ABSTRACT
BACKGROUND: Population-level estimates of linkage to HIV care among children and adolescents (CAs) can facilitate progress toward 95-95-95 goals. SETTING: This study was conducted in Bunyala, Chulaimbo, and Teso North subcounties, Western Kenya. METHODS: Linkage to care was defined among CAs diagnosed with HIV through Academic Model Providing Access to Healthcare (AMPATH)'s home-based counseling and testing initiative (HBCT) by merging HBCT and AMPATH Medical Record System data. Using follow-up data from Bunyala, we examined factors associated with linkage or death, using weighted multinomial logistic regression to account for selection bias from double-sampled visits. Based on the estimated model, we imputed the trajectory for each person in 3 subcounties until a simulated linkage or death occurred or until the end of 8 years when an individual was simulated to be censored. RESULTS: Of 720 CAs in the analytic sample, 68% were between 0 and 9 years and 59% were female. Probability of linkage among CAs in the combined 3 subcounties was 48%-49% at 2 years and 64%-78% at 8 years while probability of death was 13% at 2 years and 19% at 8 years. Single or double orphanhood predicted linkage (adjusted odds ratio [aOR]: 2.66, 95% confidence interval [CI]: 1.33 to 5.32) and death (aOR: 9.85 [95% CI: 2.21 to 44.01]). Having a mother known to be HIV-positive also predicted linkage (aOR = 1.94, 95% CI: 0.97 to 3.86) and death (aOR: 14.49, 95% CI: 3.32 to 63.19). CONCLUSION: HIV testers/counselors should continue to ensure linkage among orphans and CAs with mothers known to be HIV-positive and also to support other CAs to link to HIV care.
Subject(s)
Counselors , HIV Infections , Humans , Female , Adolescent , Child , Male , Kenya/epidemiology , HIV Infections/drug therapy , HIV Infections/epidemiology , HIV Infections/diagnosis , Counseling , MothersABSTRACT
OBJECTIVE: To obtain an estimate of the size of, and human immunodeficiency (HIV) prevalence among, young people and children living on the streets of Eldoret, Kenya. METHODS: We counted young people and children using a point-in-time approach, ensuring we reached our target population by engaging relevant community leaders during the planning of the study. We acquired point-in-time count data over a period of 1 week between the hours of 08:00 and 23:00, from both a stationary site and by mobile teams. Participants provided demographic data and a fingerprint (to avoid double-counting) and were encouraged to speak with an HIV counsellor and undergo HIV testing. We used a logistic regression model to test for an association between age or sex and uptake of HIV testing and seropositivity. FINDINGS: Of the 1419 eligible participants counted, 1049 (73.9%) were male with a median age of 18 years. Of the 1029 who spoke with a counsellor, 1004 individuals accepted HIV counselling and 947 agreed to undergo an HIV test. Combining those who were already aware of their HIV-positive status with those who were tested during our study resulted in an overall HIV seroprevalence of 4.1%. The seroprevalence was 2.7% (19/698) for males and 8.9% (23/259) for females. We observed an increase in seroprevalence with increasing age for both sexes, but of much greater magnitude for females. CONCLUSION: By counting young people and children living on the streets and offering them HIV counselling and testing, we could obtain population-based estimates of HIV prevalence.
Subject(s)
HIV Infections/epidemiology , HIV Infections/psychology , Patient Acceptance of Health Care/statistics & numerical data , Adolescent , Adult , Age Distribution , Child , Child, Preschool , Counseling , Cross-Sectional Studies , Dermatoglyphics , Female , HIV Infections/diagnosis , Humans , Kenya/epidemiology , Logistic Models , Male , Mass Screening/methods , Prevalence , Seroepidemiologic Studies , Sex Distribution , Young AdultABSTRACT
Objective To obtain an estimate of the size of, and human immunodeficiency (HIV) prevalence among, young people and children living on the streets of Eldoret, Kenya. Methods We counted young people and children using a point-in-time approach, ensuring we reached our target population by engaging relevant community leaders during the planning of the study. We acquired point-in-time count data over a period of 1 week betweethe hours of 08:00 and 23:00, from both a stationary site and by mobile teams. Participants provided demographic data and a finger print(to avoid double-counting) and were encouraged to speak with an HIV counsellor and undergo HIV testing. We used a logistic regression (model to test for an association between age or sex and uptake of HIV testing and seropositivity. Findings Of the 1419 eligible participants counted, 1049 (73.9%) were male with a median age of 18 years. Of the 1029 who spoke with a counsellor, 1004 individuals accepted HIV counselling and 947 agreed to undergo an HIV test. Combining those who were already aware of their HIV-positive status with those who were tested during our study resulted in an overall HIV seroprevalence of 4.1%. The seroprevalence was 2.7% (19/698) for males and 8.9% (23/259) for females. We observed an increase in seroprevalence with increasing age for both sexes, but of much greater magnitude for females. Conclusion By counting young people and children living on the streets and offering them HIV counselling and testing, we could obtain population-based estimates of HIV prevalence
