Predictors of Infant Age at Enrollment in Early Infant Diagnosis Services in Kenya
Predictors of Infant Age at Enrollment in Early Infant Diagnosis Services in Kenya
Kathy Goggin 0 1 2 3 4 5 6 7 8 9
Catherine Wexler 0 1 2 3 4 5 6 7 8 9
Niaman Nazir 0 1 2 3 4 5 6 7 8 9
Vincent S. Staggs 0 1 2 3 4 5 6 7 8 9
Brad Gautney 0 1 2 3 4 5 6 7 8 9
Vincent Okoth 0 1 2 3 4 5 6 7 8 9
Samoel A. Khamadi 0 1 2 3 4 5 6 7 8 9
Andrea Ruff 0 1 2 3 4 5 6 7 8 9
Michael Sweat 0 1 2 3 4 5 6 7 8 9
An-Lin Cheng 0 1 2 3 4 5 6 7 8 9
Sarah Finocchario-Kessler 0 1 2 3 4 5 6 7 8 9
0 University of Missouri-Kansas City, School of Medicine , Kansas City, MO , USA
1 Children's Mercy Hospitals and Clinics, Health Services and Outcomes Research , 2401 Gillham Road, Kansas City, MO 64108 , USA
2 & Kathy Goggin
3 Medical University of South Carolina, Department of Psychiatry and Behavioral Sciences , Charleston, SC , USA
4 Johns Hopkins Bloomberg School of Public Health, Department of International Health , Baltimore, MD , USA
5 Kenya Medical Research Institute , Nairobi , Kenya
6 Global Health Innovations , Kansas City, MO , USA
7 University of Kansas Medical Center, Department of Preventive Medicine , Kansas City, KS , USA
8 University of Kansas Medical Center, Department of Family Medicine , Kansas City, KS , USA
9 University of Missouri-Kansas City, School of Pharmacy , Kansas City, MO , USA
Despite the importance of early detection to signal lifesaving treatment initiation for HIV? infants, early infant diagnosis (EID) services have received considerably less attention than other aspects of prevention of mother to child transmission care. This study draws on baseline data from an on-going cluster randomized study of an intervention to improve EID services at six government hospitals across Kenya. Two logistic regressions examined potential predictors of ''on time'' (infant B6 weeks of age) vs. ''late'' (C7 weeks) and ''on time'' versus ''very late'' (C12 weeks) EID engagement among 756 mother-infant pairs. A quarter of the infants failed to get ''on time''
10 University of Missouri-Kansas City, School of Nursing and
Health Studies, Kansas City, MO, USA
testing. Predictors of ‘‘on time’’ testing included being
informed about EID by providers when pregnant,
perceiving less HIV stigma, and mother’s level of education.
Predictors of ‘‘very late’’ testing (C12 weeks of age)
included not being informed about EID by providers when
pregnant and living farther from services. Findings
highlight the importance of ensuring that health care providers
actively and repeatedly inform HIV? mothers of the
availability of EID services, reduce stigma by frequently
communicating judgment free support, and assisting
mothers in early planning for accessing EID services. Extra
care should be focused on engaging mothers with less
formal education who are at increased risk for seeking
‘‘late’’ EID testing. This study offers clear targets for
improving services so that all HIV-exposed infants can be
properly engaged in EID services, thus increasing the
potential for the best possible outcomes for this vulnerable
Keywords HIV/AIDS EID PMTCT
prevention Infants Global health
Early infant diagnosis (EID; infant B6 weeks of age) of
HIV infection that facilitates prompt treatment of HIV?
infants is a critical component of prevention of
mother-tochild transmission (PMTCT) efforts. EID is especially
important in Kenya where HIV prevalence among pregnant
women is 6.2 % [
] and 15 % of infants born to HIV?
mothers become infected [
]. In 2008 the Children with
HIV Early ART (CHER) study provided evidence that
early antiretroviral therapy (ART) initiation (before
12 weeks) reduced mortality by 76 % and slowed the
progression of HIV by 75 % by improving long-term viral
suppression and weight for age scores [
]. These findings
prompted new World Health Organization (WHO)
guidelines to treat all HIV? infants under age 2 rather than
waiting for immunologic thresholds to be reached [
Initiating ART early and suppressing the virus before
significant deterioration of the immune system occurs,
preserves immune function to prevent clinical disease
], improves gross motor and
neurodevelopmental profiles , and can reduce the presence of viral
reservoirs in adolescence [
]. Thus, EID is critical to the
early identification, treatment, and long term health of
these infants. EID also provides reassurance to the mothers
of infants who remain HIV negative  which has been
associated with improved infant bonding [
Despite the obvious benefits of receiving EID services,
UNAIDS estimates that less than 40 % of HIV-exposed
infants actually receive services within their first 2 months
of life [
]. Eighteen studies from across East Africa have
reported on the proportion and/or age of HIV exposed
infants who are enrolled in EID [usually defined as age
when a dried blood sample (DBS) was provided] [
Estimates of uptake from these studies range from 25 %
] to 88.3 % [
] with age of first DBS ranging from a
median of 5.6 weeks [
] to 5 months [
]. While the
National AIDS Control Council of Kenya (NACC)
estimates that EID coverage in Kenya reached 45 % of eligible
infants in 2013 , estimates from individual Kenyan
studies range widely from a low of 40 % up to a high of
87 % [
18, 27, 28
]. Median age of enrollment in the few
Kenyan studies that tracked it ranged from between
8 weeks to 5 months [
]. The limited coverage and
shortcomings of current EID services means that many
HIV? infants are not diagnosed early enough to fully
benefit from available treatment .
Despite the importance of early detection to signal
treatment initiation for HIV? infants, EID services in East
Africa have received considerably less attention than other
aspects of PMTCT care. Especially lacking are studies that
investigate predictors of ‘‘on-time’’ (infant B6 weeks of
age) engagement in EID that would help to identify factors
that put infants at risk for late engagement and
mutable targets for intervention. We could identify only 3
peer-reviewed published studies and one publically
available master’s thesis conducted in East Africa [
17, 22, 25,
] that report on predictors of engagement in EID. None
were conducted in Kenya. Combined, these studies
highlight several potentially important predictors of timely
engagement in EID (infant B6–8 weeks of age),
specifically: mother’s current ART status (being on ART [
not being on ART [
]; mother’s engagement in PMTCT
during pregnancy [
]); mother’s access to an independent
source of income [
]; having C2 previous children [
having fewer concerns that her child will face
discrimination if HIV? [
]; and delivering in a government facility
]. While far from definitive, these studies offer some
preliminary evidence for the importance of these predictors
in timely EID engagement. Nevertheless, more studies are
needed. Also lacking are studies that explore predictors of
‘‘very late’’ engagement (C12 weeks of age) when the
benefits of costly ART treatment are compromised.
Predictors of really late engagement might be quite different
than those that predict early engagement and are critical for
the development of outreach and retention efforts.
This study draws on baseline data from an on-going
cluster randomized study of an intervention to improve
EID services at six sites across Kenya [
predictors of ‘‘on time’’ (infant B6 weeks of age) EID
engagement and ‘‘very late’’ (infant C12 weeks of age) are
examined in a large and diverse sample.
This study sample included 756 HIV-infected mothers and
their HIV-exposed infants (mother-infant pairs) enrolled in
early infant diagnosis (EID) programs at six Kenyan
government hospitals between February 2014 and June 2015.
The hospitals ranged in size (provincial, county, and
subcounty level), geographic regions (2 western, 2 central and
2 coastal), and population density (3 urban and 3 peri-urban
sites). Participants were enrolled in a larger RCT
evaluating the impact of the HIV Infant Tracking System
(HITSystem) web-based intervention (35; Clinical Trials
Id: NCT02072603). The focus of this study, predictors of
age at EID enrollment, is neither an outcome of the larger
study nor targeted by the HITSystem (a system level
documentation and patient tracking system with text
reminders for mothers) that seeks to improve
communication and accountability of all stakeholders once infants
are enrolled in EID services.
Participant Eligibility and Consent
HIV-infected mothers whose infant is \18 months of age
at the time of initial enrollment in EID and presents for
care through the maternal and child health (MCH)
department at each site were eligible for inclusion in this
dataset. Data from mothers \18 years of age or who
present for care through other departments (e.g., Pediatric
Inpatient Ward) were not included in analyses. Mothers
were informed about the study during EID enrollment by
trained research or clinical staff, and those wanting to
participate provided written informed consent prior to
enrollment or completion of the baseline survey. Less than
2 % of mothers declined participation. The study protocol
was reviewed and approved by the Institutional Review
Boards at the Kenya Medical Research Institute (protocol
#2726), and the University of Kansas Medical Center
During the first EID enrollment visit, a brief survey was
conducted with each consenting mother to collect basic
demographic data and other variables of interest including:
maternal age, parity, education level, partner status, partner
support, income level, disclosure status, HIV stigma,
violence, mother’s current HIV care status, how she was
informed about EID services, EID knowledge, travel time
to hospital and associated costs, and financial concerns.
Other data (i.e., infant’s date of birth, antenatal care,
maternal ARV prophylaxis regimens, and postpartum
infant prophylaxis) was abstracted from patient charts.
The dependent and potential predictor variables are
described in Table 1.
The goal of our analyses was to identify predictors of (1)
‘‘on-time’’ (B6 weeks of age) versus ‘‘late’’ (C7 weeks) and
(2) ‘‘on-time’’ (B6 weeks) versus ‘‘very late’’ (C12 weeks)
infant testing and quantify their association with the odds of
‘‘on-time’’ or ‘‘very late’’ testing. For descriptive purposes
we compared the ‘‘on-time’’ and ‘‘late’’ (tested at or after
7 weeks of age) groups by computing their respective
medians and standard deviations on the quantitative
variables and frequencies on the categorical variables. Similarly,
the ‘‘very late’’ group (a subset of the ‘‘late’’ group) was
compared with the rest of the ‘‘late’’ group.
We used logistic regression to examine associations
between the variables and the dichotomous dependent
variables. Including the full set of variables in a logistic
regression model would result in too large a model given
the limited numbers in the ‘‘late’’ and ‘‘very late’’ groups
and potentially raise multicollinearity concerns. Thus we
followed a two-step model selection and fitting process for
both dependent variables [
First we used the ‘lasso’ (least absolute shrinkage
selection operator) [
] to select a subset of candidate
predictors for each dependent variable. The lasso is similar
to ridge regression in imposing a constraint on the
magnitude of the regression coefficients but tends to shrink
some coefficients to zero, thereby providing variable
selection without the drawbacks of selection methods
based on p values.
We implemented the lasso for logistic regression using
the ‘glmnet’ package in R [
]. All variables except study
site (a six-category control variable to be included in the
final logistic regression models regardless of association
with the dependent variables) were included in the lasso
modeling; two dummy variables were created to model
education level. For the ‘‘on-time’’ versus ‘‘late’’ model we
set the lasso tuning parameter to select 12 candidate
predictors, resulting in about 10 late observations per variable
(including the site variable, equivalent to five dummy
variables) in the final logistic regression model. Given the
small size of the ‘‘very late’’ group, we took a less
conservative approach and set the tuning parameter in the
‘‘very late’’ model to select seven candidate predictors,
resulting in five ‘‘very late’’ observations per variable in the
final logistic regression model [
(n = 186) with missing data on any variable, including the
individual stigma, support, and violence items, were
excluded from this step of the analysis, leaving 570
observations in the lasso models for both dependent
Next we fit the final logistic regression model for each
dependent variable using the LOGISTIC Procedure in SAS
9.4, including study site and the candidate predictors
selected in the lasso step. The lasso yields regression
coefficient estimates that are biased toward zero, a
limitation that can be addressed by re-fitting the lasso-selected
model without the lasso constraint [
]. Observations with
missing data on any candidate predictor were excluded
from the final models, leaving 630 (with 168 ‘‘late’’) for the
model examining ‘‘on time’’ (B6 weeks of age) versus
‘‘late’’ and 710 (with 67 ‘‘very late’’) for the ‘‘very late’’
(C12 weeks of age) model. Firth regression was used for
the ‘‘very late’’ variable to avoid quasi-complete
Descriptive statistics for the total sample shown in Table 2.
Nearly three quarters (73.8 %) of the mothers in our
sample were able to secure testing for their infant at or
before 6 weeks of age, however over a quarter (25.8 %)
were not. Rate of ‘‘on time’’ testing varied greatly by study
site. Most sites (4 of 6) had the majority of their infants
tested at or before 6 weeks (66–92 %). However, one
periurban and one urban site evidenced much poorer rates of
on-time testing with only 47–59 % of infants getting tested
before 7 weeks of age. Average age of mothers who
brought their child ‘‘on time’’ versus ‘‘late’’ was very
similar, however mothers who came ‘‘late’’ were more
likely to: have lower levels of education, not have
disclosed their HIV? status to anyone, not have been on ART
Infant age in weeks based on number of days between the date of ‘‘On-time’’: 0–6 weeks vs. C7a
birth and DBS collection ‘‘very late’’: C12 weeks vs. 0–11
Study site where mother enrolled
Mother’s current age
Number of children currently in mother’s care
‘‘What is the highest level of education you have completed?’’
‘‘Are you currently with a partner?’’
‘‘My partner/family members support my efforts to come to the
hospital for my own health’’
‘‘My partner/family members support my efforts to come to the
hospital for my infant’s health’’
Average weekly income
‘‘To whom have you disclosed your HIV status?’’
‘‘Medical staff treat me badly because I am HIV positive’’
‘‘Medical staff look down on me because I am HIV positive and
had a baby’’
‘‘Has your partner mistreated you physically or psychologically
in the past week?’’
‘‘Has any family member mistreated you physically or
psychologically in the past week?’’
‘‘How did you learn about EID?’’
Five ‘true’ or ‘false’ statementsf
Number of minutes
Continuous variable; years
Continuous variable; number
0 (No formal education), 1 (Partial/completed
primary), or 2 (Partial secondary or beyond)c
0 (No) or 1 (Yes, regardless of cohabitation status)
1 (strongly disagree) through 4 (strongly agree)
\750 Kenya Shillingse or C750 Kenya Shillings
0 (No one) or 1 (Anyone)
1 (strongly disagree) through 4 (strongly agree)
0 (No to both items) or 1 (Yes to either item)
0 (anyone else) or 1 (a health care worker while
Correct answers summed to create a 0 (lower) to 5 (higher) knowledge scale Converted to hours for modeling 2144
a Cut-offs based on findings from the CHER study3 that demonstrated the benefits of early ART initiation in reducing mortality and HIV
b Included as a control variable in the analysis
c Based on feedback from our in-country colleagues, the six original educational level categories were collapsed into the more meaningful
d Responses to items were averaged to create scales used in modeling
e Approximately $7.74 USD
f Questions related to knowledge about testing and follow-up strategy for HIV testing among infants
before becoming pregnant, not have learned about EID
from health care staff during PMTCT, report longer travel
time to the hospital, and more concern about having
sufficient funds to get to the hospital. The majority of mothers
‘‘agreed’’ or ‘‘strongly agreed’’ that their partner/family
members support their efforts to come to the hospital for
their infant’s health (‘‘on time’’ 85 %, ‘‘late’’ 73 %), but
more ‘‘late’’ mothers ‘‘disagreed’’ or ‘‘strongly disagreed’’
(32 %) with this statement than mothers who were ‘‘on
time’’ (21 % p [ 0.05; not displayed in Table 2).
Similarly, the majority of mothers ‘‘disagreed’’ or ‘‘strongly
disagreed’’ with the statement that ‘‘Medical staff look
down on me because I am HIV positive and had a baby’’
(‘‘on time’’ 87 %, ‘‘late’’ 86 %), but more ‘‘late’’ mothers
‘‘agreed’’ or ‘‘strongly agreed’’ (5 %) than mothers who
were ‘‘on time’’ (2 % p \ 0.04; not displayed in Table 2).
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When compared to the rest of the mothers in the ‘‘late’’
group (n = 131), mothers in the ‘‘very late’’ (n = 73)
subset were less likely to have sought services in an urban
site (56 vs. 71 %, p = 0.033), disclosed to anyone (81 vs.
92 %, p = 0.024), been on ART prior to pregnancy (26 vs.
43 %, p = 0.027), and learned about EID from a health
care worker (66 vs. 80 %, p = 0.024). The ‘‘very late’’
group also had a longer median travel time [60 min (IQR
30–90) vs. 30 min (30–60), p = 0.009] and higher median
scores on the money worries item [3 (IQR 2–4) vs. 2 (1–3),
p = 0.026]. The two groups were similar on the remaining
descriptive variables in Table 2.
Of the variables analyzed in the lasso stage, the following
12 were selected as candidate predictors for the model
examining ‘‘on time’’ versus ‘‘late’’ infant testing:
education level (two dummy variables), maternal age, travel time
to hospital, concern about money for transportation,
disclosure, how mother was informed about EID, stigma,
social support, violence, income, and partner status. The
seven candidate predictors selected in the lasso step for
‘‘very late’’ enrollment were education level (two dummy
variables), maternal age, travel time to hospital, concern
about money for transportation, disclosure, how mother
was informed about EID, and social support.
Results of the final logistic regression models are
provided in Tables 3 and 4. Area under the ROC curve was
0.72 for the ‘‘on time’’ model and 0.79 for the ‘‘very late’’
model, indicating moderate to good predictive power.
Predictors of ‘‘On-time’’ Infant Testing
At a = 0.05 there were five statistically significant
predictors of ‘‘on-time’’ testing (in addition to study site,
included as a control variable). The strongest predictor was
how the mother was informed about EID, with those
informed by a health care worker during pregnancy having
three times the odds of ‘‘on-time’’ testing as those informed
by another source. The odds of on-time testing were about
twice as high for mothers with at least partial primary
education (vs. no formal education), and 3.5 times as high
for those with at least partial secondary education. Higher
scores on the stigma measure were associated with lower
odds of ‘‘on-time’’ testing, with a reduction in odds of
22 % per 1-SD higher score on the stigma scale.
Predictors of ‘‘Very Late’’ Infant Testing
As with ‘‘on-time’’ vs. ‘‘late’’ testing, the strongest
predictor of ‘‘very late’’ (C12 weeks of age) testing was how
the mother was informed about EID; odds of ‘‘very late’’
testing were nearly 70 % lower for mothers informed by a
health care worker during pregnancy. Odds of ‘‘very late’’
testing were 1.5 times higher per additional hour of
reported travel time to the hospital. Study site was the only
other statistically significant predictor of ‘‘very late’’
This study explored rates and predictors of ‘‘on time’’
versus ‘‘late’’ and ‘‘very late’’ engagement in EID services
among a large sample of mother-infants dyads seeking care
at six health care facilities in Kenya. Consistent with other
East African studies [
14, 16, 24
], nearly three quarters of
mothers secured EID testing for their infant before 7 weeks
of age. Nevertheless, more than a quarter of infants who
95 % CI for aOR
needed testing did not receive it in a timely manner. Delays
in initiation of EID testing compromise the effectiveness of
life sustaining ART treatment for HIV-infected infants [
] and contribute to poor health outcomes in this
vulnerable population . Early infant testing is also a
cornerstone in achieving the global goals of closing the
treatment gap for eligible infants and preventing child
mortality due to HIV [
Descriptive analyses revealed significant variation of
‘‘on time’’ testing by clinic site with 2 of 6 facilities
reporting that only about half of their infants had been
tested before 7 weeks. Why these specific clinics (one
periurban, one urban from different regions) struggled to
achieve testing rates seen in other similar facilities is
unknown, but we assume they are specific to the sites
themselves and as such we controlled for site in the logistic
regression analyses. While not directly examined in this
study, we have observed this same pattern in our
experience working to scale-up novel system-level interventions
across multiple sites. Facilities often have their own unique
barriers (e.g., lack of space, consistent medication supply
and/or poor coordination between different clinics),
cultures (e.g., stigmatizing beliefs, established procedures that
contradict care guidelines) and staffing challenges (e.g.,
providers who lack knowledge or motivation) that decrease
the likelihood of meeting clinical guideline goals [
Future studies should explore site-specific barriers to EID
engagement to better inform needed changes.
Results of the logistic regression analyses revealed that
mothers who were informed about EID services by a
healthcare provider during their pregnancies had three
times the odds of bringing their infant for testing before
7 weeks of age as mothers who learned about EID from
other sources. Clearly mothers had to be engaged in
PMTCT and/or other prenatal care to have had the
opportunity to be informed about EID during their
pregnancies which has been highlighted in prior research [
This finding underscores the critical role that healthcare
providers play in engaging women early and retaining them
throughout their pregnancies to ensure that they are linked
to EID services after giving birth. Ensuring continuity of
care is critical, yet in most settings prenatal care, delivery,
EID and HIV care services are provided by separate
provider groups who are located in several different clinics
often housed in different sections of health centers. This
puts the burden on mothers to stay engaged in care by
finding their way to the next clinic, establishing new
relationships with new providers, and adapting to a new
setting and schedule. Our findings reinforce other work [
23, 44, 45
] that has highlighted the need for co-locating
services and linking mothers to the next clinic or provider
group as essential to improving ‘‘on-time’’ EID service
utilization. Other options include task shifting [
that the same staff follow mothers all the way from
PMTCT to EID services and/or outreach [
mothers during transitions to ensure that they stay engaged.
Mothers with less formal education were found to be at
increased risk for seeking ‘‘late’’ EID testing. Like findings
in PMTCT engagement and retention [
with less education experienced a whole host of additional
barriers to seeking care, which are also likely at play here.
Additional outreach and retention efforts focused on
engaging these mothers will be necessary.
Mothers who perceived less stigma from health care
providers for being HIV? and having a baby were
considerably more likely to seek ‘‘on-time’’ testing for their
infant. This finding is consistent with other studies that
have demonstrated the negative impact of perceived stigma
on EID treatment engagement [
], sharing of fertility
], and ART adherence . It also highlights
the importance of ensuring that all providers send a
consistent and supportive message about childbearing options
to prevent patient disengagement from care which in turn
leads to worse outcomes for mother, partners and infants
Predictors of ‘‘very late’’ (C12 weeks of age) infant
testing included being informed by a healthcare provider
about EID during pregnancy and travel time to the hospital.
Like the earlier ‘‘on-time’’ findings, results of this analysis
highlight the critical role that providers play with the odds
of seeking ‘‘very late’’ infant testing being 70 % lower for
mothers who were informed by a healthcare provider while
they were pregnant. Not surprisingly, living farther away
from the hospital greatly contributed to ‘‘very late’’ seeking
of EID services. Enhancing options for mothers who live
great distances from EID services, like increasing the
number of EID clinics and/or developing mobile EID
services, would address this known barrier. However, limited
resources in an already overburdened Kenyan healthcare
system limit the likelihood of these options coming to
fruition. Other more cost effective approaches, like small
stipends for mothers to pay for transport and
accommodations at or near the hospitals might be effective and are
already being used to support other health behaviors (e.g.,
ART adherence) [
]. At the very least, providers should
start early to develop a plan with women to facilitate early
This study makes an important and novel contribution to
the literature, but it is not without its limitations. Chief
among them are that all of the mothers in this study did
eventually present for EID services. We do not have any
information about mothers who never sought services, nor
do we know if the group of users of the services in this
study represents a small or large proportion of the total
number of mothers of HIV-exposed infants. Future studies
should explore what proportion of all HIV-exposed infants
receive EID services, as well as, what predicts
This study found that a quarter of infants in EID services at
six Kenyan hospitals failed to get tested ‘‘on time’’ (before
7 weeks of age). Findings highlight the importance of
ensuring that health care providers actively and repeatedly
inform HIV? mothers of the availability of EID services,
reduce stigma by frequently communicating judgment free
support, and assist mothers in early travel planning to
access EID services after their babies are born. Extra care
should be focused on engaging mothers with less formal
education who are at increased risk for seeking ‘‘late’’ EID
testing. Getting all HIV exposed infants engaged in EID
services and tested before 6 weeks is critical to optimize
HIV pediatric outcomes. This study offers clear targets for
improving outreach and service integration that could help
to make this important goal a reality.
Acknowledgments Funding for this study was provided by private
donations to Global Health Innovations and the National Institutes of
Child Health and Human Development, R01HD076673
Compliance with Ethical Standards
Conflict of Interest The authors have no conflict to disclose.
Open Access This article is distributed under the terms of the
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tivecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
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