Abstract
Backgrounds
In Kenya, mathematical models estimate that there are approximately 220,000 children aged less than 15 years infected with HIV. We analyzed data from the second Kenya AIDS Indicator Survey (KAIS 2012) to estimate the prevalence of HIV infection among children aged 18 months to 14 years.
Methods
KAIS 2012 was a nationally representative 2-stage cluster sample household survey. We studied children aged 18 months to 14 years whose parents or guardians answered questions pertaining to their children by interview. Blood specimens were collected for HIV serology and viral load measurement.
Results
We identified 5162 children who were eligible for the study. Blood was obtained for 3681 (71.3%) children. Among child participants, 16.4% had been tested for HIV infection in the past, and among children with parents or guardians who self-reported HIV-positive status, 52.9% had been tested for HIV infection. Twenty-eight (0.9%) children tested HIV-positive in the survey. Of these, 11 had been previously diagnosed with HIV infection before the survey. All 11 children were in HIV care and receiving cotrimoxazole; 8 were on antiretorivral therapy (ART). Among those on ART, 4 were virologically suppressed.
Conclusions
HIV causes a substantial burden of disease in the Kenyan pediatric population. Although most children who had been diagnosed with HIV before the survey were engaged in care and treatment, they represented less than half of HIV-infected children identified in the survey. Future efforts should focus on identifying infected children and getting them into care and on suppressive ART as early as possible.
Keywords: HIV, children, Kenya, antiretroviral therapy, testing
INTRODUCTION
Pediatric HIV infection is a worldwide public health challenge that disproportionately affects children in the poorest parts of the world. The Joint United Nations Programme on HIV/AIDS estimated that at the end of 2011, 3.4 million children younger than 15 years were living with HIV and that 330,000 had been newly infected in the previous year1,2; 90% of these children were in sub-Saharan Africa.2 Pediatric antiretroviral therapy (ART) coverage in low- and middle-income countries, although rapidly expanding, is relatively low. Worldwide, of the estimated 2 million HIV-infected children in need of ART, only 28% have access to ART, which is substantially lower than ART coverage in adults (58%).2,3 In Africa, of the estimated 3.1 million children living with HIV at the end of 2010, 1.8 million (60%) were estimated to be eligible for ART, but only 387,500 (21%) were receiving it.3
In Kenya, an estimated 220,000 children younger than aged 15 years were living with HIV in 2012.4 Despite efforts to scale-up prevention of mother-to-child transmission of HIV programs, almost 13,000 children were newly infected with HIV in 2011,5 and there were an estimated 13,000 child deaths due to HIV/AIDS.6 HIV is thought to cause 9% of all child mortality in Kenya,7 and many children with severe opportunistic illnesses and undiagnosed HIV infection continue to present to public health care facilities, as has been described elsewhere in Africa.8 Field experience has shown that where pediatric ART is available, the response to treatment of children in low-income countries is as good as that observed in developed countries.9 Thus, many HIV-related deaths among children living with HIV could be prevented through earlier diagnosis of HIV infection and early initiation of ART. However, despite what is known regarding the benefits of ART, treatment scale-up in the pediatric population has been slower than among adults in Kenya. In 2011, mathematical models estimated that fewer than 1 (31.1%) in 3 children who needed ART was receiving it compared to 8 in 10 adults.4
There are a number of reasons for this shortfall. Fear of discrimination has been shown to negatively affect uptake to HIV infant testing and care10–12; a recent study in Zimbabwe, for instance, showed that 42% of the parents/guardians feared discrimination against their children as a result of HIV testing.11 Other factors include lack of integration of antenatal prevention of mother-to-child transmission and pediatric HIV services, which limits the number of children accessing HIV testing in a timely manner; perceived and actual lack of expertise in the care of HIV-infected children; limited availability of some pediatric antiretroviral formulations; the complexities of using ART in the face of multiple co-morbidities (eg, tuberculosis, malaria, malnutrition); and insufficient pediatric health care resources to meet the demand.13
At the population level, HIV care and treatment comprise a cascade of interventions with coverage at each step dependent on coverage of the preceding step. This cascade involves diagnosis of HIV infection, linkage to care, determination of ART eligibility, initiation of ART, and successful suppression of viral replication. HIV testing is a critical first step in the cascade of HIV care, as well as the gateway to other prevention, treatment, and care interventions. However, to achieve access, reliable mechanisms must link individuals to needed services. Available evidence suggests considerable shortcomings with linkage and referral, including the lack of routine tracking mechanisms. As HIV diagnosis and treatment programs have scaled up in developing countries, attrition at each step in the cascade of HIV care has emerged as a critical concern limiting overall population-level impact for both adults and children.14,15 This cascade is well characterized in developed countries,16 but population-based estimates of pediatric HIV testing and care coverage are not available in most low-income countries, including Kenya.
The second Kenya AIDS Indicator Survey (KAIS 2012) was the first national survey in Kenya to collect HIV-specific data on children from 18 months to 14 years of age. KAIS 2012 allowed for estimation of HIV prevalence among this population and direct assessment of the cascade from diagnosis of HIV infection through suppression of viral replication.
METHODS
Study Design
KAIS 2012 was a nationally representative cross-sectional survey of HIV infection and associated risk behavior among persons aged 18 months to 64 years, conducted from October 2012 to February 2013. Details of the study are described elsewhere.17 Briefly, a stratified 2-stage sampling design was used to select household clusters from a national household sampling frame, using systematic random sampling; subsequently, from the clusters, eligible households were selected using equal probability systematic sampling. Because of regional security concerns, the North Eastern region was not included in the sampling frame. Since half of the households selected in KAIS 2012 were required for the child sample, every other household was selected after random selection of the first household. These households were designated as child-eligible households. If a child-eligible household did not have an eligible child aged 18 months to 14 years, the next child-eligible household was visited until one with an eligible child was identified.
In this article, we consider all children who were aged 18 months to 14 years and resided in child-eligible households. Individual questionnaires were administered to consenting children’s parents or guardians; we refer to this as the interview sample. In child-eligible households, we requested permission to draw blood from eligible children for HIV serology and, if HIV-positive, viral load measurement. We refer to this subsample as the serological sample. Questions pertaining to children aged 18 months to 14 years were embedded in the individual questionnaire for adult women and men and were answered by parents or guardians. These interviews collected information on demographics and HIV testing histories of children residing in the household. If a child was reported as HIV-positive by the parent or guardian, additional information on attendance at HIV clinics, current and past use of ART and cotrimoxazole use was collected. Parents or guardians of children in the serological sample were asked if the child had ever been tested for HIV, and if so, what the result of the test was.
Study Population
Our study population consisted of children aged 18 months to 14 years. Children were included if they were usual residents of the household or present in the household on the night before the survey and had their parent’s or guardian’s consent.
Measurements
The main outcome variable was HIV infection as determined by laboratory testing. Secondary outcomes among children with previously diagnosed HIV infection included attending an HIV clinic and receiving cotrimoxazole prophylaxis and ART. An additional outcome of interest was HIV RNA concentration among those who tested HIV-positive in the serological sample. We used an HIV RNA concentration threshold of <1000 copies per milliliter to define virologic suppression.
Laboratory Methods
We asked parents or guardians of eligible children for their verbal consent to collect a blood sample for biologic testing and extended storage for future unspecified testing at the National HIV Reference Laboratory (NHRL) in Nairobi. At NHRL dried blood spot specimens were tested for HIV antibody using the Vironostika HIV-1/2 UNIF II plus O Enzyme Immunoassay (bioMérieux SA, Marcy l’Etoile, France) and confirmed using the Murex HIV.1.2.O HIV Enzyme Immunoassay (DiaSorin SpA, Saluggia, Italy). Repeat testing was done for discordant results, and, if results remained discordant, a final determination was made using polymerase chain reaction for HIV antigen (Cobas Amplicor HIV-1 Monitor Test, version 1.5; Roche Molecular Diagnostics, Pleasanton, CA). We tested all confirmed HIV-positive blood specimens for HIV RNA concentration (Abbott M2000 Real-Time HIV-1 Assay; Abbott Laboratories, Abbott Park, IL). Test results from the NHRL were not returned to study participants. Home-based HIV testing and counseling, using rapid tests according to the national HIV testing algorithm, was offered to all persons participating in the survey, including parents and guardians of participating children.
Statistical Analysis
We merged interview and laboratory data to produce a final survey dataset for cleaning and analysis. We weighted survey data to correct for unequal probability of selection and adjust for nonresponse. The analysis on the interview sample (ie, eligible children with available interview data from their parent or guardian) was restricted to describing sociodemographic and HIV testing characteristics. The analysis on the serological sample (ie, eligible children for whom we drew blood for HIV serology) included a description of socio-demographic characteristics, HIV testing characteristics, and for HIV-positive children, access to HIV care and treatment. We estimated point prevalences and 95% confidence intervals (CI). The Taylor Series Linearization method was used to compute variance estimates. For continuous variables, we calculated medians and interquartile ranges. Categorical factors associated with HIV infection were examined using the χ2 test, and strength of associations were presented as odds ratios. We used non-normalized survey weights, based on the 2012 population projections from the 2009 national census, to estimate the national number and 95% CI of HIV-infected children aged 18 months to 14 years.18 SAS version 9.3 (SAS Institute, Cary, NC) was used for statistical analyses. Because estimates based on small sample sizes are not reliable and cannot be generalized to the broader population, we do not present weighted estimates and 95% CI for indicators based on denominators of less than 30 observations. This includes indicators describing access to care and treatment among HIV-infected children.
Ethical Considerations
The KAIS 2012 protocol was approved by the Kenya Medical Research Institute Ethical Review Committee, the US Centers for Disease Control and Prevention Institutional Review Board, and the Committee on Human Research of the University of California, San Francisco. We obtained permission from parents or guardians to draw blood and assent from children aged 10 years or older. Home-based HIV testing and counseling was done in a private location within the household. The results of home-based testing were recorded by the counselor in a password-protected tablet computer using the unique identification number for the participant. Home-based HIV test results were disclosed to parents or guardians.
RESULTS
In total, there were 9189 KAIS 2012 households of which 4146 were child-eligible; 5162 of 9683 children in these households were found to be eligible. Of the 5162 eligible children, half (50.1%) were boys. The median age was 8.4 years (interquartile range, 4.8–11.7), and 25.4% were aged 18 months to 4 years (Table 1). For 7.4% of children (95% CI: 6.0 to 8.7), 1 parent had died, and for 1.3% of children (95% CI: 0.9 to 1.8), both parents had died. Overall 74.3% of children (95% CI: 71.2 to 77.4) resided in rural areas; the largest proportions were from the poorest (26.9%, 95% CI: 22.3 to 31.5) and second poorest (26.6%, 95% CI: 23.9 to 29.3) household wealth quintiles. Overall, 2.6% of children (95% CI: 1.7 to 3.5) had parents or guardians who reported an HIV-positive status.
TABLE 1.
Select Sociodemographic and Testing Characteristics Among Children Aged 18 Months to 14 Years, Kenya AIDS Indicator Survey 2012
| Variable | Interview Sample (N = 5162)
|
Interviewed With No Serology (N = 1481)
|
Interviewed With Serology— Serological Sample (N = 3681)
|
|||
|---|---|---|---|---|---|---|
| Unweighted, n* | Weighted % (95% CI) | Unweighted, n* | Weighted % (95% CI) | Unweighted, n* | Weighted % (95% CI) | |
| Sex | ||||||
| Boy | 2569 | 50.1 (48.5 to 51.7) | 751 | 51.1 (48.5 to 53.6) | 1818 | 49.7 (47.8 to 51.6) |
| Girl | 2593 | 49.9 (48.3 to 51.5) | 730 | 48.9 (46.4 to 51.5) | 1863 | 50.3 (48.4 to 52.2) |
| Age category | ||||||
| 18 months to 4 yrs | 1320 | 25.4 (24.0 to 26.7) | 469 | 32.7 (29.8 to 35.6) | 851 | 22.4 (20.9 to 24.0) |
| 5–9 yrs | 1888 | 35.6 (34.1 to 37.1) | 539 | 35.7 (33.2 to 38.3) | 1350 | 35.6 (33.7 to 37.4) |
| 10–14 yrs | 1954 | 39.0 (37.3 to 40.7) | 474 | 31.6 (28.6 to 34.5) | 1480 | 42.0 (39.9 to 44.0) |
| Orphan status | ||||||
| Both parents dead | 60 | 1.3 (0.9 to 1.8) | 13 | 1.0 (0.4 to 1.6) | 47 | 1.5 (0.9 to 2.0) |
| One parent dead | 407 | 7.4 (6.0 to 8.7) | 99 | 5.6 (3.9 to 7.2) | 308 | 8.1 (6.5 to 9.8) |
| Both parents alive | 4603 | 89.5 (88.0 to 91.1) | 1343 | 91.9 (89.9 to 93.9) | 3260 | 88.5 (86.6 to 90.4) |
| Unknown | 92 | 1.8 (1.2 to 2.3) | 26 | 1.5 (0.6 to 2.4) | 66 | 1.9 (1.2 to 2.6) |
| Region | ||||||
| Nairobi | 366 | 6.2 (5.0 to 7.3) | 170 | 9.7 (7.9 to 11.6) | 196 | 4.7 (3.6 to 5.8) |
| Central | 452 | 9.3 (7.8 to 10.7) | 78 | 5.5 (3.8 to 7.3) | 374 | 10.8 (8.9 to 12.7) |
| Coast | 675 | 9.5 (7.2 to 11.9) | 200 | 11.7 (7.1 to 16.4) | 475 | 8.7 (6.3 to 11.0) |
| Eastern | 1248 | 16.4 (13.8 to 19.0) | 448 | 23.1 (18.3 to 27.9) | 800 | 13.7 (11.2 to 16.1) |
| Nyanza | 704 | 16.0 (13.2 to 18.7) | 143 | 11.2 (8.0 to 14.4) | 561 | 17.9 (14.2 to 21.6) |
| Rift Valley | 927 | 28.0 (24.0 to 32.0) | 299 | 29.6 (24.2 to 35.0) | 628 | 27.4 (22.6 to 32.2) |
| Western | 790 | 14.7 (12.7 to 16.6) | 143 | 9.1 (7.1 to 11.2) | 647 | 16.9 (14.4 to 19.4) |
| Residence | ||||||
| Rural | 3782 | 74.3 (71.2 to 77.4) | 1009 | 71.4 (67.0 to 75.9) | 2773 | 75.4 (71.7 to 79.2) |
| Urban | 1380 | 25.7 (22.6 to 28.8) | 472 | 28.6 (24.1 to 33.0) | 908 | 24.6 (20.8 to 28.3) |
| Wealth index quintiles | ||||||
| Poorest | 1424 | 26.9 (22.3 to 31.5) | 420 | 27.0 (20.9 to 33.0) | 1004 | 26.8 (21.7 to 32.0) |
| Second | 1333 | 26.6 (23.9 to 29.3) | 324 | 23.9 (20.1 to 27.7) | 1009 | 27.7 (24.6 to 30.8) |
| Middle | 1098 | 22.1 (19.4 to 24.8) | 305 | 21.5 (16.8 to 26.2) | 795 | 22.5 (19.8 to 25.2) |
| Fourth | 723 | 13.4 (11.2 to 15.7) | 211 | 13.4 (10.0 to 16.8) | 510 | 13.4 (11.1 to 15.7) |
| Richest | 584 | 11.0 (8.9 to 13.0) | 221 | 14.2 (10.8 to 17.7) | 363 | 9.7 (7.5 to 11.8) |
| Self-reported HIV status of parent/guardian | ||||||
| HIV-positive | 93 | 2.6 (1.7 to 3.5) | 14 | 1.0 (0.2 to 1.8) | 79 | 3.3 (2.1 to 4.5) |
| HIV-negative | 3611 | 97.4 (96.5 to 98.3) | 1120 | 99.0 (98.2 to 99.8) | 2491 | 96.7 (95.5 to 97.9) |
| HIV testing history of child of HIV-positive parent/guardian | ||||||
| Child ever been tested | 48 | 52.9 (39.5 to 66.2) | 10 | 76.2 (55.6 to 96.7) | 38 | 49.6 (35.7 to 63.5) |
| Child never been tested/don’t know | 45 | 47.1 (33.8 to 60.5) | 4 | 23.8 (3.27 to 44.4) | 41 | 50.4 (36.5 to 64.3) |
| Child tested before KAIS 2012 | ||||||
| Yes | 742 | 16.4 (13.9 to 18.9) | 205 | 15.2 (12.2 to 18.2) | 537 | 16.9 (13.8 to 20.0) |
| No | 3883 | 83.6 (81.1 to 86.1) | 1185 | 84.8 (81.8 to 87.8) | 2698 | 83.1 (80.0 to 86.2) |
Due to missing responses totals may vary between variables.
Of the 5162 eligible children, 3681 (71.3%) children had consent obtained for the blood draw for HIV serology and viral load measurement in the NHRL (serological sample). Children who provided blood were comparable with those who did not provide blood with respect to most baseline characteristics assessed except for age (P < 0.0001), geographic region (P < 0.0001), and self-reported HIV status of the child’s parent or guardian (P = 0.0019). Compared with children who did not provide blood, children who provided blood were more likely to be aged 10–14 years (42.0% vs. 31.6%); reside in Central (10.8% vs. 5.5%), Nyanza (17.9% vs. 11.2%) and Western (16.9% vs. 9.1%) regions; and have a parent or guardian who self-reported HIV-positive status (3.3% vs. 1.0%), respectively (Table 1). Among children in the serological sample, 16.9% (95% CI: 13.8% to 20.0%) had been tested for HIV before the survey.
Overall, 28 (0.9%, 95% CI: 0.5 to 1.3) children tested HIV-positive in the survey (Table 2). HIV prevalence among girls was 1.1% (95% CI: 0.4 to 1.7) compared with 0.7% (95% CI: 0.3 to 1.1) among boys. Children younger than 5 years of age had a HIV prevalence of 1.6% (95% CI: 0.5 to 2.7) and had significantly higher odds of being HIV-positive compared with older children aged 10–14 years (odds ratio, 2.9, 95% CI: 1.1 to 7.5). Children whose parents were dead (ie, 1 or both parents) had similar HIV prevalence (0.8%, 95% CI: 0 to 1.8) compared with children whose parents were alive (0.7%, 95% CI: 0.4 to 1.1). Children living in rural residences also had similar HIV prevalence compared with children living in urban residences (0.9%, 95% CI: 0.4 to 1.4 vs 0.8%, 95% CI: 0.1 to 1.6, respectively). High HIV prevalence was observed among children whose parent or guardian self-reported HIV-positive status (6.5%, 95% CI: 2.9 to 10.2) and among children who had been tested for HIV infection in the past (3.2%, 95% CI: 1.3 to 5.1).
TABLE 2.
HIV Prevalence Among Children Aged 18 Months to 14 Years and Associations With Select Sociodemographic, Testing, and Clinical Characteristics, Kenya AIDS Indicator Survey 2012
| Variable | Unweighted, N* | Unweighted, n | Weighted % (95% CI) | Odds Ratio (95% CI) | P |
|---|---|---|---|---|---|
| Total | 3681 | 28 | 0.9 (0.5 to 1.3) | — | — |
| Sex | |||||
| Boy | 1818 | 14 | 0.7 (0.3 to 1.1) | 1.0 | — |
| Girl | 1863 | 14 | 1.1 (0.4 to 1.7) | 1.6 (0.7 to 3.5) | 0.241 |
| Age categories | |||||
| 18 months to 4 years | 851 | 9 | 1.6 (0.5 to 2.7) | 2.91 (1.1 to 7.5) | 0.028 |
| 5–9 years | 1350 | 10 | 0.8 (0.1 to 1.4) | 1.42 (0.5 to 3.8) | 0.485 |
| 10–14 years | 1480 | 9 | 0.6 (0.2 to 0.9) | 1.0 | — |
| Parent status | |||||
| One or both parents dead | 355 | 3 | 0.8 (0.0 to 1.8) | 1.1 (0.3 to 4.3) | 0.914 |
| Both parents alive | 3260 | 20 | 0.7 (0.4 to 1.1) | 1.0 | — |
| Residence | |||||
| Rural | 2773 | 21 | 0.9 (0.4 to 1.4) | 1.1 (0.4 to 3.1) | 0.896 |
| Urban | 908 | 7 | 0.8 (0.1 to 1.6) | 1.0 | — |
| Self-reported HIV status of parent/guardian† | |||||
| Parent/guardian is HIV-positive | 237 | 15 | 6.5 (2.9 to 10.2) | 17.4 (7.5 to 40.4) | <0.001 |
| Parent/guardian is HIV-negative | 2932 | 9 | 0.4 (0.1 to 0.7) | 1.0 | — |
| HIV testing history of child of HIV-positive parent/guardian | |||||
| Child ever tested | 99 | 11 | 11.0 (3.8 to 18.2) | 4.7 (1.4 to 16.4) | 0.015 |
| Child never tested | 136 | 4 | 2.6 (0 to 5.32) | 1.0 | — |
| Child tested before KAIS 2012 | |||||
| Yes | 537 | 14 | 3.2 (1.3 to 5.1) | 7.9 (3.3 to 18.8) | <0.001 |
| No | 2698 | 10 | 0.4 (0.1 to 0.7) | 1.0 | — |
| Child’s reported HIV status | |||||
| HIV-positive | 11 | 11 | ‡ | — | — |
| HIV-negative | 495 | 3 | 0.8 (0 to 1.8) | — | — |
Due to missing responses, totals vary between variables.
Data missing for 392 children whose parent/guardian was not interviewed.
Estimate unreliable and suppressed due to small sample size.
Due to the small sample size of children with laboratory-confirmed HIV infection (N = 28), the following section describes, in absolute numbers, select indicators in the cascade of care for HIV-positive children. Of the 28 children who were found to be HIV-infected in our sample, 11 had been previously diagnosed with HIV infection. Among these 11, all had attended an HIV clinic at least once before the survey and were currently taking daily cotrimoxazole. Eight were currently on ART and of those, 4 were virologically suppressed. Three of the 28 HIV-infected children were orphans with at least 1 parent who had died.
DISCUSSION
Our study provides the first population-based estimate of children living with HIV in Kenya. We found that the overall prevalence of HIV infection in children aged 18 months to 14 years was 0.9%, corresponding to an estimated 104,000 HIV-infected children in this age group. Previous estimates on the burden of HIV among children have been measured indirectly through mathematical modeling.6,19 These models estimated that approximately 200,000 children younger than 15 years were living with HIV in 2010, of whom an estimated 158,000 required ART. Our survey identified fewer children living with HIV compared to these indirect estimates. Our estimates are likely to underestimate the true burden of pediatric HIV infection given that our survey sampled children who had already survived up to 18 months. Without ART, 30% HIV-infected children are expected to die by 1 year of age. This increases to 50% by the second year.20 Thus, our estimation of the burden of pediatric HIV in Kenya omits a substantial number of children who die early if no intervention is provided. We also found variability in the burden of HIV among children, with a decrease in HIV prevalence with increasing age. This is consistent with the likely high mortality in the infected pediatric population in Africa from earlier birth cohorts.20,21 Orphanhood was much lower than that reported in previous studies, which have estimated that about 45% of children with HIV infection will be orphaned,22,23 but selective mortality among children and their parents may have led to our lower estimates. Another possibility is that the scale-up of ART for adults may have resulted in more parents surviving. Also the proportion of orphans in our study could be an underestimation considering that children whose parents’ status was unknown may have been orphaned.
Only 16% of children were reported to have had a previous HIV test, and less than half of children with HIV-infected parents or guardians had ever been tested for HIV. Our study also confirmed that most children who were living with HIV remained undiagnosed and unable to access care and treatment. Although significant progress has been made in scaling up HIV testing for adults,24 these findings highlight the need to improve testing strategies for children. The high proportion of undiagnosed HIV infection, particularly among those children whose parents or guardians were infected, underscores the magnitude of missed opportunities for diagnosis of HIV infection. Expansion of family testing strategies in facility and community-based settings can help to rapidly increase identification of HIV-infected children and link them into care.25
We were encouraged to find that all children in the sample who had been previously diagnosed with HIV infection had accessed HIV care and had started cotrimoxazole prophylaxis. Nonetheless, that only 8 of 28 children with laboratory-diagnosed HIV infection were receiving ART should be a cause for concern. In addition, only half of children who were currently on ART were virologically suppressed. This was lower than proportions reported in other studies in Kenya where the estimated proportion of children who were able to achieve and maintain virologic suppression was around 70%.25,26 Because we did not assess the duration of ART for these children, it is possible that some of these children may have initiated ART recently and therefore not yet achieved viral suppression.
Our study had several limitations. Although the majority of childhood infections are likely to occur in children younger than aged 18 months, we chose to survey only children from 18 months of age because of the complicated logistics of RNA testing in the field and returning results for these children after survey teams had left the cluster. Therefore, our estimates are not generalizable to all children. The details of medical histories were obtained from mothers and other caregivers, and we were unable to confirm these data by chart review, introducing the potential for recall bias. Finally, although this was a national household survey, we were only able to identify 28 HIV-infected children. Based on this small sample size, some of our estimates are imprecise and not generalizable to the broader population. Caution should therefore be used when interpreting reported indicators of care and treatment among HIV-infected children.
Despite these limitations, KAIS 2012 is the first survey to provide direct estimates of HIV-related indicators for children, information that program managers and policy makers can use immediately to inform pediatric programs for HIV prevention, care, and treatment. HIV causes a substantial burden of disease in the pediatric population in Kenya. Future efforts should focus on expanded testing of children to identify HIV-infected children and getting them into care and on suppressive ART as early as possible.
Acknowledgments
The authors thank the fieldworkers and supervisors for their excellent work during KAIS data collection and all the children and families who participated in this national survey. The authors would also like to thank Anthony Gichangi and Eddas Bennett for their statistical input on the analysis; Amanda Viitanen, Janet Burnett, and Kevin De Cock for discussing and reviewing the manuscript; and the KAIS Study Group for their contribution to the design of the survey and collection of the data set: Willis Akhwale, Sehin Birhanu, John Bore, Angela Broad, Robert Buluma, Thomas Gachuki, Jennifer Galbraith, Anthony Gichangi, Beth Gikonyo, Margaret Gitau, Joshua Gitonga, Mike Grasso, Malayah Harper, Andrew Imbwaga, Muthoni Junghae, Mutua Kakinyi, Samuel Mwangi Kamiru, Nicholas Owenje Kandege, Lucy Kanyara, Yasuyo Kawamura, Timothy Kellogg, George Kichamu, Andrea Kim, Lucy Kimondo, Davies Kimanga, Elija Kinyanjui, Stephen Kipkerich, Dan Koros, Danson Kimutai Koske, Boniface O. K’Oyugi, Veronica Lee, Serenita Lewis, William Maina, Ernest Makokha, Agneta Mbithi, Joy Mirjahangir, Ibrahim Mohamed, Rex Mpazanje, Silas Mulwa, Nicolas Muraguri, Patrick Mureithi, Lilly Muthoni, James Muttunga, Jane Mwangi, Mary Mwangi, Sophie Mwanyumba, Francis Ndichu, Anne Ng’ang’a, James Ng’ang’a, John Gitahi Ng’ang’a, Lucy Ng’ang’a, Carol Ngare, Bernadette Ng’eno, Inviolata Njeri, David Njogu, Bernard Obasi, Macdonald Obudho, Edwin Ochieng, Linus Odawo, Jacob Odhiambo, Caleb Ogada, Samuel Ogola, David Ojakaa, James Kwach Ojwang, George Okumu, Patricia Oluoch, Tom Oluoch, Kenneth Ochieng Omondi, Osborn Otieno, Yakubu Owolabi, Bharat Parekh, George Rutherford, Sandra Schwarcz, Shanaaz Sharrif, Victor Ssempijja, Lydia Tabuke, Yuko Takanaka, Mamo Umuro, Brian Eugene Wakhutu, Celia Wandera, John Wanyungu, Wanjiru Waruiru, Anthony Waruru, Paul Waweru, Larry Westerman, and Kelly Winter.
KAIS 2012 was supported by the National AIDS and STI Control Programme, Kenya National Bureau of Statistics, National Public Health Laboratory Services, National AIDS Control Council, National Council for Population and Development, Kenya Medical Research Institute, US Centers for Disease Control and Prevention (CDC/Kenya, CDC/Atlanta), United States Agency for International Development (USAID/Kenya), University of California, San Francisco, Joint United Nations Team on HIV/AIDS, Japan International Cooperation Agency, Elizabeth Glaser Pediatric AIDS Foundation, Liverpool Voluntary Counselling and Testing, African Medical and Research Foundation, World Bank, and Global Fund. This publication was made possible by support from the US President’s Emergency Plan for AIDS Relief through cooperative agreements (#PS001805, GH000069, and PS001814) from the US Centers for Disease Control and Prevention, Division of Global HIV/AIDS. This work was also funded in part by support from the Global Fund, World Bank, and the Joint United Nations Team for HIV/AIDS.
Footnotes
The authors have no conflicts of interest to disclose.
The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention and the Government of Kenya.
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