Preprint: Please note that this article has not completed peer review.
Is caregiver sex associated with HIV infection among
orphans and vulnerable children in Tanzania?
Learning from the USAID Kizazi Kipya Project
CURRENT STATUS:
ACCEPTED
Amon Exavery
Pact Tanzania
aexavery@gmail.comCorresponding Author
ORCiD: https://orcid.org/0000-0001-8545-1801
John Charles
Pact Tanzania
Erica Kuhlik
Pact Inc.
Asheri Barankena
Pact Tanzania
Alison Koler
Pact Tanzania
Levina Kikoyo
Pact Tanzania
Elizabeth Jere
Pact Tanzania
DOI:
10.21203/rs.2.14365/v2
SUBJECT AREAS
Health Policy
KEYWORDS
Orphans, children, OVC, HIV/AIDS, caregiver, sex, at risk populations, HIV testing
services, USAID Kizazi Kipya, Tanzania
1
Abstract
Background Tanzania has met only 50.1% of the 90% target for diagnosing HIV in children. Contextspecific strategies are necessary to find the hidden children for HIV testing. This study assesses the
association between caregiver sex and HIV status of orphans and vulnerable children (OVC). Methods
Data originate from the community-based, USAID-funded Kizazi Kipya Project, which works towards
increasing OVC’s and their caregivers’ uptake of HIV/AIDS and other social services in Tanzania.
Included in this study are 39,578 OVC ages 0–19 years who the project served during January-March
2017 in 18 regions of Tanzania and who voluntarily reported their HIV status. Data analysis involved
multi-level logistic regression, with OVC HIV status as the outcome and caregiver’s sex the main
independent variable. Results Three-quarters (74.3%) of the OVC included in the study had female
caregivers, and their overall HIV prevalence was 7.1%. The prevalence was significantly higher
(p<0.001) among OVC with male caregivers (7.8%) than among OVC with female caregivers (6.8%),
and indeed, multivariate analysis showed that OVC with male caregivers were significantly 40% more
likely to be HIV-positive than those with female caregivers (OR=1.40, 95% CI 1.08–1.83). This effect
was the strongest among 0–4 year-olds (OR=4.02, 95% CI 1.61–10.03), declined to 1.72 among 5–9
year-olds (OR=1.72, 95% CI 1.02–2.93), and lost significance for children over age 9 years. This effect
was adjusted for OVC sex and nutritional status; caregiver marital status, education level, and HIV
status; family’s place of residence, size, wealth quintile, and health insurance ownership; and coresidence of multiple OVC. Conclusion OVC in Tanzania with male caregivers have a 40% higher
likelihood of being HIVpositive than those with female caregivers. HIV risk assessment activities
should target OVC with male caregivers, as well as OVC who have malnutrition, HIV-positive
caregivers, or caregivers who do not disclose their HIV status to community volunteers. Further,
younger HIV-positive OVC are more likely to live in rural areas, while older HIV-positive OVC are more
likely to live in urban areas. These factors should be integrated in HIV risk assessment algorithms to
enhance HIV testing yields and pediatric case-finding in the OVC population in Tanzania.
Background
The human immunodeficiency virus (HIV) that causes acquired immunodeficiency syndrome (AIDS)
2
(1,2) remains a global threat (3,4). The UNAIDS estimates that there are 37 million people living with
HIV/AIDS (PLHIV) worldwide, a majority of whom are in developing countries, more than half are
women, and 5.7% are children under 15 years of age (5). In 2016, UNAIDS estimated Tanzania’s
overall HIV prevalence among adults at 4.7% (6), and in 2018, UNICEF estimated an HIV prevalence of
0.4% among children (7) under age 15 years in Tanzania (8). This prevalence was also reported by
the 2016‒2017 Tanzania HIV Impact Survey (9). Further estimates by the UNAIDS show that in 2018,
there were 92,000 (72,000–110,000) children living with HIV, 8,600 (6,500–13,000) children newly
infected with HIV, and 5,400 (3,200–8,900) child deaths due to AIDS in Tanzania (10).
Methods of and factors leading to transmission of HIV in children
Vertical transmission, commonly known as mother-to-child transmission of HIV (MTCT) is the
predominant mode through which children acquire HIV (11,12). Other routes include blood
transfusions and the use of contaminated sharp objects (13). In communities affected by AIDS,
children who have lost parents and family members become more vulnerable to HIV infection from
the lack of caregivers, lack of access to school and inability to stand for their rights; in these cases,
children can be infected through sexual abuse or rape (14). Prevention of mother-to-child
transmission of HIV (PMTCT) services during pregnancy, delivery and breastfeeding can stop MTCT
(15), but relying primarily on this approach does not address the challenge of maternal
seroconversion during late pregnancy and breastfeeding (16,17) and creates coverage gaps (18).
In the areas heavily affected by HIV/AIDS, such as sub–Saharan Africa, the association of orphanhood
and AIDS is well established (19–21). Orphanhood, which occurs when a child under 18 years of age
loses one or both parents (11), increases HIV risk in children. For example, orphans are two to three
times more likely than their non-orphaned counterparts to have acquired HIV by the time they reach
adolescence (22,23). In 2016, Tanzania had 2.6 million orphans from all causes, 810,000 of whom
were orphaned by AIDS (24). The magnitude of orphanhood in the country increases with age, from as
low as 1% in children under age 2 years to as high as 18% in children aged 15–17 years (25).
Orphanhood also varies by geographical location, with the highest rates in Iringa (13%), Ruvuma
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(12%), and Mara (12%) regions (25). However, widespread access to antiretroviral therapy (ART) has
led to increased survival among HIV-positive caregivers, reducing cases of children orphaned due to
HIV (26).
In this context, pediatric HIV testing, care and treatment must receive the same attention and
resources as PMTCT (27). Pediatric HIV care has lagged as a result of weak and fragmented systems
for pediatric case finding. Consequently, many children die of HIV, often undiagnosed (27).
The 90-90-90 targets
In 2014, at the 20th International AIDS Conference in Melbourne, Australia, UNAIDS launched the 9090-90 targets for HIV/AIDS programming, which state that by 2020, 90% of all PLHIV will know their
status, 90% of people diagnosed with HIV will be on ART, and 90% of people on ART will achieve viral
suppression (28). Essentially, early identification, prompt and sustained treatment, and viral
suppression can prevent the transmission of HIV, thus reducing HIV incidence at a population level
(29).
While the first 90 is the parent of the subsequent 90s in the cascade, its performance gap is largest
(30), with only 75% of people worldwide knowing their status in 2017 (31). Tanzania’s progress
towards achieving the 90-90-90 targets mirrors the global trend at 61-94-87 among adults (9).
Progress in the pediatric population also lags behind, with only 50.1% of Tanzanian children living
with HIV (CLHIV) diagnosed (9). Therefore, a priority for the country is identifying and linking to care
all individuals, and particularly children, who could be infected but are unaware of their HIV status (9).
Gaps in testing coverage and efficacy for orphans and vulnerable children (OVC)
Most HIV-positive children are diagnosed late and at an advanced stage of disease progression (32).
Further, evidence shows that without ART, 53% of CLHIV die before their second birthday (33). Most
of these children are born to women who do not access or who only partially access PMTCT services
(34). A substantial proportion of these deaths could have been prevented if the children were
identified, diagnosed, and initiated on treatment. But, pediatric HIV case-finding remains challenging
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(34,35), particularly access to HIV testing services (HTS) for children.
Factors associated with HIV status in children have been identified in previous studies and can
demonstrate heightened risk for acquiring HIV, thus an increased need to focus HTS for specific
groups. For example, maternal CD4 count during pregnancy, mixed feeding, and being hospitalized
since birth were noted among children born to mothers in PMTCT programs in Zimbabwe (36). A study
among HIV exposed children in Uganda observed that infants who did not receive ART prophylaxis at
birth and children delivered outside the health facility were more likely to be HIV-positive than their
counterparts (37). Significant association between malnutrition and HIV status in children has been
observed in many countries, including Burkina Faso, Ghana, Rwanda, and India (38–42). Other studies
have noted a higher likelihood of HIV infection in children living with HIV infected caregivers (43).
However, the literature lacks adequate evidence of HIV prevalence among OVC and corresponding
risk factors. The association between caregiver sex and OVC HIV status is missing. Given the links
between orphanhood and HIV, knowing how caregiver sex and other individual and household
characteristics associate with OVC HIV status is crucial for informing pediatric case-finding strategies
to ultimately close the pediatric gap in the first 90.
Tanzania offers index testing services to children if the biological mother is HIV-positive or if the
father is HIV-positive and reports that the child’s mother is HIV-positive, deceased, or of unknown
status and/or that a biological sibling under age 15 years is HIV-positive (44). However, if the father
comes for HTS and tests HIV-negative, nothing else is enquired under the current index testing
algorithm. While children with female caregivers are further covered by HTS under the current index
testing algorithm, children under the direct care of these fathers will be missed. The problem is
compounded by a lower predilection for health-seeking behavior, including HIV testing, among men
than among women (45,46). This highlights a need for a critical analysis of whether caregiver sex is
associated with HIV infection in children, especially OVC. This will inform further targeted efforts
toward diagnosis targets and to further improvement in pediatric case-finding modalities for universal
coverage of HTS for children.
Methods
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Data source
Data are from Pact’s community-based, USAID-funded Kizazi Kipya Project in Tanzania (2016–2021).
The project aims to increase the uptake of HIV and other health and social services by OVC and their
household members. Community Case Workers (CCWs) collected the data from caregivers’ selfreports during beneficiary enrollment using the project’s Screening and Enrollment, and Family and
Child Asset Assessment (FCAA) tools. Beneficiaries are enrolled into the project if their household
meets one or more of the 14 enrollment criteria that cover household vulnerabilities related to HIV:
household is headed by a child (under age 18 years), household is headed by an elderly caregiver
(age 60 years or older), household cares for at least one single or double orphan, caregiver is
chronically ill and unable to meet his/her children’s basic needs, caregiver is a drug user, caregiver or
an adolescent age 10-19 years in the household is a sex worker, at least one adolescent girl age 1019 years in the household is sexually active, adolescent girl age 10-19 years in the household is
pregnant or has a child of her own, at least one household member is HIV-positive, at least one child
in the household has tuberculosis, at least one child in the household is severely malnourished, at
least one child in the household has been or is being abused or at risk of abuse, at least one child in
the household is living and/or working on the streets, and at least one child in the household is
working in mines. These criteria are equally applied for all implementation areas and age groups.
Study area
Data for this study originated from 18 regions of Tanzania where the USAID Kizazi Kipya project had
implemented enrollment activities in 2017: Dar es Salaam, Dodoma, Geita, Iringa, Kagera, Katavi,
Mbeya, Mjini Magharibi, Morogoro, Mtwara, Mwanza, Njombe, Pwani, Rukwa, Ruvuma, Singida,
Tabora, and Tanga. Of these regions, Mjini Magharibi has very low adult HIV prevalence (0.6%), while
Njombe has the highest in the country (11.4%) according to the recent Tanzania HIV Impact Survey
(9). A total of 67 district councils (48 rural and 19 urban) considered high HIV burden from the 18
regions were included in this study.
6
Study population
The study population encompassed 39,578 OVC who were enrolled in the USAID Kizazi Kipya Project
from January to March 2017, and had complete information on their HIV status and their caregivers’
characteristics. In the context of the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR), an
OVC is a child, ages 0-17 years, who is either orphaned (i.e. lost one or both parents to HIV/AIDS) or
made more vulnerable because of HIV/AIDS (47). For programming purposes, the USAID Kizazi Kipya
Project extends the OVC age to 19 to include all adolescents (48). Therefore, OVC included in this
study were aged 0–19 years. The majority of the OVC were under age 15 years (n = 27,935, 70.6%).
USAID Kizazi Kipya defines a caregiver as a guardian with the greatest responsibility for the daily care
and rearing of one or more OVC in a single household. A caregiver is not necessarily a biological
parent. Only one caregiver per OVC was included in this study: the person identified as having
primary responsibility for caring for the child, i.e., the primary caregiver. References to caregiver in
this manuscript denote each child’s singular, primary caregiver.
Study design
The study design constituted a cross-sectional secondary analysis of the existing FCAA data, as
described above. The data were collected once during beneficiary screening and enrollment.
Variables
OVC HIV status as reported by the caregiver was the outcome or dependent variable and was
measured through the two categories of negative and positive. For computational purposes, the
variable was organized as follows: (see Formula 1 in th Supplementary Files)
The main independent variable for this study was sex of the caregiver, measured through the two
categories of male and female. Other independent variables included OVC sex, OVC age (in years),
OVC nutritional status, caregiver age (in years), HIV status of the caregiver, education of the
caregiver, family size, whether some or all the family members are covered by health insurance,
whether the caregiver is physically or mentally disabled, household wealth quintile, and type of
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residence (rural or urban). Rural residence included all those living in district councils, whereas those
living in township, municipal or city councils were considered as urban residents.
Family size (i.e., number of people living in the same household) was divided into three categories:
households with 2–3 members, households with 4–13 members, and households with 14 or more
members. This was based on an explorative analysis of OVC HIV prevalence by family size as a
discrete variable. Families with similar prevalence were grouped together, thus the categories. The
smallest household had two occupants – the OVC and his/her caregiver.
Nutritional status was assessed using mid-upper arm circumference (MUAC) measuring tapes. MUAC
is recommended for community-based screening of acute malnutrition (49). Interpretation of the
readings was guided by the standard definitions of the colors, whereby the person being assessed is
nourished if the reading falls in the tape’s green zone, the person being assessed is moderately
undernourished if the reading falls in the yellow zone, and the person being assessed is severely
undernourished if the reading falls in the red zone (50).
Wealth quintile was constructed using principal component analysis (PCA) of household assets to
determine household socio-economic status (51). Five wealth quintiles were formed, ranging from the
lowest quintile (Q1) for the poorest households, to the highest quintile (Q5) for the most well-off
households. Family-owned assets included in the PCA were dwelling materials (brick, concrete,
cement, aluminium, other), livestock (chicken, goats, cows, other), transportation assets (bicycle,
motorcycle/moped, tractor, motor vehicle, other), and productive assets (sewing machine, television,
couch/sofa, cooking gas, hair dryer, radio, refrigerator, blender, oven, other).
Data analysis
Data analysis was conducted using Stata version 14.0 statistical software. Exploratory analysis was
conducted through one-way tabulations to obtain distributional features of the respondents in each
variable. Cross-tabulation of OVC HIV status by each of the independent variables was conducted to
assess the variability of OVC HIV prevalence by levels of each of the independent variables. The ChiSquare (χ2) test was used to assess the degree of association between OVC HIV status and each of
8
the independent variables.
Multivariate analysis was conducted using a random-effects logistic regression model due to the
hierarchical or clustered structure of the data (52). The usual assumption of independence of the
observations did not hold because two or more OVC who have the same caregiver, or who reside in
the same household may be correlated. Thus, a multilevel model, which recognizes these data
hierarchies and allows for residual components at each level in the hierarchy, was used (53). This
choice was based on the assumptions that OVC from the same household and caregiver are
dependent in their behavioral, physical, or mental characteristics because they share the same social,
health, and economic resources available at the household level. This is likely to exert a related
influence in their social life and health outcomes.
Five multivariate models were constructed. The first model encompassed the entire study population
of 39,578 OVC ages 0–19 years. The remaining models broke down the study population by age
group: the second model was for 5,217 OVC in the age group 0–4 years, the third model was for
10,457 OVC in the age group 5–9 years, the fourth model was for 12,261 OVC in the age group 10–14
years, and the fifth model was for 11,643 OVC in the age group 15–19 years. The stratification of the
multivariate analysis by OVC age offered a deeper examination, interpretation and comparisons of
the patterns and concentration of the association between caregiver sex and OVC HIV status across
different bands of the OVC age.
All statistical inferences were made at the conventional significance level of 5% (α = 0.05), whereby
any association corresponding with a p-value less than 0.05 was considered statistically significant.
Limitations
Some key variables, such as whether the caregiver was the child’s biological parent, were not
available in the data. Recall bias was possible during data collection because all information (except
for nutritional status, which was measured) was self-reported, though findings suggest that the effect
may be minimal because results are comparable with existing biomedical and clinical studies. Since
this study was cross-sectional in design, temporality cannot be established, which precludes drawing
9
causal inferences from these findings.
Results
Profile of OVC
Three-quarters of the OVC (74.3%) were living with a primary caregiver who was female. These OVC
had caregivers with mean age of 48.7 [SD = 14.1] years. Nearly half (45.1%) of the OVC were living
with married caregivers, and 35.6% were living with widowed caregivers. More than three–quarters of
the OVC (77.2%) had caregivers with primary education. Just over half of the OVC (54.5%) lived in
rural areas. Regarding family size, the majority (75.7%) of OVC were living in families with 4-13
people. Slightly more than a quarter (26.3%) of the OVC were living with HIV-positive caregivers.
Table 1 Profile of OVC
Variable
Number of
OVC (n)
OVERALL
OVC HIV status
Negative
Positive
Caregiver sex
Female
Male
Caregiver age group (in years)
18—29
30—39
40—49
50—59
60+
Mean = 48.7, SD = 14.1, Median = 46, Min = 18, Max = 110
Caregiver marital status
Married or living together
Divorced or separated
Never married (single)
Widowed
Family size
2-3 people
4-13 people
≥14 people
Caregiver mentally or physically disabled?
No
Yes
OVC sex
Female
Male
OVC age group (in years)
0—4
5—9
10—14
10
39,578
36,776
2,802
29,401
10,177
2,280
9,283
11,571
6,847
9,597
—
17,833
5,061
2,584
14,100
9,440
29,944
194
37,967
1,611
20,304
19,274
5,217
10,457
12,261
Percent
OVC (
15—19
Mean = 10.9, SD = 5.0. Median = 11, Min = 0, Max = 19
Caregiver HIV status
Negative
Positive
Undisclosed
Wealth Quintile
Lowest (Q1)
Second
Middle
Fourth
Highest (Q5)
Caregiver education
Never attended
Primary
Secondary or higher
OVC nutritional status (MUAC)
Green (healthy)
Yellow (moderately malnourished)
Red (severely malnourished)
Unknown
Household member(s) has health insurance card
Yes
No
Place of residence
Rural
Urban
11,643
—
21,818
10,398
7,362
10,842
5,348
6,794
7,575
9,019
7,676
30,569
1,333
23,156
1,416
144
14,862
5,813
33,765
21,585
17,993
OVC HIV status by background characteristics
OVC HIV prevalence by each of the independent variables is presented in Figure 1.
Figure 1. Percentage of HIV-positive OVC in Tanzania, by background characteristics, 2017
(n = 39,578)
Overall 7.1% (n = 2,802) of OVC were reported HIV-positive. This proportion varied significantly by
levels of several independent variables. With respect to caregiver sex, OVC HIV prevalence was
significantly higher (p<0.001) among OVC with male caregivers than those with female caregivers
(7.8% and 6.8%, respectively). HIV prevalence was lowest (3.8%) among OVC living with HIV-negative
caregivers and highest (14.1%) among OVC living with HIV-positive caregivers (p<0.001). OVC HIV
status varied significantly by OVC nutritional status (p<0.001), whereby HIV prevalence among OVC
who were severely and moderately undernourished was 21.5% and 17.0%, respectively, and 6.9%
among OVC who were nourished. Caregiver’s marital status was also associated with OVC HIV status
(p<0.001), with OVC HIV prevalence being lowest (6.5%) among OVC with caregivers who were
married or living together and highest (7.9%) among OVC living with caregivers who were never
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married.
HIV prevalence also varied by family size; it was highest among OVC living in households with 14 or
more and 1–3 household members (11.3% and 10.6% respectively) and lowest (6.0%) among OVC
living in households with 4–13 members (p<0.001). With respect to location, HIV prevalence was
significantly higher among OVC living in rural areas than in urban areas (8.2% and 5.7%, respectively)
(p<0.001). As detailed in Figure 2, HIV prevalence among OVC living in rural areas was highest in the
youngest age group (0–4 years) and continued declining as OVC age advanced. After age 15 years,
the OVC HIV prevalence in urban areas surpassed that in the rural areas. The proportion of OVC living
with HIV varied by health insurance ownership, with the prevalence highest (10.8%) among OVC living
in households with health insurance and lowest (6.5%) in households without health insurance.
Figure 2. Rural-urban differentials in HIV prevalence among OVC in Tanzania, by age
group, 2017 (n = 39,578)
HIV prevalence among OVC was not significantly associated with the caregiver’s education level (p =
0.496), household wealth quintile (p = 0.298), OVC sex (p = 0.263), or caregiver disability status (p =
0.555).
Results from the multivariate analysis
Adjusted odds ratios (OR) and their corresponding 95% confidence intervals (CIs) for the association
between caregiver’s sex and OVC HIV status are presented in Table 2.
Table 2. Multivariate random-effects logistic regression models of the association between
caregivers’ sex and OVC HIV-positive status, 2017 (see Supplementary Files)
The overall results show that OVC with male caregivers were significantly and independently 40%
more likely to be HIV-positive than OVC with female caregivers (OR = 1.40, 95% CI 1.08–1.83). This
effect was four times stronger for OVC ages 0–4 years (OR = 4.02, 95% CI 1.61–10.03) and almost
twice as high for OVC ages 5–9 years (OR = 1.72, 95% CI 1.02–2.93). These effects were adjusted for
OVC sex, OVC nutritional status, caregiver marital status, caregiver education, place of residence,
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caregiver HIV status, family size, wealth quintile, and whether some or all household members have
health insurance. The effects also were adjusted for the correlation between OVC who reside in the
same household (co-residence) or OVC with the same caregiver. The intra-class correlation coefficient
(ICC) was 0.85, indicating that the household-level random effect accounted for 85% of the total
residual variance. This meant that OVC were more likely to be HIV-positive if they were residing in the
same household as other OVC.
There were other factors with significant association with OVC HIV status. The largest effect was
exerted by caregiver HIV status, whereby OVC with HIV-positive caregivers were 29.27 times more
likely to be HIV-positive than OVC with HIV-negative caregivers (OR = 29.27, 95% CI 21.04–40.72).
These effects remained statistically significant with their direction unchanged across all OVC age
groups. Similarly, both OVC who were moderately undernourished (OR = 11.03, 95% CI 7.40–16.44)
and severely undernourished (OR = 12.71, 95% CI 4.36–37.06) were more likely to be HIV-positive
than those who were nourished.
OVC in each of the age groups of 5–9 years (OR = 1.35, 95% CI 1.04–1.75), 10–14 years (OR = 1.44,
95% CI 1.11–1.86), and 15–19 years (OR = 1.37, 95% CI 1.05–1.79) were more likely to be reported
HIV-positive than OVC in the youngest age group (0–4 years). A one-person increase in family size
resulted in 18% less likelihood of an OVC being reported HIV-positive (OR = 0.82, 95% CI 0.78–0.87).
OVC living in households without health insurance were 66% less likely than those living in
households with health insurance to be reported HIV-positive (OR = 0.34, 95% CI 0.25–0.45); this
effect remained statistically significant and unaltered in direction across all the OVC age groups.
Overall, OVC residing in urban areas were 29% less likely to be reported HIV-positive than their rural
counterparts (OR = 0.71, 95% CI 0.55–0.91). The magnitude of this effect was the strongest among
the youngest OVC (0–4 years), whose likelihood of being HIV-positive was 84% less in urban than in
rural areas (OR = 0.16, 95% CI 0.06–0.43). The direction of the effect changed among 15–19 year-old
OVC residing in urban areas, who were 59% more likely to be HIV-positive than their rural
counterparts of the same age (OR = 1.59, 95% CI 1.04–2.44).
Discussion
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Linkages between caregiver sex and OVC HIV status
This study assessed how caregiver sex and other individual and household characteristics are
associated with HIV infection among OVC in Tanzania. Findings revealed that OVC with male
caregivers were 40% more likely to be HIV-positive than those with female caregivers. This effect
remained statistically significant even after adjusting for OVC sex, caregiver HIV status, OVC
nutritional status, household family size, caregiver marital status, wealth quintile, place of residence,
health insurance ownership, and household co-residence. In the stratified analysis by OVC age, the
association was strongest among the 0–4 years age group and declined (but with statistical
significance) among 5–9 year-olds. In the older OVC age groups of 10–14 and 15–19 years, the
association declined further and lost statistical significance, although the direction of the association
remained.
Given the Tanzanian cultural context, when a male is the primary caregiver, likely this is because the
child’s mother has died, possibly due to HIV, which increases the likelihood that the child is HIVinfected. The child may have acquired the HIV through MTCT. This has important implications for risk
assessment and referral to HIV testing services (HTS) for children. As noted earlier, orphaned children
living with male caregivers are likely to miss HTS because the current case-finding modalities, like
index testing services, are offered to individuals who are at risk of HIV exposure from the original
client, who is often the mother. Specifically, if an HTS client is a man and tests HIV-negative, the
process stops (44). This leaves a service gap for children and other family members of the male HTS
client who may be at risk or already infected with HIV. Therefore, in view of this association, the
current pediatric case finding strategies may be expanded by considering caregiver sex an imperative
dimension for targeted HTS among OVC.
Additionally, caregiving work has traditionally been viewed as the responsibility of women and girls
(54–56), especially in African communities. These traditional gender norms have been reported to
exclude men and boys from becoming caregivers, thus exacerbating the caregiving burden on women
(54). This is corroborated by this study, in which about three-quarters of the OVC had female
caregivers. Thus, men become caregivers not by choice, but because circumstances dictate (e.g., the
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child’s mother has died, and possibly there is no female relative to care for the children etc.). In this
context, men are likely to provide inadequate or suboptimal care for reasons such as lack of
experience in child-rearing activities., This can result into less protection of the child from HIV risks
and risk-seeking behaviors. Due to traditional occupational gender norms, men generally provide
more economic support to the family than women (57), but not social or direct support in the
caregiving process. Although the level of parental supervision has been acknowledged as an
important factor in preventing and remediating HIV in children and youth (58), evidence of men’s
participation in the whole process of caregiving work is scant (59). There is a known link between HIV
and child abuse and neglect (60) whereby child abuse by male caregivers puts children at a greater
risk of HIV acquisition (61). While this study demonstrates a significant association between caregiver
sex and OVC HIV status, further research is needed to uncover and explain the causal pathways of the
relationship.
Additional risk factors for OVC HIV status
As expected, OVC with HIV-positive caregivers were more than 29 times more likely to be HIV-positive
than OVC whose caregivers were HIV-negative, which is consistent with the literature (43,62–66).
Children primarily acquire HIV from their mothers in utero, during their delivery, or while being
breastfed (12).This maybe a possible mechanism underlying the findings of this study, wherein most
of the OVC in this study had female caregivers, the majority of whom were possibly their biological
mothers. Therefore, although it is important to address barriers against universal coverage of HIV
services to prevent MTCT, HIV risk assessment and referral to HTS and other community case-finding
activities should target OVC whose caregivers are HIV-positive.
Similarly, undernourishment of any kind (moderate or severe) was significantly associated with OVC
HIV-positive status, suggesting compulsory HIV testing for all undernourished children. From the
literature, the relationship between nutrition and HIV is bi-directional (67,68): HIV compromises the
immune system, leading to undernutrition, which, in turn, leads to further immune malfunction that
accelerates HIV transmission and progression to AIDS (69–72). Tanzania protocols already
15
recommend referral of malnourished children to HTS as a case-finding approach. Because such a
large percentage of HIV-positive OVC were undernourished at the time of enrollment, this finding
further emphasizes the importance of integrating nutrition services into community-based OVC
programming and into HIV prevention and treatment programs to enhance OVC health outcomes.
There was also a residence location aspect of the variability in HIV prevalence among OVC in the
study area. The study population was almost evenly split between urban and rural locations, but
urban residence was associated with a 29% lower odds of HIV infection than rural residence, implying
that OVC who reside in rural areas may have higher burden of HIV infection. Rates of HIV prevalence
due to location were highest among OVC ages 0–4 years who resided in rural areas compared to their
urban counterparts in the same age group (9.6% vs. 3.7%; see Figure 2). The rural–urban gap in OVC
HIV prevalence declined consistently with OVC age until prevalence among urban OVC exceeded that
of rural OVC in the 15–19 years age category. This finding could have several interpretations. First, it
could reflect cultural patterns of OVC mobility across extended family households due to vulnerability
in a household, abandonment by the parent or caregiver, or death of one or more parents or
caregivers (73). Younger OVC could be more likely to stay in or be relocated to caregivers in rural
areas, while older OVC could be more likely to move to urban areas for education or economic
opportunities. However, there is little published data on mobility of OVC in Tanzania to substantiate
these possibilities. Further, urban areas may have better exposure to HIV knowledge and awareness
campaigns (74) and better access to health and social services (75,76), which may have contributed
to lower HIV prevalence among OVC in urban than in rural areas. The results suggest a need to target
rural communities with HIV preventive, diagnostic, and treatment services as well as social welfare
and case management services, especially for children under 15 years of age.
Interestingly, as mentioned before, the relationship between place of residence and OVC HIV status
changed direction among the 15–19 years age group, wherein urban residence was associated with a
59% greater likelihood of HIV infection than rural residence. This finding suggests that older OVC are
less likely to be long-term survivors of perinatal infection and are primarily infected through sexual
transmission. While one study found greater HIV infection among 15–24 year-olds in rural than urban
16
areas (77), many other studies around Africa have shown that HIV prevalence among adults is higher
in urban than in rural areas (78–80). This reinforces the need to address risk factors of HIV infection in
orphans and vulnerable adolescents, particularly in urban areas. Further research is required to clarify
the pathway by which rural or urban residence affects HIV risk among OVC.
Finally, the observed higher likelihood of OVC HIV-positive status by health insurance ownership can
be associated with the USAID Kizazi Kipya’s support to the communities, whereby presence of an HIVpositive person in a household was one of the criteria to support health insurance acquisition.
Conclusions
The current study demonstrates that, OVC living with male caregivers are 40% more likely to be HIVpositive than those living with female caregivers. This observation suggests that to benefit the current
pediatric case finding strategies in Tanzania, considering sex of the caregiver as one of the priority
factors indicating where to target case finding efforts may be worthwhile. Further qualitative and
quantitative research is needed to uncover the mechanism responsible for this trend.
At the facility level, health care workers should continue to prioritize index testing for children of HIVpositive biological mothers, but the policy can expand the algorithms with HIV-positive men to identify
at-risk OVC who may reside in their households. HTS providers can include questions to HIV-negative
men about the known HIV status of OVC in their households. And, criteria for enrolment of OVC into
social welfare programming can be reviewed from a gender lens to monitor that OVC living with male
caregivers are not excluded or do not face other enrolment biases.
A such, more gender-sensitive programmatic activities targeting OVC with male caregivers are
needed. For community-based programs such as the USAID Kizazi Kipya, which is built on a social
welfare platform, households where the caregiver is male require additional attention during program
service provision. For example, evidence–based HIV prevention approaches for adolescent OVC are
often integrated into parenting classes that involve the adolescent and the caregiver together.
Information on early infant diagnosis of HIV is integrated into early childhood development
approaches. Prevention of sexual abuse is included in all parenting approaches. It is worth examining
further the extent to which male caregivers are engaged in these parenting activities.
17
Other key dimensions that should be targeted and integrated in HIV programming efforts for
improved OVC health outcomes are individual characteristics such as age and nutritional status;
caregiver characteristics such as HIV status and marital status; household characteristics such as
health insurance status, and family size; and rural versus urban residence. These factors should be
considered when setting targets for community based OVC programs engaged in community-based
pediatric case-finding activities.
Abbreviations
AIDS: acquired immunodeficiency syndrome
ART: antiretroviral therapy
CD4: cluster of differentiation 4
CI: confidence interval
CLHIV: children living with HIV
FCAA: Family and Child Asset Assessment
HIV: human immunodeficiency virus
HTS: HIV testing services
MRCC: Medical Research Coordinating Committee
MTCT: mother-to-child transmission of HIV
MUAC: mid-upper arm circumference
NIMR: National Institute for Medical Research
OR: odds ratio
OVC: orphans and vulnerable children
PCA: principal component analysis
PLHIV: people living with HIV
PMTCT: prevention of mother-to-child transmission of HIV
SD: standard deviation
UNAIDS: Joint United Nations Programme on HIV/AIDS
USAID: United States Agency for International Development
18
Declarations
Ethics approval and consent to participate
Ethics approval was received from the Medical Research Coordinating Committee (MRCC) of the
National Institute for Medical Research (NIMR) in Tanzania (NIMR/HQ/R.8a/Vol.IX/3024). NIMR also
permitted the publication of this specific manuscript (NIMR/HQ/P.12 VOL XXVII/63). Screening and
enrollment of beneficiaries into the USAID Kizazi Kipya Project was entirely voluntary. The FCAA tool
was completed only after each caregiver had signed a statement of an informed consent. All
information was voluntarily provided by the respective OVC’s caregiver.
Consent for publication
Not applicable
Availability of data and materials
The datasets analyzed during the current study are not publicly available due confidentiality
restrictions, but are available from the corresponding author on reasonable request.
Competing interests
The authors declare that they have no competing interests.
Funding
USAID Kizazi Kipya is a five-year project (July 2016 to June 2021) implemented in Tanzania and funded
by PEPFAR through the United States Agency for International Development (USAID). The contents of
this paper; the study design, data collection, analysis, and interpretation; and the manuscript’s
writing remain the sole responsibility of the authors and do not necessarily reflect the views of USAID
or the United States Government.
Authors’ contributions
AE conceptualized the problem, conducted statistical analysis, reviewed the literature, and drafted
the manuscript. JC participated in problem refinement, design, statistical analysis, and critical review
of the manuscripts. EK critically reviewed the manuscript for intellectual content and advised on the
structure. AB, AK, LK, and EJ critically reviewed the manuscripts for intellectual content. All authors
read and approved the final draft of the manuscript.
19
Acknowledgements
A version of this paper was presented at the 19th International Conference on AIDS and STIs in Africa
that took place in Abidjan, Côte D’Ivoire, December 4–9, 2017. Comments received from the
conference are greatly acknowledged. We are thankful to Rachel Elrom from Pact headquarters for
editing the manuscript. Kassimu Tani from Pact Tanzania and Ramadhan Abdul from the Ifakara
Health Institute are acknowledged for reviewing the manuscript.
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Table 2
Due to technical limitations Table 2 is available as a download in the supplementary section.
Figures
29
Figure 1
Percentage of HIV-positive OVC in Tanzania, by background characteristics, 2017 (n =
39,578)
30
Figure 2
Rural-urban differentials in HIV prevalence among OVC in Tanzania, by age group, 2017 (n
= 39,578)
Supplementary Files
This is a list of supplementary files associated with this preprint. Click to download.
Table 2.pdf
Formula 1.pdf
31