Demographic and clinical variables of active patients registered in the EMR system pre- and post-intervention.

<p>^* patients eligible for ART, based on CD4 or WHO stage, but who have not started ART</p><p>Demographic and clinical variables of active patients registered in the EMR system pre- and post-intervention.</p

Patients eligible but not on ART and patients followed up following a missed clinic appointment pre- and post-intervention.

<p>^* Two-sample test of proportions</p><p>^** patients eligible for ART, based on CD4 count ≤350 cells/μl or WHO clinical stage 3 or 4, but who have not yet started ART</p><p>^*** patients who have missed next appointment date by more than two weeks (as % of patients registered)</p><p>Patients eligible but not on ART and patients followed up following a missed clinic appointment pre- and post-intervention.</p

Mother-to-child transmission of HIV in Kenya: A cross-sectional analysis of the national database over nine years

<div><p>Objective</p><p>To describe factors associated with mother-to-child HIV transmission (MTCT) in Kenya and identify opportunities to increase testing/care coverage.</p><p>Design</p><p>Cross-sectional analysis of national early infant diagnosis (EID) database.</p><p>Methods</p><p>365,841 Kenyan infants were tested for HIV from January 2007-July 2015 and results, demographics, and treatment information were entered into a national database. HIV risk factors were assessed using multivariable logistic regression.</p><p>Results</p><p>11.1% of infants tested HIV positive in 2007–2010 and 6.9% in 2014–2015. Greater odds of infection were observed in females (OR: 1.08; 95% CI:1.05–1.11), older children (18–24 months vs. 6 weeks-2 months: 4.26; 95% CI:3.87–4.69), infants whose mothers received no PMTCT intervention (vs. HAART OR: 1.92; 95% CI:1.79–2.06), infants receiving no prophylaxis (vs. nevirapine for 6 weeks OR: 2.76; 95% CI:2.51–3.05), and infants mixed breastfed (vs. exclusive breastfeeding OR: 1.39; 95% CI:1.30–1.49). In 2014–2015, 9.1% of infants had mothers who were not on treatment during pregnancy, 9.8% were not on prophylaxis, and 7.0% were mixed breastfed. Infants exposed to all three risky practices had a seven-fold higher odds of HIV infection compared to those exposed to recommended practices. The highest yield of HIV-positive infants were found through targeted testing of symptomatic infants in pediatric/outpatient departments (>15%); still, most infected infants were identified through PMTCT programs.</p><p>Conclusion</p><p>Despite impressive gains in Kenya’s PMTCT program, some HIV-infected infants present late and are not benefitting from PMTCT best practices. Efforts to identify these early and enforce evidence-based practice for PMTCT should be scaled up. Infant testing should be expanded in pediatric/outpatient departments, given high yields in these portals.</p></div

Characteristics [N (%)] of samples from patients receiving a routine viral load test after 6+ months on first-line^a treatment in 2015–2016 and associations with elevated VL (≥1000 copies/mL)^b.

<p>Characteristics [N (%)] of samples from patients receiving a routine viral load test after 6+ months on first-line<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190659#t002fn001" target="_blank">^a</a> treatment in 2015–2016 and associations with elevated VL (≥1000 copies/mL)<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190659#t002fn002" target="_blank">^b</a>.</p

Flow Chart of samples included in the analysis.

<p>Flow Chart of samples included in the analysis.</p

Characteristics [N/%/median (IQR)] of samples in the viral load database over program scale-up.

<p>Characteristics [N/%/median (IQR)] of samples in the viral load database over program scale-up.</p

Risk factors for HIV positivity in 2007–2010 (N = 96,505; 11.1% HIV-positive) vs. 2011–2013 (N = 168,346; 8.8% HIV-positive) vs. 2014–2015 (N = 100,990; 6.9% HIV-positive) among infants testing for HIV in Kenya.

<p>Risk factors for HIV positivity in 2007–2010 (N = 96,505; 11.1% HIV-positive) vs. 2011–2013 (N = 168,346; 8.8% HIV-positive) vs. 2014–2015 (N = 100,990; 6.9% HIV-positive) among infants testing for HIV in Kenya.</p

Predictive factors for HIV positivity in 365,841 infants testing for HIV in Kenya.

<p>Predictive factors for HIV positivity in 365,841 infants testing for HIV in Kenya.</p

HIV-associated mortality in the era of antiretroviral therapy scale-up – Nairobi, Kenya, 2015

<div><p>Background</p><p>Declines in HIV prevalence and increases in antiretroviral treatment coverage have been documented in Kenya, but population-level mortality associated with HIV has not been directly measured. In urban areas where a majority of deaths pass through mortuaries, mortuary-based studies have the potential to contribute to our understanding of excess mortality among HIV-infected persons. We used results from a cross-sectional mortuary-based HIV surveillance study to estimate the association between HIV and mortality for Nairobi, the capital city of Kenya.</p><p>Methods and findings</p><p>HIV seropositivity in cadavers measured at the two largest mortuaries in Nairobi was used to estimate HIV prevalence in adult deaths. Model-based estimates of the HIV-infected and uninfected population for Nairobi were used to calculate a standardized mortality ratio and population-attributable fraction for mortality among the infected versus uninfected population. Monte Carlo simulation was used to assess sensitivity to epidemiological assumptions. When standardized to the age and sex distribution of expected deaths, the estimated HIV positivity among adult deaths aged 15 years and above in Nairobi was 20.9% (95% CI 17.7–24.6%). The standardized mortality ratio of deaths among HIV-infected versus uninfected adults was 4.35 (95% CI 3.67–5.15), while the risk difference was 0.016 (95% CI 0.013–0.019). The HIV population attributable mortality fraction was 0.161 (95% CI 0.131–0.190). Sensitivity analyses demonstrated robustness of results.</p><p>Conclusions</p><p>Although 73.6% of adult PLHIV receive antiretrovirals in Nairobi, their risk of death is four-fold greater than in the uninfected, while 16.1% of all adult deaths in the city can be attributed to HIV infection. In order to further reduce HIV-associated mortality, high-burden countries may need to reach very high levels of diagnosis, treatment coverage, retention in care, and viral suppression.</p></div

Polling booth survey sample coverage of key populations in each study site across Kenya.

<p>Polling booth survey sample coverage of key populations in each study site across Kenya.</p