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Contents lists available at ScienceDirect
Vaccine
journal homepage: www.elsevier.com/locate/vaccine
Use of rapid needs assessment as a tool to identify vaccination delays
in Guatemala and Peru
Katie K. D’Ardenne a , Juliana Darrow b , Anna Furniss c , Catia Chavez b,c ,
Herminio Hernandez d , Stephen Berman a,b , Edwin J. Asturias a,b,∗
a
Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
Center for Global Health, Colorado School of Public Health, Aurora, CO, USA
c
Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS), Aurora, CO, USA
d
School of Medicine and Public Health, University Cayetano Heredia, Lima, Peru
b
a r t i c l e
i n f o
Article history:
Received 19 September 2015
Received in revised form 24 January 2016
Accepted 25 January 2016
Available online xxx
Keywords:
Rapid needs assessment
Immunization delays
Peru
Guatemala
Rotavirus
Measles
Pentavalent
Vaccines
a b s t r a c t
Objective: To explore the use of rapid needs assessment (RNA) surveys to determine the prevalence and
factors contributing to delays in vaccination of children in two low middle-income countries (LMIC).
Methods: Data from two RNA surveys performed as part of program improvement evaluations in
Guatemala and Peru were used for this analysis. The primary endpoint was the timeliness of immunization with delay defined as administration of vaccines beyond 28 days from recommended age for
DTwP-HepB-Hib (Penta) and measles–mumps–rubella (MMR) vaccines, as well as past age-restrictions
for rotavirus vaccine. Independent risk factors analyzed included child’s gender, birth year, number of
children in household, maternal age, maternal education, and food insecurity.
Results: Vaccine information was available from 811 children from 838 households surveyed. High rate
of immunization delays was observed, with 75.6% of children in Guatemala and 57.8% of children in Peru
being delayed for the third dose of Penta primary series. Factors associated with delayed vaccination in
Guatemala included advanced maternal age and increased number of children in household. In Peru, significant associations were birth year before 2009, lower maternal education level, and increased number
of children in household.
Conclusions: RNA is a fast and effective method to identify timely vaccine coverage and derive a hypothesis
of factors possibly associated with vaccination delay.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
Immunization has proven to be the most effective way to prevent childhood infectious diseases at the individual and population
levels when administered before the period of risk. Delays in vaccination not only expose children to infections at the time they are
most vulnerable, but also place them at risk for never completing
their immunization schedule [1,2]. Worldwide, the Global Vaccine
Action Plan (GVAP) goal – endorsed by the 194 Member States
of the World Health Assembly in May 2012 – seeks to make the
benefits of immunizations equitably extended to all people “reaching every community” and engaging underserved and marginalized
groups by 2020. The World Health Organization (WHO) has issued
immunization guidelines that address the recommended number
∗ Corresponding author at: Center for Global Health, 13199 East Montview Blvd,
Suite 310, Aurora, CO, USA. Tel.: +1 303 724 6282; fax: +1 303 72 46286.
E-mail address: [email protected] (E.J. Asturias).
of doses that can be adapted to each individual country’s immunization strategy [3].
Latin America is a pioneer and model region for immunizations that has resulted in the elimination of measles and congenital
rubella [4]. Most countries report 90% or more national coverage
of immunization in young children; however timeliness of vaccination remains a challenge [4,5]. This trend holds true globally, as
studies have shown difficulty in reaching the last 10–15% of unimmunized children in most of low and middle-income countries
(LMIC) due to multiple factors associated with immunization delays
[6–14]. There is no standardized method to evaluate immunization delay; past studies have utilized a wide range of statistical
methods including case control studies, retrospective studies, and
cross-sectional survey studies [15]. To our knowledge, no study
has utilized a rapid needs assessment (RNA) to evaluate vaccine
coverage and factors that could be contributing to immunization
delay.
RNA is a fast and reliable tool that can be utilized to quickly
develop an initial understanding of a community health status
http://dx.doi.org/10.1016/j.vaccine.2016.01.060
0264-410X/© 2016 Elsevier Ltd. All rights reserved.
Please cite this article in press as: D’Ardenne KK, et al. Use of rapid needs assessment as a tool to identify vaccination delays in Guatemala
and Peru. Vaccine (2016), http://dx.doi.org/10.1016/j.vaccine.2016.01.060
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Table 1
Baseline demographic characteristics of mothers and children participating in the rapid needs assessment surveys in Guatemala and Peru 2010–12.
Demographic
Level
Guatemala (n = 313)
N
Peru (n = 498)
Percenta
N
Percenta
Gender of child
Male
Female
167
145
53.5
46.5
252
241
51.1
48.9
Child’s age (years)
Mean (median)
0 to =1 years
<1 to =2 years
<2 to =3 years
<3+ years
312
43
57
65
147
3.0 (3)
13.8
18.3
20.8
47.1
492
122
98
104
168
2.3 (2)
24.8
19.9
21.1
34.1
Cohort
Early cohort (<2009)
Late cohort (≥2009)
161
151
51.6
48.4
117
375
23.8
76.2
Number of children <15 years in household
Mean (median)
1 child
2–5 children
>5 children
313
45
201
67
3.8 (3)
14.4
64.2
21.4
498
105
310
83
3.3 (3)
21.1
62.2
16.7
Mother’s age (years)
Mean (median)
18 & younger
19 to <25 years old
25 to <35 years old
35 and older
313
25
98
126
64
28.0 (26)
8.0
31.3
40.3
20.4
497
34
151
203
109
28.4 (27)
6.8
30.4
40.8
21.9
Mother’s education
None
Primary
Secondary/advanced
65
151
90
21.2
49.3
29.4
138
355
28.0
72.0
Food insecure
Food secure
217
96
69.3
30.7
200
298
40.2
59.8
Food security
a
Percent reported unless indicated to be mean (median).
and develop hypotheses for future studies and interventions [16].
We took advantage of data available from two RNAs coordinated
by the Center for Global Health (CGH) of the Colorado School
of Public Health to evaluate maternal and child health programs
in Guatemala and Peru to estimate the timeliness of immunization and identify possible factors associated with delays in
vaccination.
2. Methods
2.1. Population
Rural communities in the southwest departments of Quetzaltenango and San Marcos in Guatemala, as well as rural and urban
communities in the Loreto Region of Peru, were surveyed as part of
two RNAs conducted by the CGH and aimed at evaluating maternalchild health needs and program outcomes. Both surveys were
considered to be program evaluation rather than human subject
research by the Colorado Multiple Institutional Review Board, and
therefore informed consent was not required. Interviews were conducted with mothers of children less than 5 years of age who
resided in the target communities. In Guatemala, the RNA was
designed to evaluate the impact of “Mis Mejores Familias” (MMF),
a local health education program intended to improve maternal
and child well-being [17]. Preliminary results on vaccine coverage
by age in the MMF vs. non-MMF children in Guatemala showed
no significant differences, allowing us to use both populations for
this study. The target communities in Peru were part of the area
of influence of Centura Health’s Global Health Initiative on-going
maternal-child health programs [18]. Guatemala offers free access
to vaccines through the Ministry of Health [19]. Peru has a decentralized health care system, where the Ministry of Health accounts
for 60% of coverage, and a combination of private and public insurance accounts for the remaining [20]. Regions targeted by this study
in both Guatemala and Peru are considered to be underserved in
healthcare resources.
2.2. Design and data abstraction
The RNA surveys consisted of a 90-item questionnaire administered by students and community health workers under the
coordination of the CGH in October 2011 in Guatemala and July
2012 in Peru. Families were identified using a cluster sampling
technique following the Lot Quality Assurance Sampling (LQAS)
method adapted from the WHO [21,22,23]. Thirty clusters of seven
households were included in Guatemala using the house of a MMF
program participant as the index for each cluster. In Peru, thirty
clusters of seven households were selected at random using health
districts maps from both urban and rural zones, for a total of sixty
clusters. A sample size of 210 households for each area was chosen
as per LQAS, plus 30% additional households to account for missing
data. For both countries, random selection was done by proceeding
to the third house on the left from the previous participant whenever possible. There were no recorded instances of participation
refusal; however when a family was absent from the home the surveyors proceeded to an additional house to the left. Mothers were
interviewed in privacy of their homes with no other members of the
household present whenever possible. Immunization information
was obtained from the child’s vaccination card. If a vaccination card
was not available, the survey was completed leaving the vaccine
information blank. For this analysis, children in whom vaccination
card information was absent or who were younger than 6 weeks,
and therefore ineligible for the targeted vaccines, were excluded.
Data from the Guatemala RNA was entered using Teleform®
software (Cardiff, USA), and for the Peru RNA using RedCap® (Vanderbilt University, TN, USA). Both data sets were de-identified at
export and no personal information was available to the investigators for this analysis.
2.3. Definition of vaccination delay
The primary endpoint of this analysis was the timeliness of
immunization categorized as delayed or not delayed for each
Please cite this article in press as: D’Ardenne KK, et al. Use of rapid needs assessment as a tool to identify vaccination delays in Guatemala
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Fig. 1. Cumulative distribution of 3 primary doses of Penta (DTwP-HBV-Hib) vaccine in children <5 years of age in Guatemala and Peru.
vaccine. The interval for immunization was calculated comparing
the date of each vaccination administration with the date of birth.
In accordance with previous studies, vaccination delay was defined
as receipt of vaccine greater than 28 days after recommended age
according to the recommended national immunization schedule
in each country for all doses of Penta and the MMR dose [24].
Guatemala and Peru immunization programs follow a 2, 4 and 6
month primary schedule providing Penta and polio; in addition
to rotavirus and pneumococcal vaccines at 2 and 4 months. The
rotavirus vaccine was introduced in Peru in January 2009 and in
Guatemala in February 2010 and age-restriction windows were in
place according to the manufacturer’s package insert that the first
dose be administered before 15 weeks of age, and the last dose
by 32 weeks. Therefore, for rotavirus vaccine, a delay was defined
as the first dose given past 15 weeks of age, and the last dose
administered later than age 32 weeks. Because of the timing of the
RNA relative to introduction of the rotavirus vaccine, a larger sample of children eligible for rotavirus vaccination was available in
Peru. The first MMR is recommended at 12 months of age in both
countries since measles and rubella have been nearly eliminated
from the region.
2.4. Variables related to vaccination delay
Independent variables included were gender of child, birth year
cohort, number of children in household, maternal age, maternal
education, and food insecurity. Maternal education level was classified as primary if mothers had completed up to the 6th grade,
secondary if completed through 12th grade, and advanced if a post
high school degree was obtained. A “none” category was used for
Please cite this article in press as: D’Ardenne KK, et al. Use of rapid needs assessment as a tool to identify vaccination delays in Guatemala
and Peru. Vaccine (2016), http://dx.doi.org/10.1016/j.vaccine.2016.01.060
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mothers who had never completed any formal schooling. Food insecurity was measured using 4 of the survey questions adapted from
the Household Food Insecurity Access Scale (USAID 1987, Washington DC, USA) that assessed on a 1–3 Likert measure the status
of food availability in each mother’s family. These questions were
scored and 0–4 classified as food secure and 5–12 as food insecure.
2.5. Statistical analysis
Proportions were used to describe the basic characteristics of
the populations and to estimate vaccination status. Proportions for
the primary outcome (delayed or not) for all Penta doses and MMR
were all >10%. Therefore a log-binomial regression was used to test
associations between variables and the dependent factors and to
generate relative risks [25]. Due to the limited number of children
receiving rotavirus in Guatemala, it was not modeled. All regression models were adjusted for the random effects of community
within each country; therefore, community was not tested independently with any primary outcome. Due to the limited number
of children available for various demographic characteristics and
primary outcomes, only univariate associations were performed, as
a multivariate analysis would not have provided a stable estimate.
All analyses were conducted using SAS (version 9.3, SAS Institute,
Cary, NC, USA).
Fig. 2. Proportion of children in Guatemala and Peru delayed for vaccination against
Penta, Rotavirus and measles–mumps and rubella vaccines 2011–2012. Note: Percent late for vaccination: >28 days for dose 1–3 of Penta and MMR, and >15 weeks
for Rota 1 and >32 weeks of age for Rota 2.
their first dose after the recommended age of 15 weeks; and 8
(21.1%) and 14 (5.4%) infants, respectively, received the last dose
of vaccine past 32 weeks of age.
3.2. Variables related to vaccination delay in Guatemala and Peru
3. Results
RNA surveys were conducted in Guatemala between September
30 and October 3, 2011 and in Peru from July 1 to 7, 2012. Among the
eight hundred and thirty households surveyed; 283 (34.1%) were
from Guatemala and 547 (65.9%) from Peru. There were 1057 children <5 years in those households; 391 (36.9%) from Guatemala
and 670 (63.1%) from Peru. Of these children, 246 (29.6%) without a vaccination card were excluded from the analysis. Therefore,
811 children were included; 313 (38.6%) from Guatemala and 498
(61.4%) from Peru.
Table 1 provides baseline demographic characteristics of children and mothers. The mean age of children in Guatemala was 3.0
years, with 161 (51.6%) children having been born before 2009. The
mean number of children in household was 3.8 with mean maternal age 28.0 in Guatemala. Only 90 (29.4%) Guatemalan mothers
had completed education beyond primary school, and 217 (69.3%)
mothers reported moderate to severe food insecurity. In Peru, the
mean age of children was 2.3 years and mean maternal age was
28.4 years. The mean number of children in household was 3.3 and
117 (23.8%) children in Peru were born before the year 2009. Completion of secondary or advanced education was reported in 355
(72.0%) mothers in Peru and food insecurity was reported in 200
(40.2%) households.
3.1. Immunization status of children
Fig. 1 shows the cumulative proportion of children who received
on-time vaccination for the Penta vaccine by dose. Approximately
half of infants in Guatemala (n = 163, 54.3%) and two thirds in Peru
(n = 316, 66.8%) completed their first dose of Penta vaccine on time.
There was a significant increasing trend in the proportion of children delayed for each subsequent dose of Penta vaccine in both
Guatemala and Peru (p < 0.0001). As shown in Fig. 2, the cumulative proportion of children with delayed immunization >28 days
from recommended age increased from 45.7% of Penta 1 to 77.4%
of Penta 3 in Guatemala and from 33.2% of Penta 1 to 59.9% of Penta
3 in Peru. MMR vaccination was administered on time in 58.2% of
children in Guatemala and 44.3% of children in Peru.
For rotavirus, of those children eligible for rotavirus vaccine, 23
(41.1%) infants in Guatemala and 48 (14.2%) infants in Peru received
Table 2 shows the factors evaluated for association with vaccination delay. In Guatemala, there were no significant associations for
late administration of the Penta series. Late administration of MMR
vaccine was associated with advanced maternal age (RR = 1.13,
p < 0.05), and male gender was protective for delay in MMR vaccination (RR = 0.70, p < 0.05). For each additional child in the household
above the mean of 3.8 children, there was a 7% increased risk of late
administration of MMR vaccine (RR = 1.07, p < 0.05).
In Peru, birth year cohort before 2009 was significantly associated with late administration of all Penta vaccines and MMR
(p < 0.001). Lower maternal education level was associated with late
administration of Penta 1 (RR 1.39, p < 0.05) and Penta 3 (RR 1.25,
p < 0.05). Increased number of children in the household beyond
the mean of 3.3 was associated with late administration of Penta
2 (RR 1.06, p < 0.05), Penta 3 (RR 1.05, p < 0.05) and MMR (RR 1.07,
p < 0.05). Food insecurity was also observed to be linked to on-time
receipt of Penta 3 (RR = 0.83, p < 0.05).
4. Discussion
Our findings demonstrate the feasibility of using RNA surveys
(LQAS or cluster-sample based) to detect high rate of delays in
childhood immunizations in both Guatemala and Peru. The data
from RNA surveys in different areas of Latin America can be used
in the future as a system to monitor not only vaccine coverage and
completeness, but also possible factors that influence failures and
delays to vaccinate children. Although the traditional measures of
childhood vaccination coverage (e.g. Penta 3 by 12 months of age,
or MMR by 24 months) provide information on the proportion of
children up-to-date based on recommended schedules, they do not
reveal the degree of immunization delays [26]. Therefore, an ageappropriate vaccination measure is a better indicator of vaccination
status in a specific population that could allow immunization programs to reach unimmunized children [27].
Other methods used to evaluate vaccination timeliness and the
risk factors for delays include the use of active surveillance programs [24]; prospective studies [28], and case-control studies [29].
However, most of these methods are personnel and cost intensive
or require good immunization registry databases that are linked
to demographic and health care information. Adapted from the
Please cite this article in press as: D’Ardenne KK, et al. Use of rapid needs assessment as a tool to identify vaccination delays in Guatemala
and Peru. Vaccine (2016), http://dx.doi.org/10.1016/j.vaccine.2016.01.060
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Table 2
Unadjusted associations with late administration (>28 days) of vaccines in (a) Guatemala and (b) Peru.
Country and variable
(A) Guatemala
Gender of child
No. of children in HH
Mother’s age (years)
(B) Peru
Education
Food security
Cohort
No. of children in HH
Mother’s age (years)
*
†
Level
Penta, dose 1
Relative risk, 95% CI
Penta, dose 2
Relative risk, 95% CI
Penta, dose 3
Relative risk, 95% CI
SPR (MMR)
Relative risk, 95% CI
Male
Female (ref.)
(per additional 1 child)
(per additional 5 years)
0.91 (0.72, 1.16)
–
1.01 (0.96, 1.06)
1.02 (0.95, 1.09)
0.98 (0.84, 1.15)
–
1.00 (0.97, 1.04)
0.98 (0.93, 1.04)
0.99 (0.88, 1.12)
–
0.97 (0.94, 1.00)
0.94 (0.90, 0.99)
0.70 (0.52, 0.96)*
–
1.07 (1.02, 1.12)*
1.13 (1.06, 1.21)*
Primary
Secondary/advanced
(ref.)
Food insecure
Food secure (ref.)
Early cohort (<2009)
Late cohort (>=2009)
(ref.)
(per additional 1 child)
(per additional 5 years)
1.39 (1.06, 1.83)*
–
1.20 (0.97, 1.49)
–
1.25 (1.05, 1.48)*
–
1.15 (0.93, 1.42)
–
1.00 (0.76, 1.32)
–
1.95 (1.53, 2.48)†
–
0.85 (0.69, 1.05)
–
1.55 (1.28, 1.86)†
–
0.83 (0.69, 0.99)*
–
1.48 (1.27, 1.73)†
–
0.98 (0.80, 1.20)
–
1.57 (1.30, 1.89)†
–
1.04 (0.98, 1.11)
0.95 (0.87, 1.04)
1.06 (1.01, 1.11)*
1.00 (0.94, 1.06)
1.05 (1.03, 1.08)†
0.99 (0.94, 1.05)
1.07 (1.04, 1.09)†
1.03 (0.97, 1.10)
p < 0.05.
p < 0.001.
disaster preparedness and response experience, RNAs have been
applied to rapidly evaluate health priority needs for program
response and evaluation [30–32]. The inclusion of immunization
information and household, environmental and socio-economic
data could be a powerful resource to explore potential factors that influence lagging immunization coverage in certain
populations.
As a result, our analysis found several factors to be associated
with vaccination delays, including lower maternal educational status, advanced maternal age, and increased number of children in
the household. Previous studies have looked at age-appropriate
vaccination, and found delays in immunization to be associated
with similar factors [33–35]. In India, immunization delays were
linked to increased family size, number of children <5 years old,
maternal education, socio-economic status, and distance from
the health center [36]. One study from Argentina found that for
DTwP and HepB vaccinations, delays were associated with later
place in the birth order, children whose caregivers had not completed primary school, and residence within a central zone of
the city [37]. The observed association of lower maternal education and immunization delay has been supported by numerous
studies. This finding may be driven by the ability to generate a
more complete knowledge of immunizations with an advanced
education [38].
The observation that more children received timely vaccinations in Peru if born during or after 2009 could be attributed to
the “Threshold Program”, which was implemented by the Peruvian
government with the help of the Millennium Challenge Corporation in June of 2008. This thirty-five million dollar grant targeted
immunization of rural children and assisted the Ministry of Health
in strengthening vaccination program management and outreach
[39]. Additionally, the national introduction of both rotavirus and
pneumococcal vaccinations in 2009 may have resulted in changes
in the national vaccination strategy that increased coverage and
opportunity for immunization [40].
The delayed administration of rotavirus vaccine in Guatemala
and Peru was to be expected when deploying a vaccine having age
restrictions in LMICs. Age-restrictions, while aimed to minimize
the risk of intussusception, may preclude children from completing
the vaccination series in LMICs where access and opportunity for
vaccination is problematic [41]. In Brazil, four years after rotavirus
vaccine was introduced, vaccine coverage for two doses of rotavirus
vaccine at 1 year of age was only 83% as compared to 98.4% for DTPHib2; a coverage gap that was perceived to be due to age restrictions
[42]. A benefit-risk model was developed by the Centers for Disease
Control and Prevention to address rotavirus vaccine age-specific
guidelines. This model predicted that by removing age restrictions
there would be 47,200 fewer rotavirus deaths worldwide and only
294 additional intussusception deaths, for an incremental benefitrisk ratio of 154 fewer deaths for every one death caused by vaccine
related-intussusception [14]. In January 2013, WHO recommended
that countries could use a more lenient age for completing the
rotavirus series by 24 months of age, encouraging them to focus
on early vaccine administration [43].
There are several limitations of the present study. First, the
RNAs were designed to evaluate the maternal-child health status of the communities, and not specifically to study risk factors
for immunization timeliness. Therefore, if risk factors for immunization delays are to be elucidated, investigators and program
evaluators will need to make use of best epidemiological practices
of risk-factor analysis. RNA is not a validated method to draw conclusions on risk factors, but is a way to generate hypotheses that
could be tested in case-control or immunization registry cohort
studies. Second, we were only able to include children with the
vaccination card in our analysis, resulting in exclusion of a third
of children and we made no attempts to extrapolate data to the
excluded households, even when some children were reported to
have received immunizations, but their card was unavailable. This
introduces a selection bias to our findings, as households without
a vaccination card may be different from households that keep the
vaccination card.
Third, these data sets reflect only the timeliness of immunizations in two less-developed regions of Guatemala and Peru, and
may not be representative of the national immunization program
coverage levels for each country. As previous studies have shown,
the proportion of those vaccinated and the impact of the vaccines
may differ between distinct regions within a country [27]. The study
could not account for the impact of availability of vaccines at government clinics in both countries that may influence the timely
completion of vaccine schedules. As it was shown in Peru, the
younger cohorts had better completion rates after an optimized
immunization strategy was used.
Additionally, the sample size was not calculated to estimate differential effects, but we can infer that the larger sample size in Peru
contributed to more associations than in Guatemala. Finally, our
limited sample size prevented the use of a multivariate regression
model and consequently we cannot comment on the presence of
potential confounders.
Please cite this article in press as: D’Ardenne KK, et al. Use of rapid needs assessment as a tool to identify vaccination delays in Guatemala
and Peru. Vaccine (2016), http://dx.doi.org/10.1016/j.vaccine.2016.01.060
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5. Conclusion
[9]
RNA is a quick and effective tool to evaluate vaccine coverage and possible risk factors for immunization delay. This study
demonstrates that if a set of core variables and factors can be
identified and confounders controlled, RNAs can shed light on population determinants of lower vaccine coverage and timeliness.
High rates of delays in childhood immunizations in both Guatemala
and Peru appear to be related to maternal, family and program
access factors. Improving vaccination coverage in countries that
have already reached high rates of immunization requires tools
to identify age-appropriate immunization strategies that can overcome the reasons associated with delayed immunizations.
[11]
Funding source
[14]
Funding for the RNA surveys was provided by program evaluation grants from the Foundation Jose Fernando Bolaños Menendez
in Guatemala, and Centura Global Health Initiative for Peru.
[10]
[12]
[13]
[15]
[16]
Author’s contributions
[17]
EJA and KKD conceptualized and designed the study. EJA, KKD,
CC, HH and SB participated in the collection of data. EJA, KKD,
JD, AF and SB were responsible for analysis and interpretation of
data. KKD, JD, AF and EJA collaboratively wrote the manuscript. All
authors read and approved the final version.
[18]
[19]
[20]
[21]
Acknowledgements
[22]
The authors will like to thank the community health workers
from Guatemala and Peru who actively conducted surveys. Jose
Guillermo Rivera from University del Valle in Guatemala helped in
the survey design and data management. Greg Hodgson from Centura Global Health Initiative provided leadership and support for
the Peru RNA and the Ministry of Health of Loreto collaborated in
the design and execution. Students from the School of Medicine at
University Cayetano Heredia and CU Peru, University of Colorado,
under the leadership of Herminio Hernandez and Jennifer Bellows
participated in the administration of the survey in Peru. Sheana
Bull guided the initial analysis of the data.
Conflict of interest: All the authors have declared that they have
no competing interests.
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