In Kenya, HIV/AIDS remains a leading cause of morbidity and mortality among adolescents living with HIV (ALHIV). Our study evaluated associations between demographic and healthcare factors and HIV treatment outcomes among ALHIV in care in Kenya. This retrospective cohort study evaluated the clinical outcomes of newly diagnosed ALHIV enrolled in HIV care during January 2017-June 2018 at 32 healthcare facilities in Homabay and Kakamega Counties. Demographic and clinical data were abstracted from patient clinical records and registers during the follow up study period January 2017-through May 2019. ALHIV were stratified by age (10–14 versus 15–19 years). Categorical variables were summarized using descriptive statistics; continuous variables were analyzed using mean values. The latest available treatment and virological outcomes for ALHIV were assessed. 330 ALHIV were included in the study (mean age 15.9 years; 81.8% female, 63.0% receiving HIV care at lower-level healthcare facilities). Most (93.2%) were initiated on ART within 14 days of diagnosis; 91.4% initiated EFV-based regimens. Of those on ART, only 44.6% were active on care at the end of the study period. Of those eligible for viral load testing, 83.9% were tested with 84.4% viral suppression rate. Retention in care was higher at higher-level facilities (67.5%) compared to lower-level facilities (28.6%). Factors associated with higher retention in care were school attendance (aRR = 1.453), receipt of disclosure support (aRR = 13.315), and receiving care at a high-level health facility (aRR = 0.751). Factors associated with viral suppression included older age (15–19 years) (aRR = 1.249) and pre-ART clinical WHO stage I/II (RR = .668). Viral suppression was higher among older ALHIV. Studies are needed to evaluate effective interventions to improve outcomes among ALHIV in Kenya.

Viral suppression is suboptimal among children and adolescents on antiretroviral therapy (ART) in Kenya. We implemented and evaluated a standardized enhanced adherence counseling (SEAC) package to improve viral suppression in children and adolescents with suspected treatment failure in Homa Bay and Turkana. The SEAC package, implemented from February 2019 to September 2020, included: standard procedures operationalizing the enhanced adherence counseling (EAC) process; provider training on psychosocial support and communication skills for children living with HIV and their caregivers; mentorship to providers and peer educators on EAC processes; and individualized case management. We enrolled children and adolescents aged 0 to 19 years with suspected treatment failure (viral load [VL] >1000 copies/mL) who received EAC before standardization as well as those who received SEAC in a pre-post evaluation of the SEAC package conducted in 6 high-volume facilities. Pre-post standardization comparisons were performed using Wilcoxon-Mann-Whitney and Pearson's chi-square tests at a 5% level of significance. Multivariate logistic regression was performed to identify factors associated with viral resuppression. The study enrolled 741 participants, 595 pre-and 146 post-SEAC implementation. All post-SEAC participants attended at least 1 EAC session, while 17% (n = 98) of pre-SEAC clients had no record of EAC attendance. Time to EAC following the detection of high VL was reduced by a median of 8 days, from 49 (interquartile range [IQR]: 23.0-102.5) to 41 (IQR: 20.0-67.0) days pre-versus post-SEAC (P = .006). Time to completion of at least 3 sessions was reduced by a median of 12 days, from 59.0 (IQR: 36.0-91.0) to 47.5 (IQR: 33.0-63.0) days pre-versus post-SEAC (P = .002). A greater percentage of clients completed the recommended minimum 3 EAC sessions at post-SEAC, 88.4% (n = 129) versus 61.1% (n = 363) pre-SEAC, P < .001. Among participants with a repeat VL within 3 months following the high VL, SEAC increased viral suppression from 34.6% (n = 76) to 52.5% (n = 45), P = .004. Implementation of the SEAC package significantly reduced the time to initiate EAC and time to completion of at least 3 EAC sessions, and was significantly associated with viral suppression in children and adolescents with suspected treatment failure.

Despite large numbers of patients accessing antiretroviral treatment (ART) in Kenya, few studies have explored factors associated with virologic failure in Western Kenya, specifically. We undertook a study in Homa Bay County, Kenya to assess the extent of virologic treatment failure and factors associated with it. This was an observational retrospective study conducted from September 2020 to January 2021. Data were abstracted from the records of patients who had been on ART for at least six months at the time of data collection after systematic sampling stratified by age group at ART initiation (0–14 and 15+ years), using probability proportion to the numbers of patients attending the facility. Confirmed viral treatment failure was defined as viral load ≥1000 copies/ml based on two consecutive viral load measurements after at least three months of enhanced adherence counseling. Data were analyzed using descriptive statistics and Cox regression modeling. Of the 2,007 patients sampled, 160 (8.0%) had confirmed virologic treatment failure. Significantly higher virologic treatment failure rates were identified among male patients 78/830 (9.4%) and children 115/782 (14.7%). Factors associated with virologic treatment failure (VTF), were age 0–14 years, adjusted hazard ratio (AHR) 4.42, (95% Confidence Interval [CI], 3.12, 6.32), experience of treatment side effects AHD: 2.43, (95% CI, 1.76, 3.37), attending level 2/3 health facility, AHR: 1.87, (95% CI: 1.29, 2,72), and history of opportunistic infections (OIs), AHR: 1.81, (95% CI, 1.76, 3.37). Children, attendees of level 2/3 health facilities, patients with a history of OIs, and those experiencing treatment side-effects are at risk of VTF. Increased focus on children and adolescents on screening for drug resistance, administration of and adherence to medication, and on effective information and education on side-effects is critical. Additionally, there is need for increased training and support for health care workers at primary level care facilities.

Tuberculosis (TB) infections among children (below 15 years) is a growing concern, particularly in resource-limited settings. However, the TB burden among children is relatively unknown in Kenya where two-thirds of estimated TB cases are undiagnosed annually. Very few studies have used Autoregressive Integrated Moving Average (ARIMA), and hybrid ARIMA models to model infectious diseases globally. We applied ARIMA, and hybrid ARIMA models to predict and forecast TB incidences among children in Homa Bay and Turkana Counties in Kenya. The ARIMA, and hybrid models were used to predict and forecast monthly TB cases reported in the Treatment Information from Basic Unit (TIBU) system by health facilities in Homa Bay and Turkana Counties between 2012 and 2021. The best parsimonious ARIMA model that minimizes errors was selected based on a rolling window cross-validation procedure. The hybrid ARIMA-ANN model produced better predictive and forecast accuracy compared to the Seasonal ARIMA (0,0,1,1,0,1,12) model. Furthermore, using the Diebold-Mariano (DM) test, the predictive accuracy of ARIMA-ANN versus ARIMA (0,0,1,1,0,1,12) model were significantly different, p<0.001, respectively. The forecasts showed a TB incidence of 175 TB cases per 100,000 (161 to 188 TB incidences per 100,000 population) children in Homa Bay and Turkana Counties in 2022. The hybrid (ARIMA-ANN) model produces better predictive and forecast accuracy compared to the single ARIMA model. The findings show evidence that the incidence of TB among children below 15 years in Homa Bay and Turkana Counties is significantly under-reported and is potentially higher than the national average.

Background Tuberculosis (TB) infections among children (below 15 years) is a growing concern, particularly in resource-limited settings. However, the TB burden among children is relatively unknown in Kenya where two-thirds of estimated TB cases are undiagnosed annually. Very few studies have used Autoregressive Integrated Moving Average (ARIMA), hybrid ARIMA, and Artificial Neural Networks (ANNs) models to model infectious diseases globally. We applied ARIMA, hybrid ARIMA, and Artificial Neural Network models to predict and forecast TB incidences among children in Homa bay and Turkana Counties in Kenya. Methods The ARIMA, ANN, and hybrid models were used to predict and forecast monthly TB cases reported in the Treatment Information from Basic Unit (TIBU) system for Homa bay and Turkana Counties between 2012 and 2021. The data were split into training data, for model development, and testing data, for model validation using an 80:20 split ratio respectively. Results The hybrid ARIMA model (ARIMA-ANN) produced better predictive and forecast accuracy compared to the ARIMA (0,0,1,1,0,1,12) and NNAR (1,1,2) [12] models. Furthermore, using the Diebold-Mariano (DM) test, the predictive accuracy of NNAR (1,1,2) [12] versus ARIMA-ANN, and ARIMA-ANN versus ARIMA (0,0,1,1,0,1,12) models were significantly different, p<0.001, respectively. The 12-month forecasts showed a TB prevalence of 175 to 198 cases per 100,000 children in Homa bay and Turkana Counties in 2022. Conclusion The hybrid (ARIMA-ANN) model produces better predictive and forecast accuracy compared to the single ARIMA and ANN models. The findings show evidence that the prevalence of TB among children below 15 years in Homa bay and Turkana Counties is significantly under-reported and is potentially higher than the national average.