities in 98 Health Areas in 15 Health Zones in the three provinces were included in the study sample. Select providers received training on gender-intentional approaches for the collection and use of geospatial data which was evaluated through a targeted qualitative study. A secondary analysis of immunization coverage survey data (2020–2022) was conducted to assess the associated effects on immunization coverage, especially changes in rates of zero dose children, defined as those aged 12–23 months who have not received a single dose of Pentavalent vaccine.

Results
This research study shows that georeferenced microplans are well received, utilized, and led to changes in routine immunization service planning and delivery. In addition, the gender intervention is perceived to have led to changes in the approaches taken to overcome sociocultural gender norms and engage communities to reach as many children as possible, leveraging the ability of women to engage more effectively to support vaccination services. The quantitative analyses showed that georeferenced microplans may have contributed to a dramatic and sustained trend of high immunization coverage in the intervention site of Haut-Lomami, which saw dramatic improvement in coverage for 3 antigens and little change in Pentavalent drop-out rate over three years of implementation.

Conclusion
The overall study identified positive contributions of the georeferenced data in the planning and delivery of routine immunization services. It is recommended to conduct further analyses in Kasai in 2024 and 2025 to evaluate the longer-term effects of the gender intervention on immunization coverage and equity outcomes.

Trial registration
The study was registered and given BMC Central International Standard. Randomised Controlled Trial Number ISRCTN65876428 on March 11, 2021.

Full text

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Ngo-Bebe et al. BMC Public Health (2025) 25:311
https://doi.org/10.1186/s12889-025-21578-x BMC Public Health
*Correspondence:
Patricia Mechael
patty@healthenabled.org
Full list of author information is available at the end of the article
Abstract
Background The National Expanded Program on Immunization in the Democratic Republic of the Congo
implemented a program in 9 Provinces to generate georeferenced immunization microplans to strengthen the
planning and implementation of vaccination services. The intervention aimed to improve identication and
immunization of zero-dose children and overall immunization coverage.
Methods This study applies a mixed-methods design including survey tools, in-depth interviews and direct
observation to document the uptake, use, and acceptance of the immunization microplans developed with
geospatial data in two intervention provinces and one control province from February to June 2023. A total of 113
health facilities in 98 Health Areas in 15 Health Zones in the three provinces were included in the study sample. Select
providers received training on gender-intentional approaches for the collection and use of geospatial data which was
evaluated through a targeted qualitative study. A secondary analysis of immunization coverage survey data (2020–
2022) was conducted to assess the associated eects on immunization coverage, especially changes in rates of zero
dose children, dened as those aged 12–23 months who have not received a single dose of Pentavalent vaccine.
Results This research study shows that georeferenced microplans are well received, utilized, and led to changes
in routine immunization service planning and delivery. In addition, the gender intervention is perceived to have
led to changes in the approaches taken to overcome sociocultural gender norms and engage communities
to reach as many children as possible, leveraging the ability of women to engage more eectively to support
vaccination services. The quantitative analyses showed that georeferenced microplans may have contributed to a
dramatic and sustained trend of high immunization coverage in the intervention site of Haut-Lomami, which saw
dramatic improvement in coverage for 3 antigens and little change in Pentavalent drop-out rate over three years of
implementation.
Assessing the use of geospatial data
for immunization program implementation
and associated eects on coverage and equity
in the Democratic Republic of Congo
DosithéeNgo-Bebe1, PatriciaMechael2,3*, Fulbert NappaKwilu1, Théophane KekembBukele1, FélicitéLangwana4,
Genèse LolimoLobukulu1, Marcelo IlungaKalonji1, BahindwaKalalizi2, KevinTschirhart5, Christophe LungayoLuhata6
and CarineGachen7
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Page 2 of 14
Ngo-Bebe et al. BMC Public Health (2025) 25:311
Background
e World Health Organization (WHO) Global Vaccine
Action Plan (2011–2020) was developed to help all indi-
viduals and communities enjoy lives free from vaccine-
preventable diseases, demonstrating that the benets of
immunization are equitably extended to all people, wher-
ever they are located [1]. Gavi, the Vaccine Alliance’s
5.0 Strategy 2021–2025 and the Global Immunization
Agenda 2030 [2, 3] promote the use of geospatial data
and technology applications for immunization programs
to reach all children, especially unvaccinated children
referred to as “zero-dose”.
In the Democratic Republic of the Congo (DRC), the
Mashako Plan is a unique, high-level national health
strategy that aims to drastically increase complete child-
hood immunization coverage at a national level [4]. e
integration of geospatial tools, technologies and data for
planning and delivery of immunization services supports
the Mashako Plan through a participatory process to
create geospatially accurate maps of settlements, dene
health area boundaries and generate improved popula-
tion estimates. e integration of these geospatial tools
and technologies into immunization programs has dem-
onstrated potential to enhance immunization coverage
and equity [5] and address persistent challenges of data
quality, inated reports of coverage rates and inaccurate
denominators [6, 7]. e use of geospatial data, geospa-
tial tools and technologies for immunization program-
ming in the DRC was intended to address some of these
challenges and to support the immunization program
to accurately monitor immunization coverage and plan
upcoming vaccination activities.
Description of the intervention
e Mapping for Health (M4H) project aimed to
strengthen the equity and eectiveness of vaccination
interventions in the DRC, increase national geospatial
capacities and promote gender-intentional program-
ming through the provision of geo-enabled microplans
within the National Expanded Program on Immunization
(NEPI). e project has been implemented by the Min-
istry of Health with support from the Geo-Referenced
Infrastructure and Demographic Data for Development
(GRID3) Consortium since 2019.
To improve the eectiveness of immunization micro-
plans, the GRID3 Consortium supported the National
Immunization Program activities to promote gender-
intentional planning and to generate geospatial data and
population modeling to determine the target population
(denominator) and produce core geospatial data lay-
ers: settlements, health boundaries, and health facili-
ties. ese data were then used to optimize vaccination
strategies in Health Zones in the form of geo-enabled
microplans.
While gender equity in the delivery of vaccines is of
critical importance, gender also plays a role in relation-
ships between health workers and supervisors, digital
literacy, division of labor, data use, decision-making and
leadership within the health system [8]. e cultural con-
texts and gendered barriers among health providers and
the communities they serve can impact the adoption,
access and use of digital technologies that are intended
to improve immunization outcomes. For this reason,
the M4H intervention included a gender audit, a series
of gender trainings to strengthen stakeholder capacity
to understand and apply gender-intentional principles
in program design and implementation, multi-sectoral
stakeholder engagements and a gender-based analysis
tool. In collaboration with the Ministry of Gender and
Social Aairs these gender interventions promoted
strategies to engage more women in the process of gen-
erating and utilizing geospatial data and to apply gender-
responsive strategies to immunization program planning
and service delivery using the geo-enabled microplans.
ese activities were carried out in one study Province
(Kasai) in targeted Health Zones and Health Areas where
the gender intervention was evaluated separately using a
rapid ethnographic sub-study.
To evaluate the adoption and use of geo-enabled
microplans and the complementary gender interven-
tion in a sub-set of sites, Gavi, the Vaccine Alliance
engaged health.enabled through the “Eective Design,
Implementation, Integration, and Evaluation of Digital
Health Systems to Enhance the Strategic Use of Data for
Immunization Programming” to assess immunization
Conclusion The overall study identied positive contributions of the georeferenced data in the planning and
delivery of routine immunization services. It is recommended to conduct further analyses in Kasai in 2024 and 2025 to
evaluate the longer-term eects of the gender intervention on immunization coverage and equity outcomes.
Trial registration The study was registered and given BMC Central International Standard. Randomised Controlled
Trial Number ISRCTN65876428 on March 11, 2021.
Keywords Geospatial data, Mapping for health, Immunization coverage, Vaccine coverage survey, Immunization
equity, Democratic republic of the congo, Expanded program for immunization, Routine immunization, Zero dose,
Microplanning
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
service providers’ acceptance and use of geospatial data
for microplanning and routine immunization service
delivery and associated eects on the vaccine coverage in
DRC.
e generation of core geospatial layers is intended to
provide key and timely insights for Health Zone and Pro-
vincial decision-makers to identify hard-to-reach settle-
ments or settlements likely to fall in between two health
catchment areas; estimate the population of the health
areas and health zones; estimate a healthcare facility’s
catchment population; estimate the number of vaccines
needed for a health area based on its population; assess
the population coverage of current xed vaccination
strategies; optimize outreach vaccination strategies based
on population distribution; and optimize the cold chain
and new refrigerator allocation based on population dis-
tribution. e theory of change for M4H describes how
the systematic generation and use of geospatial data and
associated population distribution, including the identi-
cation of previously missed settlements, contributes to
more eective immunization program planning and ser-
vice delivery, which contributes to improved immuniza-
tion coverage and equity. is theory of change was used
to inform the development of the qualitative instruments
(observation and interview guides developed by the
research team), the intervention strength survey instru-
ments, and the secondary analyses of immunisation cov-
erage survey data.
Methods
is is a mixed-methods study with a quasi-experimental
design focusing on the adoption, perceptions, and use of
geospatial data for microplanning and routine immuniza-
tion service delivery, and subsequent impact on vaccina-
tion coverage. Impact was assessed using a pre/post study
design which draws upon the NEPI Vaccine Coverage
Surveys (VCS) conducted in 2021 (for 2020 pre-interven-
tion data), and repeated in 2023 (for 2021 and 2022 data);
all surveys focus on children age 6–11 months and 12–23
months [9]. Eorts to assess impact were informed and
complemented by qualitative research (direct observa-
tions and in-depth interviews) and intervention strength
surveys in prioritized Health Areas in intervention and
control sites to assess adherence to microplans with
and without georeferenced data. A targeted rapid eth-
nographic study was conducted in Health Zones and
Health Areas in Kasai which were exposed to gender-
specic program activities. ese sites were purposefully
included in the intervention strength survey sample. e
intervention strength survey and interview guides were
developed in French by the research team and have been
included as Supplementary Material.
e qualitative approach focused on interviews with
various participants, including the Provincial Head of
Division, NEPI branch Medical Chief, NEPI branch
Data Managers, and the Analysts in charge of the health
information to the Provincial Division, NEPI Monitoring
and Evaluation Service Chief, and the person in charge
of mapping in the National Health Information System
(NHIS) Oce at the central level. Interview guides were
designed to facilitate the interviews with key informants.
In addition, a comparative descriptive analysis was
performed to determine whether the use of geo-enabled
microplans in Haut-Lomami is associated with signi-
cant dierences in the percentage of zero-dose children
aged 12–23 months post-intervention in the poorest and
poorest economic strata between 2020 and 2021.
Setting
e study took place in 3 Provinces, namely Kasai (inter-
vention site with gender component), Haut Lomami
(intervention site without gender component), and Kasai
Central (control site) illustrated in the Fig.1 map. Priori-
tized survey sites included Health Zones that represent
urban and remote areas. Our sample size was 113 health
facilities in 98 Health Areas in 15 Health Zones in the
three provinces as illustrated in Fig.2.
For the sampling, we considered 30% of the total num-
ber of Health Zones for each stratum. To do this, we
carried out simple random sampling using the Android
application, “Randomizer”. e same approach was used
to select30% of the total number of Health Areas for each
Health Zone. In the control Province, we used the same
sampling method to select 15% of the total number of
Health Areas for each stratum and 15% of the total num-
ber of Health Areas for each Health Zone.
Data collection
Data collection at Provincial and Health Zone levels took
place from February to June 2023. e process involved
in-depth interviews conducted in French and audio
recorded and transcribed for qualitative analysis. e
focus of these interviews was on the acceptance and use
of geo-enabled microplans for immunization planning.
A total of 19 in-depth interviews were conducted. Before
each interview, the interviewers presented the objectives
of the evaluation to the participants. Individual writ-
ten informed consent was required and obtained from
each respondent to participate in the study. Interviewers
made appointments with each respondent, according to
availability.
At Health Area and health facility levels, data collection
techniques included: (1) a structured survey; (2) direct
observation of maps and georeferenced microplans; (3)
document review; and (4) semi-structured interviews
with key informants. Quality control was carried out on
an ongoing basis, at various stages of the study.
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
Fig. 2 Representation of the Sampling of Heath Areas. *HZ: health zone, HA: health area
Fig. 1 Map of the Democratic Republic of the Congo showing intervention, study and control Provinces
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Prior to the data collection
Interviewers with previous research experience were
recruited among Kinshasa School of Public Health
(KSPH) alumni (MPH degree) to guarantee data qual-
ity. e selection was based on their experience with this
type of survey and on their availability for the period of
this study. A two-day training was organized by province
supervisors (academic assistants at the KSPH) focusing
on the overall protocol of the study, its objectives, ethics
measures to take into consideration, data collection using
the Computer Assisted Personal Interview system, and
adherence to dierent instruments. e questionnaire
was digitized using SurveyCTO with automatic lters,
constraints, and relevance criteria for certain questions
to control data entry.
During and after data collection
e supervisor developed a follow-up plan for the eld
teams to ensure that the interviewers were in the vari-
ous assignment zones. A supervision form was com-
pleted to report on eld progress, including the number
of interviews completed as well as any problems encoun-
tered in the eld. All teams were linked by a WhatsApp
group for rapid sharing of information in the eld. Auto-
matic checks of completed and sent questionnaires were
carried out by the coordinator in charge of data pro-
cessing and analysis. When necessary, the provincial
supervisor was alerted to take corrective action. Data
editing was carried out during data collection to ensure
data quality, notably by searching for “I don’t know” or
“refusal” responses and by cleaning the database prior to
the analysis.
Data analysis
e content of the in-depth interviews and open-ended
survey questions was analyzed using ATLAS TI software.
rough an inductive and iterative process, we used
content analysis methods based on thematic codes and
sub-codes. e initial list of codes was derived from the
themes and questions contained in the interview guides.
All transcripts were coded using the coding list. We
looked for subgroups to highlight specic experiences
and the reasons for those experiences.
e intervention strength survey data collected by the
interviewers was transferred to the server after veri-
cation by the eld supervisor. Secondary data cleaning
was carried out using Survey CTO software. Data analy-
sis was performed using SPSS Version 25 software. e
data were analyzed to produce expected frequencies for
categorical variables and continuous variables as well as
the measure of central tendency (mean or median) and
dispersion (standard deviation or interquartile range)
according to the normality of the distribution. e Chi-
square test was used to test for association, with an alpha
of 0.05.
To assess the coverage and equity study objectives, sec-
ondary analyses of immunization coverage and equity
survey data were conducted. e data extracted from
the dierent VCS reports by the KSPH covered Haut-
Lomami, Kasai, and Kasai Central. e extraction of the
data was done manually. e variable measured was the
percentage of children age 12–23 months who have not
received any dose of Pentavalent vaccine to represent
zero-dose prevalence or unvaccinated children. Addi-
tional quantitative analyses were carried out to further
assess drop-out rates.
Results
Our ndings are presented by study aims and objectives
beginning with the socio-demographic characteristic of
the interviewees (Table1).
Most respondents were male (88%). e most com-
mon age group in all three provinces is 35–49 years age
old with a total of 48% of all respondents interviewed.
More than three out of four respondents had a higher or
Table 1 Socio-demographic characteristics of participants in the
3 provinces
Haut-Lomami Kasai Kasai
Central
To-
gether
n = 46 (%) n = 49
(%)
n = 16 (%) n = 111
(%)
Sex
Male 39 (85) 43 (88) 16 (100) 98 (88)
Female 7 (15) 6 (12) 0 (0) 13 (12)
Total 46 (100) 49 (100) 16 (100) 111
(100)
Age range
< 25 years 1 (1) 0 (0) 0 (0) 1 (1)
25–34 15 (33) 5 (10) 5 (31) 25 (23)
35–49 18 (39) 26 (53) 9 (56) 53 (48)
≥ 50 12 (26) 18 37) 2 (13) 32 (29)
Total 46 (100) 49 (100) 16 (100) 111
(100)
Level of Study
Secondary 13 (28) 15 (31) 4 (25) 32 (29)
Higher or
University
33 (72) 34 (69) 12 (75) 79 (71)
Total 46(100) 46(100) 16 (100) 111(100)
Function
IT (Head Nurse of
Health center
17 (37) 44 (90) 8 (50) 69 (62)
IS (Health Zone
Nurse supervi-
sor in charge of
immunization)
3 (7) 3 (6) 3 (19) 9 (8)
MCZ 0 (0) 1 (2) 0 (0) 1 (1)
Other 26 (57) 1 (2) 5 (31) 32 (29)
Total 46 (100) 49 (100) 16 (100) 111
(100)
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
university degree. ree-fths of respondents assumed
the role of Head Nurse of Health center (62%), except in
the Province of Haut-Lomami where slightly more than
half were in other roles (57%).
Study Aim 1: program implementation context and
mechanisms
Process through which geospatial data was created
Participation or contribution in the process e
majority of study participants were not involved in the
development of the design of the intervention. Dierences
in the engagement of the various stakeholders emerged,
i.e., at the central level, not all the Ministry stakehold-
ers had the same degree of participation or contribution
to the intervention. At the provincial level, participa-
tion was in the planning and implementation phase. e
interviewees noted that the intervention’s objectives took
account of the gender aspect from the point of view of the
service providers and concrete implementation, as in the
identication of vaccinated children by sex and age. For
the equity aspects, they considered all social strata. e
design of the georeferenced and gender data set-up was
perceived to contribute to eective identication of where
the targets are and informed the mechanisms to reach and
vaccinate them according to NEPI guidelines. e project
was also credited with resolving the problem of imprecise
Health Area and Health Zone boundaries, as well as the
location of populations overlooked during vaccination
activities.
A content analysis by respondent category according to
health system levels revealed a dierence in perception of
the gender and inclusion aspect. At the central level, the
gender intervention was clearly known, and the various
stakeholders recognized this dimension in the interven-
tion and also contributed to it in the training aspects of
the eld teams. At the provincial level, the gender and
social inclusion dimension was perceived dierently by
the various stakeholders.
Respondents conrmed that the community had taken
part in the process through the community animation
cells (CACs) with the agreement of the local author-
ity, applying the principle that “whatever you do with-
out me, you do against me”. e Head Nurse of Health
Areas organized brieng meetings to enlighten commu-
nity members on the merits of mapping data. However,
the community was perceived as both a barrier and an
enabler. e result was mistrust on the part of the pop-
ulation in some communities, which were not accus-
tomed to seeing sophisticated technological devices. In
some Health Zones, the local population believed that
they were being expropriated from their land, requiring
repeated explanations despite prior authorization of the
village chief. In some cases, the community resisted the
activities outright.
As described by one of the respondents, “In terms of
ease of use, it’s the community that knows the boundar-
ies…. From a social point of view, you had to see the chief,
because when you say, for example, “Where does your vil-
lage end?” he’s the one who should say, “My land goes as
far as here”. In terms of barriers, when we see an activity
where we have to use fairly technological equipment, we
wonder what the purpose is and that’s the barrier or reti-
cence that we could feel.” (Head Nurse, Kasai).
e contribution of the community extended to the
feedback it provided for the validation of mapping data
collected, even if community leaders (CAC) are still
expecting to receive updated maps with corrected infor-
mation, where needed. With regard to gender, the main
reection of key informants was that Health Zone man-
agement teams take into account the gender dimension
in the current immunization register, where vaccinated
children are well identied by age and sex.
Mapping acceptance, challenges, and prospects e
mapping was well accepted by various stakeholders.
Positive aspects include the production of better-quality
maps, enabling more accurate location of sites compared
with the old handwritten maps along with the production
of more accurate population estimates and population
densities, enabling better planning of vaccination activi-
ties. Negative aspects were related to the imperfection of
the maps, which had some omissions or inaccuracies of
specic customary landmarks. For certain Health Zones,
some Health Areas had almost disappeared, for which the
respondents wanted the maps to be updated.
On the optimal future for the mapping, one respondent
commented: “It’s a promising future, but it’s only the rst
step. I think that these will be dynamic maps that can be
updated as we go along…. So, the project will have to see
how to establish a certain periodicity for updating these
maps”. (NEPI branch oce, Haut-Lomami).
Process through which project georeferenced data is shared
for use in microplanning
Many of the respondents have worked for more than
10 years, directly or indirectly, in the microplanning of
routine immunization activities using a paper-based
microplanning process. ey are therefore experienced
resources in this eld, from the Head Nurses and the
community (community relays, community animation
cells and health development committees) who took
an active part in the microplanning of their respective
Health Areas and transmission to Health Zone central
oce level.
e following considerations were perceived as facili-
tators for the use of geospatial data for microplanning
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
and routine immunization: the existence of a legend
that makes it easy to read a map; attraction to technol-
ogy; transition from analogue to digital; the desire to do
things dierently and better; users were involved in the
process; user support; buy-in and use of the tool by the
service provider.
For some Health Zones, the following were perceived
as obstacles: the problem of connecting to the Internet;
lack of knowledge of the tool; lack of training; unavail-
ability of logistical and nancial resources; most of the
tools used in vaccination are paper-based; most of the
tools are intended for people who are not too literate in
terms of technology; technological tools require a sub-
stantial investment; old habits; other logistical, nancial
and economic constraints in implementation.
Process through which geospatial data is used as part of
microplanning processes
All Health Zones as well as all Health Areas surveyed in
the Kasai Province (49/49 health facilities) received the
georeferenced data. Almost the entire Haut-Lomami
Province, 98% (45/46), received the georeferenced data;
no georeferenced tools were received in Kasai Central
Province (16/16), which is the control Province. At the
time of the study, dierent maps generated by the proj-
ect were observed by the research team to be taped to the
oce walls of almost all (98%; 48/49) of the health facili-
ties investigated in the Kasai Province and 70% (32/46)
of the walls of the Haut-Lomami Province. Unanimously,
respondents mentioned their satisfaction and armed
that the maps were an important addition in general and
that their use in vaccination activities made it possible to
improve their knowledge and acquire more information
on the respective entities. is also made it possible to
resolve conicts over the delimitation of the geographical
boundaries of the Health Areas, since in some cases, the
limits dened on these tools did not reect the reality on
the ground.
Overall, microplanning tools are displayed by the
Health Area Head Nurses in 83% of the health facili-
ties visited: respectively 89% (41/46) and 86% (42/49) in
the two provinces of intervention of Haut-Lomami and
Kasai, and 63% (10/16) in the control province of Kasai
Central. Almost all microplanning tools (98%) were in
paper format. e microplanning tool is accessible in
most cases to full-time nurses in 88% and to other nurses
in 39% of the health facilities visited.
In the two intervention Provinces, the main users of
the microplanning tool are the health center nurses in
92% of cases compared to 75% in the control Province.
Before the introduction of georeferenced data, half of
the health facilities in Haut-Lomami used data from the
NEPI Program (51%) when developing their microplans,
while more than four-fths of Kasai Province (86%) and
half of Kasai Central health facilities (50%) respondents
reported using routine data.
In the two intervention Provinces, 84% of health facili-
ties are now using the georeferenced estimates of the tar-
get population, its distribution by site or location (78%),
the identication of the sites of vaccination (76%), the
identication of vaccination sites for optimizing vaccina-
tion strategies, i.e., outreach strategy (63%) and the iden-
tication of new villages (62%), as presented in Table2.
According to the qualitative analyses, respondents,
particularly at the Health Zone and provincial levels,
indicated that support for vaccination activities has sig-
nicantly improved with the introduction of geospatial
data. Apart from the numbers of the target populations
which experienced variation in the direction of increase
(Kasai Province) or decrease (Haut Lomami Province),
other data from the Health Areas in terms of the number
of settlements, xed or advanced sites, neighborhoods
remained almost the same before and after of the intro-
duction of geospatial data.
Process through which geospatial data is used as part of
routine immunization programme implementation
Almost all (94%) of health facilities in the intervention
provinces use geospatial data for routine immunization
programme implementation in their Health Areas. is
use is more pronounced in the Haut-Lomami Province
(96%) compared to that of Kasai (92%).
e interviews unanimously emphasized that geore-
ferenced data was important in the planning process.
ey made it possible to improve information relating to
the dierent vaccination strategies (e.g. xed, outreach,
mobile), the number of vaccines to order, the availability
and location of refrigerators, and the size of the popula-
tion to be covered in the context of vaccination activities.
A small group of respondents reported that the use of
geospatial data made it possible to improve distribution
in terms of the number of vaccines to be requisitioned
according to consumption.
Most respondents (69%) declared that the geospa-
tial enabled tools are very easy to use. More than three
quarters are at least satised with the information con-
tained in the tool and its use in activity planning. Most
respondents agreed that the geospatial tool has reduced
their working time and improved data quality, as shown
in Table3.
According to the qualitative results, respondents unan-
imously stated that the tool had more advantages than
disadvantages. One of the most signicant benets men-
tioned by respondents is reaching zero-dose children in
each Health Area. At the provincial level, the tool helped
improve the planning, implementation, and supervision
of vaccination activities.
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
Acceptance and perceptions of gender intervention with
geospatial data use in Kasai
Interviews with all gender training participants (14/14)
in the targeted Health Zones in Kasai Province revealed
that this was a good training course focusing on gender
considerations. Field teams are now starting to disaggre-
gate data in terms of gender and increase women’s partic-
ipation as vaccinators. Knowledge of vaccination teams
has improved, and gender principles were included in
vaccination activities and complimented the geo-enabled
microplans for better immunization coverage.
Most of the community members who took part in
this study recognized that the gender training helped
them to solve problems linked to inequality and dis-
crimination between men and women in the commu-
nity, starting with immunization but also more generally.
All the participants in the interviews recognized that
now, some women are involved in vaccination activities
in the community. As noted by a participant: “I too nd
that gender or parity has helped a lot, even at the level
of vaccination teams. Back then, it was mainly men who
went around vaccinating children in the Health Area.
Now, we also see women giving vaccines, this has brought
about a change in the community”. (Gender intervention
respondent).
However, the ratio of women to men in the health sys-
tem is still low, and many participants felt that all the
authorities should enhance women’s capacities and skills,
as they are able to contribute to strengthened immuniza-
tion services in the community. A key informant noted,
“In our Health Zone, there is no female managing the
CODESA [Comité de Développement de l’Aire de Santé /
Health Area Development Committee]. All the twenty-
eight are men. So, we’ve made a plea to our partners to
help us revitalize the CODESAs, to see where there are
Table 2 Distribution of microplan users and reported georeferenced data and uses
Haut-Lomami Kasai Kasai Central Together
Num (%) Num (%) Num (%) Num (%)
Microplan Users
IT (Head nurse of Health center) 41(91.1) 45(91.8) 12(75.0) 98(89.1)
Male nurse 23(51.1) 15(30.6) 1(6.3) 39(35.5)
RECO (community relay) 14(31.1) 11(22.4) 1(6.3) 26(23.6)
Others 2(4.4) 17(34.7) 2(12.50) 21(19.1)
IS (Supervisor Nurse in the Health zone in charge of immunization) 5(11.1) 5(10.2) 6(37.5) 16(14.5)
MCZ (Health Zone Chief medical doctor) 4(8.9) 3(6.1) 3(18.8) 10(9.1)
What was the source of information before Georeferenced data?
Routine data * 18(40.0) 42(85.7) 8(50.0) 68(61.8)
National EPI ** 23(51.1) 2(4.1) 6(37.5) 31(28.2)
Other (s) to be specied 4(8.9) 5(10.2) 2(12.5) 11(10.0)
Type of georeferenced data included in the tools
Target population (new denominator) 38(84.4) 43(87.8) N / A 81(84.5)
Distribution of the target population by site or location (number) 34(75.6) 43(87.8) N / A 77(77.3)
Identication of vaccination sites 34(75.6) 34(69.4) N / A 68(72.7)
New villages, neighborhoods, hamlets and/or camps identied (on the map) 34(75.6) 32(65.3) N / A 66(69.1)
Identication of outreach strategy vaccination sites 30(66.7) 32(65.3) N / A 62(64.5)
Other (s) to be specied 8(17.8) 13(26.5) N / A 21(20.9)
Seasonal movement of the target population 11(24.4) 6(12.2) N / A 17(16.4)
What planning need is solved with Georeferenced Tools?
Location of the target population 39(86.7) 45(91.8) N / A 84(89.4)
Number of doses to plan 26(57.8) 37(75.5) N / A 63(67.0)
Reliable denominator 20(44.4) 18(36.7) N / A 38(40.0)
Others 7(15.6) 11(22.4) N / A 18(19.1)
Georeferenced data actually used as reported by microplan users
Target population 37(82.2) 42(85.7) N / A 79(84.0)
Distribution of the target population by site or location 32(71.1) 41(83.7) N / A 73(77.7)
Identication of vaccination sites 35(77.8) 36(73.5) N / A 71(75.5)
Identication of outreach strategy vaccination sites 32(71.1) 27(55.1) N / A 59(62.8)
Identication of villages, neighbourhoods, hamlets, camps (mapping) 31(68.9) 27(55.1) N / A 58(61.7)
Seasonal movement of the target population 2(4.4) 10(20.4) N / A 12(12.8)
Others 4(8.9) 3(6.1) N / A 7(7.4)
Legend: * Ro utine data: Data collec ted at local level by the he alth zone; ** Population es timates data provided by t he NEPI at central level
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
shortcomings so that we can get back on track with compe-
tent women”. (Gender intervention respondent).
How does gender aect health workers’ use of mapping
and georeferenced data?
Most respondents acknowledged that this focus on
gender has enabled them to put into practice this new
strategy involving women and men in microplanning,
awareness-raising, and mobilizing mothers for immuni-
zation. ey also noted that complementarity between
women and men is essential to reach zero-dose children
and children lost to follow-up or incompletely vaccinated
children in the community.
For the gender distribution in training on the produc-
tion of spatial maps and estimates of vaccination target
populations, interviews revealed that in each Health
Zone, there were a total of twenty (20) people, fteen (15)
women, and ve (5) men. It was clear that all the women
had carried out the process of capturing data with geo-
spatial tools, so that they could have the matrix to dem-
onstrate to the other members of their community.
However, respondents noted that service delivery is
impacted by deep-rooted social and cultural norms con-
cerning the roles and responsibilities of men and women,
constituting challenges, obstacles or barriers to immuni-
zation which can aect both caregivers and health work-
ers, and negatively inuence the provision, demand and
use of immunization services.
Geospatial data use with a gender lens
Regarding the impact of gender on health workers’
immunization planning and conduct of routine immu-
nization activities, most of the respondents revealed that
today, immunization campaigns are prepared using tele-
phones, which means that health workers have a very
good grasp of the boundaries of their Health Areas, as
well as the targets to be immunized in the Health Area.
ey noted that the representation of men and women
facilitated the participation and complementarity of all
health workers in all upstream and downstream activi-
ties to achieve good results. One participant pointed
out that “in terms of vaccination, for example, you’ll nd
that when a woman administers the vaccine, people are
so happy. So, there are always positive inuences”. (Gender
intervention respondent).
e gender-intentional training as part of the geore-
ferenced microplan development process has contrib-
uted to re-evaluating the composition of vaccination
teams, namely the CODESA and CAC teams, supporting
women to achieve good results to reach and vaccinate
all the children expected. To this end, most respondents
indicated that all providers (women and men) work
together to achieve targets.
Study Aim 2: associated eects of the acceptance and use
of georeferenced data by health zones and health areas on
immunization coverage and equity
For the second study aim, a quasi-experimental design
study in the three provinces was used to determine the
associated eects of the acceptance and use of geospatial
data on immunization coverage and equity. e second-
ary data analyses were based on data from the immu-
nization coverage and equity surveys of children 12–23
months of age.
Table 3 Distribution of participants according to satisfaction
with informational content and use of georeferenced tool
Haut-Lomami Kasai Kasai
Central
Together
n= (%) n= (%) n= (%) n= (%)
Is the tool easy to use
Easy to use 34 (75.6) 31(63.3) N / A 65 (69.1)
Very easy 5 (11.1) 13 (26.5) N / A 18 (19.1)
Not easy to
use
4 (8.9) 5(10.2) N / A 9 (9.6)
Easy enough 2 (4.4) 0(0.0) N / A 2 (2.1)
Are you satised with the information contained in the georefer-
enced microplanning tool?
Satised 26 (57.8) 33(67.3) N / A 59 (62.8)
Very satised 13(28.9) 11(22.4) N / A 24 (25.5)
Somewhat
satised
3 (6.7) 5(10.2) N / A 8 (8.5)
Unsatised 3 (6.7) 0(0.0) N / A 3 (3.2)
Are you satised with using this tool?
Satised 26 (57.8) 33(67.3) N / A 59 (62.8)
Very satised 13(28.9) 12 (24.5) N / A 25(26.6)
Somewhat
satised
5 (11.1) 3 (6.1) N / A 8 (8.5)
Unsatised 1 (2.2) 1 (2.0) N / A 2 (2.1)
The reason for not being satised with the information contained
in the microplan
Too long 3 (100) 0(0.0) N / A 3 (100)
Dicult to
use
3 (100) 0(0.0) N / A 3 (100)
Contribution of microplanning tool in reducing working time
All right 22 (48.9) 26(53.1) N / A 48 (51.1)
Totally agree 10 (22.2) 17(34.70) N / A 27(28.7)
Disagree 7 (15.6) 2(4.1) N / A 9 (9.6)
Fairly agree 6 (13.3) 3 (6.1) N / A 9 (9.6)
not agree
at all
0(0.0) 1 (2.0) N / A 1 (1.1)
Will the microplanning tool improve the quality of your data
All right 30 (66.7) 31(63.3) N / A 61 (64.9)
Totally agree 10 (22.2) 13(26.5) N / A 23 (24.5)
Fairly agree 3 (6.7) 2(4.1) N / A 5 (5.3)
Disagree 1 (2.2) 3(6.1) N / A 4 (4.3)
not agree
at all
1 (2.2) 0(0.0) N / A 1 (1.1)
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Ngo-Bebe et al. BMC Public Health (2025) 25:311
It is important to note that the intervention had not
been implemented for a sucient time in Kasai to con-
tribute to signicant improvements in immunization
coverage or equity. Georeferenced tools were distributed
in Kasai in 2023 and would need at least 12 months of
implementation to contribute to substantial changes in
immunization outcomes. us, for this part of the study,
Kasai was also considered as control with Haut Lomami
as the unique intervention site.
Changes in immunization coverage and loss to follow up
after at least 12 months of implementation
Secondary data analysis of Bacillus Calmette–Guérin
(BCG), Oral Polio Virus (OPV) 0 and Pentavalent vacci-
nation coverage from the 2020, 2021 and 2022 VCS in the
three Provinces show some marked improvement in the
intervention Province during the period of implementa-
tion with stagnation in other two sites [9].
Coverage surveys show improvements in BCG vac-
cination coverage in the intervention Province of Haut-
Lomami Province (9.9% (2020), 78.9% (2021) and 94%
(2022)). Kasai Central (control Province) saw some
improvement in BCG coverage between 2020 and 2021
(25.3% in 2020 to 56.9% in 2021) with stagnation in 2022
(at 56.2%). Kasai (control Province) showed an improve-
ment in BCG antigen coverage, with a “V”-shaped evolu-
tion over the three years, i.e. a drop from 52.9% in 2020
to 44.9% and then an improvement to 57.1% in 2022.
(Fig.3).
e trend for OPV 0 is similar to that observed with
BCG, with large improvements in coverage in the
intervention Province of Haut-Lomami and moderate
improvements or stagnation in the control Provinces of
Kasai Central and Kasai (See Fig.4).
For Pentavalent 1 antigen, the VCS data show a large
increase in coverage in Haut-Lomami Province (Inter-
vention) across the 3 time points (9.9% in 2020 to 78.5%
in 2021 and 93.6% in 2022). For the two control Prov-
inces, the rate saw more modest net improvements at the
third timepoint. For the 3rd dose of Pentavalent, the vac-
cine coverage rate also showed a signicant improvement
for Haut-Lomami with similar drop-out rates across the
3 timepoints indicating stability within the immuniza-
tion program. In the two Control Provinces of Kasai and
Kasai Central there was a net increase in the dropout rate
between Penta 1 and Penta 3, indicating a decline in the
immunization program’s follow-up with children who
started the vaccination schedule (See Table4).
It emerged from interviews that in general, the use of
georeferenced data made it possible to improve involve-
ment of health facilities that have not oered immuni-
zation services and consequently to reach children who
missed vaccination days. In addition, this made it pos-
sible to improve the vaccination catch-up which was
carried out previously by the community relays to reach
zero-dose children. A nurse stated the following: “You
know a health facility which 15 kms far away from a
health center and does not vaccinate. If for example the
nursing sta of a health center starts moving with vac-
cines to the health facility that does not vaccinate, when
Fig. 4 Estimates of OPV0 antigen vaccination coverage for children aged
12 to 23 months. Point estimates of OPV0 antigen vaccination cover-
age indicators according to the vaccination map in children aged 12 to
23 months in the Provinces of Kasai, Kasai Central and Haut-Lomami in
the DRC from 2020, 2021 and 2022. Source: Vaccination coverage survey
(VCS) in DRC: 2020, 2021 and 2022 [9]
Fig. 3 Estimates of BCG antigen vaccination coverage for children aged
12 to 23 months. Point estimates of BCG antigen vaccination coverage
indicators according to the vaccination map for children aged 12 to 23
months in the provinces of Kasai, Kasai Central and Haut-Lomami in the
DRC in 2020, 2021 and 2022. Source: VCS in DRC: 2020, 2021 and 2022 [9]
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Page 11 of 14
Ngo-Bebe et al. BMC Public Health (2025) 25:311
they arrive there, you will see all these children who were
zero dose will come to be vaccinated and even this health
facility will also be interested in vaccination. So, it does
inuence positively the reduction of zero doses and even
the involvement of other types health facilities in vaccina-
tion.” (Respondent; Health Area, Haut-Lomami).
However, in Kasai, some respondents reported dif-
culties linked to recurrent population movements.
is creates challenging in locating target children with
the consequence of uneven vaccination coverage. For
example, one respondent said: “e obstacles that we
often experience is movement, we are in a purely mining
Health Zone where the population is moving all the time.”
(Respondent _09, HA, Kasai).
Impact of geospatial data on equity
e impact of geospatial data on equity was assessed in
terms of reaching the most marginalized children 0–23
months (girls/boys) and the main caregivers - women
and adolescent girls in their reproductive years (15–49
years of age). However, because of the unavailability of
economic data, the ability to conduct robust equity anal-
yses was limited. e results of the equity analyses were
inconclusive, and therefore, not presented here. ey
have been included in the comprehensive research report
provided as Supplementary Material.
Discussion
e study aimed to assess the acceptance and use of
geoenabled microplans for better immunization planning
and services delivery. It tested the hypothesis that the
availability and eective use of geospatial data can con-
tribute to increased immunization coverage and equity,
through the identication of missed settlements and
zero-dose children, the optimization of vaccination strat-
egies, and the supply distribution. It also incorporated a
gender-sensitive approach and included a gender sub-
study to assess gender-specic interventions in a sub-set
of Health Zones and Health Areas in Kasai, as part of
Gavi’s intensied strategy to address gender inequity and
the global Immunization Agenda 2030 focus on gender
[1–3].
e results indicate that the georeferenced microplans
in Haut-Lomami and Kasai were well received, used, and
led to changes in the planning and delivery of vaccination
services. As an innovation, the context and mechanisms
through which geospatial data and tools were created
and accepted for use conrmed their importance and
eective adoption at Health Zones and Health Areas. As
found in Haut Lomami, geospatial data enabled the visu-
alization and analysis of health data in spatial contexts,
oering insights into the geographical distribution of the
population, health area boundaries, healthcare facilities
and immunization coverage. In line with our results, it
has been largely documented that Geospatial Informa-
tion Systems (GIS) and other geospatial technologies
facilitate targeted interventions, allowing health authori-
ties to optimize and enhance the precision of resource
allocation in resource-constrained settings and identied
underserved areas to allocate resources eciently in spe-
cic geographic areas [10–15].
e potential of GIS and spatial analysis to enhance
the eectiveness of health providers and monitor immu-
nization coverage has been emphasized in other Central
African countries [16–19]. e evaluation of immuniza-
tion coverage in Haut Lomami before and after the avail-
ability of geospatial data have shown that these tools
may have contributed as one component of a broader
set of immunization strategies to signicant increases in
immunization coverage rates and lower dropouts, includ-
ing reduced numbers of zero-dose children. ese results
corroborated with other studies in the context of LMICs
[5, 13, 17]. Additional study with a longer observation
time, i.e., more than three years, is recommended in Kasai
to triangulate ndings from Haut-Lomami and assess the
additional contribution of gender-intentional approaches
to improved immunization outcomes. However, to be
fully eective, the production and use of geospatial data
and maps need more work to build capacity and ensure
the quality of data and maps, as persistent challenges in
Table 4 Estimates of Penta 1 and 3 vaccination coverage ages 12–23 months
Provinces VCS 2020 VCS 2021 VCS 2022
Penta1 (%) Penta 3 (%) Drop-
out
rate
(%)
Penta 1 (%) Penta 3
(%)
Drop-
out
rate
(%)
Penta 1 (%) Penta 3
(%)
Drop-
out
rate
(%)
Kasai VC (%) CI 95% 51.0
(46.6–55.4)
45.3
(41.2–49.4)
5.7 48.1 (44.3–51.8) 34.4
(30.8–38.2)
13.7 58.3
(53.3–62.0)
38.0
(33.4–42.6)
20.3
Haut-Lomami VC (%) CI 95% 9.9 (7.1–13.6) 8.9 (6.3–12.6) 1.0 78.5 (73.3–83.0) 76.8
71.4–81.4)
1.7 93.6
(92.0-94.9)
92.0
(90.4–93.8)
1.6
Kasai Central VC (%) CI 95% 26.3
(23.6–29.2)
21.8
(19.3–24.6)
4.5 61.1 (57.4–64.6) 47.2
(43.2–51.2)
13.9 59.3
(55.7–62.9)
43.8
(40.7–47.9)
15.5
Legend: Point estimates of Penta 1 and 3 vaccination coverage indicators in children aged 12 to 23 months in the 3 provinces of the study in 2020, 2021 and 2022.
Source: VCS in DR C: 2020, 2021 and 2022 [9]. VC: Vaccine Coverag e; CI: Condence Interva ls
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Page 12 of 14
Ngo-Bebe et al. BMC Public Health (2025) 25:311
data quality, such as inated coverage gures and inac-
curate denominators, remain signicant hurdles [7, 16,
20, 21]. Qualitative research in the 2 intervention Prov-
inces included in this study show that gaps remain in the
protocols for validating the data with the community and
making regular updates in the datasets. ere is room for
improvement to boost the acceptance, quality and eec-
tive use of the geo-referenced microplans through mean-
ingful community engagement, capacity building and
digital literacy training for end users.
e drastic improvements in immunization outcomes
in Haut-Lomami may be also explained by other fac-
tors, such as the parallel implementation of some specic
immunization projects, which worked in synergy. e
Province of Haut-Lomami has been a Mashako Plan site
with intensied support of the NEPI [4, 22]. In addition,
an intervention aiming to improve the distribution of
vaccine products up to the last kilometer and using Infor-
mation and Communication Technologies in the elds of
health has intensively assisted the Province through the
NEPI branch oce of Kamina [22, 23]. We are unable to
attribute the full increase observed for the Penta3 vac-
cine between 2020 and 2021 (from 8.9% in 2020 to 76.8%
in 2021) to the adoption and use of geospatial data alone
and acknowledge that it may be an important part of a
larger package of strategic NEPI interventions.
Taking a gender lens for the overall study, we identied
perceived positive contributions to the intervention and
the evaluation. In the delivery of immunization services,
it is important to include transformative and equitable
gender strategies, taking into account the socio-cultural
contexts in which health workers and caregivers live and
work. Gender mainstreaming must be carried out at all
levels of microplanning design and implementation,
in the use of georeferenced data, in conducting routine
immunization, and in monitoring and evaluation. To
achieve this, awareness and action is needed at national
and sub-national levels to conduct gender analyses and
design gender-sensitive interventions to reduce gender-
related barriers to immunization and georeferenced data
use. Targeted interventions based on spatial analysis
eectively reduced disparities, promoting a more equi-
table distribution of immunization services, that address
specic barriers faced by vulnerable populations [13,
24–26]. Due to the lack of availability of robust data that
would enable the assessment of eects related to equity,
we were unable to compare results beyond those associ-
ated with the reduced rate of zero-dose children detected
in Haut-Lomami Province. However, to tackle inequi-
ties in immunization, for over a decade countries have
been focusing on eective immunization microplans at
the subdistrict level, using georeferenced data and maps
for better planning of immunization activities, such as
community-based Reach Every Child (REC) intervention
[11, 12, 25–28].
Limitations of the study
Overall, while our study is in line with the recent lit-
erature and demonstrates the positive contribution of
geospatial data on immunization outcomes, challenges
persist. e intervention did not allocate sucient
resources and time for socialization and capacity building
to promote the adoption and eective use of the maps,
geospatial data and geo-referenced microplans. is was
compounded by delays from the COVID outbreak that
impacted the overall routine immunization program and
limited community engagement in the mapping process
and created a gap between the collection and generation
of the geospatial data and the distribution and adoption
of the geospatial resources. Additional challenges are
inherent in the design of the intervention that optimizes
strategies based on population distribution. By targeting
areas with higher populations for improved immuniza-
tion delivery strategies, areas with lower populations may
not benet from improvements in immunization cover-
age at the same rate. While the overall goal is to reach
high childhood immunization rates in all geographic
areas for all populations, tradeos are often necessary
especially in the implementation of new strategies and
technology approaches. Future implementation research
should focus on overcoming these challenges, optimizing
the use of geospatial data into immunization strategies
in all health facilities, and expanding gender-sensitive
approaches across the full NEPI.
is research study faced constraints and limitations
due to delays in project implementation that resulted in
a shortened period between implementation, distribu-
tion and adoption of the maps in health facilities and the
research data collection, preventing the ability to observe
impact on immunization outcomes for the recommended
12–24 month period. A follow-up study to measure lon-
ger-term outcomes is in the planning stages. e study
was also not able to calculate cost-eectiveness, conduct
costing analysis or determine the impacts on socio-eco-
nomic equity due to the unavailability of these data from
external surveys. Since the quantitative pre/post data
relied on secondary analysis of VCS survey reports, the
study was not able to include more detailed analysis of
vaccine cards and memory recall.
Conclusion
e situation of zero-dose children in the DRC is a major
concern. e overall objective of the study was to evalu-
ate the acceptance and use of geo-enabled microplans
for the planning and delivery of routine immunization
services, and the associated contribution to increased
and sustained immunization coverage with a focus on
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Page 13 of 14
Ngo-Bebe et al. BMC Public Health (2025) 25:311
the identication and vaccination of zero-dose children.
e results indicate that the georeferenced microplans
in Haut-Lomami and Kasai were well received, used, and
led to changes in planning for and delivery of vaccina-
tion services. In addition, the gender ethnographic study
in Kasai indicates that the gender intervention led to the
greater inclusion of women in immunization activities.
We observed a signicant positive trend in Haut-Lomami
in immunization outcomes, including an increase in
overall vaccination coverage and improved identica-
tion and immunization of zero-dose children. Due to the
delayed time of georeferenced microplan adoption and
use, a supplemental study to follow the implementation
in Kasai in 2024 and 2025 for further immunization cov-
erage and equity analyses is planned.
In general, this research study revealed important les-
sons for the design and implementation of geospatial data
programs for immunization program planning. Com-
munity engagement and a gender-intentional approach
throughout the planning, data and map creation pro-
cesses are valuable to increase impact and eectiveness.
More attention should be paid to economies of scale
and seek out opportunities for cross-sector investment
in geospatial data sets which can be foundational assets
across national priorities, not only for the immunization
program. Capacity strengthening for people involved in
the creation and use of geo-referenced microplans as
well as a long-term plan for maintaining and updating
the data should be embedded in the project from the
beginning.
Abbreviations
BCG Bacillus Calmette–Guérin vaccine
CAC Cellule d’Animation Communautaire (Community Animation
Cells)
DRC The Democratic Republic of Congo
CODESA Comité de Développement de l’Aire de Santé (Health Area
Development Committee)
DTP1 Diphtheria–tetanus–pertussis containing vaccine, rst dose
Gavi Gavi, the Vaccine Alliance
GIS Geographic Information System
GRID3 Geo–Referenced Infrastructure and Demographic Data for
Development
KSPH Kinshasa School of Public Health
LMIC Low–and middle–income country
M4H Mapping for Health
NEPI Expanded Program on Immunization
NHIS National Health Information System
OPV Oral polio vaccine
VCS Vaccine Coverage Survey
WHO World Health Organization
Supplementary Information
The online version contains supplementary material available at h t t p s : / / d o i . o r
g / 1 0 . 1 1 8 6 / s 1 2 8 8 9 - 0 2 5 - 2 1 5 7 8 - x .
Supplementary Material 1
Supplementary Material 2
Supplementary Material 3
Supplementary Material 4
Supplementary Material 5
Supplementary Material 6
Acknowledgements
The authors would like to thank the DRC EPI at the national, provincial, facility,
and community levels and implementing partners for their support and
participation in the evaluation.
Author contributions
DNB is the Principal Investigator and led the research on behalf of the KSPH.
PM led the overall research design and publication process on behalf of
health.enabled. FK, TB, GL, FL, KL, and MK supported the research design,
eld research, report and publication writing with the KSPH. BK provided
overall support for research activities in DRC on behalf of health.enabled. KT
provided inputs into the research study and review of ndings on behalf of
the implementation partner, Columbia University. CL reviewed the ndings of
the research study on behalf of National Expanded Program on Immunization.
CG provided overall guidance for the research study and review of ndings on
behalf of Gavi, the Vaccine Alliance.
Funding
Funding was provided for the implementation and evaluation of Mapping for
Health by Gavi, the Vaccine Alliance through the INFUSE Project.
Data availability
Data is provided within the manuscript and can be requested via email to
ngobebed@gmail.com.
Declarations
Ethics approval and consent to participate
The Mapping for Health Study has been reviewed and cleared by the
Kinshasa School of Public Health Internal Review Board. The research team
obtained informed written consent from all study participants prior to their
engagement in the research study. The study has also been registered with
BMC Central International Standard Randomised Controlled Trial Number
ISRCTN65876428 on 3/11/2021.
Consent for publication
All human subjects have provided informed written consent to participate in
the study and for results to be published. All co-authors have reviewed the
paper and agreed to have it submitted for review and publication.
Competing interests
The authors declare no competing interests.
Author details
1Kinshasa School of Public Health, University of Kinshasa, Kinshasa,
Democratic Republic of Congo
2health.enabled, 3147 Tennyson St NW, Washington, DC 20015, USA
3Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
4Department of Social Science, University of Kinshasa, Kinshasa,
Democratic Republic of Congo
5Earth Institute, Columbia University, New York City, USA
6National Expanded Program on Immunization, Ministry of Health,
Kinshasa, Democratic Republic of Congo
7Gavi, The Vaccine Alliance, Geneva, Switzerland
Received: 28 February 2024 / Accepted: 21 January 2025
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