Uptake and effect of universal test-and-treat on twelve months retention and initial virologic suppression in routine HIV program in Kenya.

Early combination antiretroviral therapy (cART), as recommended in WHO's universal test-and-treat (UTT) policy, is associated with improved linkage to care, retention, and virologic suppression in controlled studies. We aimed to describe UTT uptake and effect on twelve-month non-retention and initial virologic non-suppression (VnS) among HIV infected adults starting cART in routine HIV program in Kenya. Individual-level HIV service delivery data from 38 health facilities, each representing 38 of the 47 counties in Kenya were analysed. Adults (>15 years) initiating cART between the second-half of 2015 (2015HY2) and the first-half of 2018 (2018HY1) were followed up for twelve months. UTT was defined based on time from an HIV diagnosis to cART initiation and was categorized as same-day, 1-14 days, 15-90 days, and 91+ days. Non-retention was defined as individuals lost-to-follow-up or reported dead by the end of the follow up period. Initial VnS was defined based on the first available viral load test with >400 copies/ml. Hierarchical mixed-effects survival and generalised linear regression models were used to assess the effect of UTT on non-retention and VnS, respectively. Of 8592 individuals analysed, majority (n = 5864 [68.2%]) were female. Same-day HIV diagnosis and cART initiation increased from 15.3% (2015HY2) to 52.2% (2018HY1). The overall non-retention rate was 2.8 (95% CI: 2.6-2.9) per 100 person-months. When compared to individuals initiated cART 91+ days after a HIV diagnosis, those initiated cART on the same day of a HIV diagnosis had the highest rate of non-retention (same-day vs. 91+ days; aHR, 1.7 [95% CI: 1.5-2.0], p<0.001). Of those included in the analysis, 5986 (69.6%) had a first viral load test done at a median of 6.3 (IQR, 5.6-7.6) months after cART initiation. Of these, 835 (13.9%) had VnS. There was no association between UTT and VnS (same-day vs. 91+ days; aRR, 1.0 [95% CI: 0.9-1.2], p = 0.664). Our findings demonstrate substantial uptake of the UTT policy but poor twelve-month retention and lack of an association with initial VnS from routine HIV settings in Kenya. These findings warrant consideration for multi-pronged program interventions alongside UTT policy for maximum intended benefits in Kenya.

All-cause and cause-specific mortality rates for Kisumu County: a comparison with Kenya, low-and middle-income countries.

BACKGROUND: Understanding the magnitude and causes of mortality at national and sub-national levels for countries is critical in facilitating evidence-based prioritization of public health response. We provide comparable cause of death data from Kisumu County, a high HIV and malaria-endemic county in Kenya, and compared them with Kenya and low-and-middle income countries (LMICs). METHODS: We analyzed data from a mortuary-based study at two of the largest hospital mortuaries in Kisumu. Mortality data through 2019 for Kenya and all LMICs were downloaded from the Global Health Data Exchange. We provided age-standardized rates for comparisons of all-cause and cause-specific mortality rates, and distribution of deaths by demographics and Global Burden of Disease (GBD) classifications. RESULTS: The all-cause age-standardized mortality rate (SMR) was significantly higher in Kisumu compared to Kenya and LMICs (1118 vs. 659 vs. 547 per 100,000 population, respectively). Among women, the all-cause SMR in Kisumu was almost twice that of Kenya and double the LMICs rate (1150 vs. 606 vs. 518 per 100,000 population respectively). Among men, the all-cause SMR in Kisumu was approximately one and a half times higher than in Kenya and nearly double that of LMICs (1089 vs. 713 vs. 574 per 100,000 population). In Kisumu and LMICs non-communicable diseases accounted for most (48.0 and 58.1% respectively) deaths, while in Kenya infectious diseases accounted for the majority (49.9%) of deaths. From age 10, mortality rates increased with age across all geographies. The age-specific mortality rate among those under 1 in Kisumu was nearly twice that of Kenya and LMICs (6058 vs. 3157 and 3485 per 100,000 population, respectively). Mortality from injuries among men was at least one and half times that of women in all geographies. CONCLUSION: There is a notable difference in the patterns of mortality rates across the three geographical areas. The double burden of mortality from GBD Group I and Group II diseases with high infant mortality in Kisumu can guide prioritization of public health interventions in the county. This study demonstrates the importance of establishing reliable vital registry systems at sub-national levels as the mortality dynamics and trends are not homogeneous.

The COVID-19 pandemic and disruptions to essential health services in Kenya: a retrospective time-series analysis.

BACKGROUND: Public health emergencies can disrupt the provision of and access to essential health-care services, exacerbating health crises. We aimed to assess the effect of the COVID-19 pandemic on essential health-care services in Kenya. METHODS: Using county-level data routinely collected from the health information system from health facilities across the country, we used a robust mixed-effect model to examine changes in 17 indicators of essential health services across four periods: the pre-pandemic period (from January, 2018 to February, 2020), two pandemic periods (from March to November 2020, and February to October, 2021), and the period during the COVID-19-associated health-care workers' strike (from December, 2020 to January, 2021). FINDINGS: In the pre-pandemic period, we observed a positive trend for multiple indicators. The onset of the pandemic was associated with statistically significant decreases in multiple indicators, including outpatient visits (28·7%; 95% CI 16·0-43·5%), cervical cancer screening (49·8%; 20·6-57·9%), number of HIV tests conducted (45·3%; 23·9-63·0%), patients tested for malaria (31·9%; 16·7-46·7%), number of notified tuberculosis cases (26·6%; 14·7-45·1%), hypertension cases (10·4%; 6·0-39·4%), vitamin A supplements (8·7%; 7·9-10·5%), and three doses of the diphtheria, tetanus toxoid, and pertussis vaccine administered (0·9%; 0·5-1·3%). Pneumonia cases reduced by 50·6% (31·3-67·3%), diarrhoea by 39·7% (24·8-62·7%), and children attending welfare clinics by 39·6% (23·5-47·1%). Cases of sexual violence increased by 8·0% (4·3-25·0%). Skilled deliveries, antenatal care, people with HIV infection newly started on antiretroviral therapy, confirmed cases of malaria, and diabetes cases detected were not significantly affected negatively. Although most of the health indicators began to recover during the pandemic, the health-care workers' strike resulted in nearly all indicators falling to numbers lower than those observed at the onset or during the pre-strike pandemic period. INTERPRETATION: The COVID-19 pandemic and the associated health-care workers' strike in Kenya have been associated with a substantial disruption of essential health services, with the use of outpatient visits, screening and diagnostic services, and child immunisation adversely affected. Efforts to maintain the provision of these essential health services during a health-care crisis should target the susceptible services to prevent the exacerbation of associated disease burdens during such health crises. FUNDING: Bill & Melinda Gates Foundation.

Impact of nucleos(t)ide reverse transcriptase inhibitor resistance on dolutegravir and protease-inhibitor-based regimens in children and adolescents in Kenya.

We assessed the impact of using dolutegravir or a protease inhibitor with an inactive nucleoside-reverse transcriptase inhibitor (NRTI) in children and adolescents. We observed high-levels of viral suppression among those on tenofovir-lamivudine-dolutegravir even in presence of an inactive NRTI backbone but lower levels among those on protease inhibitors, especially those retained on an inactive abacavir. Although tenofovir may be recycled with dolutegravir, more studies are needed to determine if abacavir can be reused with dolutegravir or protease inhibitors.

Impact of the First Wave of the COVID-19 Pandemic on HIV/AIDS Programming in Kenya: Evidence from Kibera Informal Settlement and COVID-19 Hotspot Counties.

The study sought to determine the impact of COVID-19 on HIV/AIDS programming in the Kibera informal settlement and COVID-19 hotspot counties during the first wave of the pandemic. The study was conducted in two phases. The first phase entailed the analysis of HIV care and treatment secondary data (2018-2020) from the Kenya Health Information System. In the second phase, a prospective cohort study was conducted among people living with HIV in the Kibera informal settlement. A total of 176 participants aged 18 years and above accessing HIV services at selected healthcare facilities in Kibera were randomly sampled from facility electronic medical records and followed up for three months. Socio-demographics and contact details were abstracted from the records and telephone interviews were conducted with consenting participants. Results from the retrospective review of HIV program data indicated a 56% (p < 0.000, 95% CI: 31.3%-62.8%) reduction in uptake of HIV services. Clients starting antiretroviral therapy (ART) reduced significantly by 48% (p < 0.001, 95% CI: 35.4%-77%) in hotspot counties. However, pre-exposure prophylaxis uptake increased significantly by 24% (p < 0.019, 95% CI: 4%-49%). In Kibera, 14% reported missing medications at the onset of the COVID-19 pandemic because of lack of food (38%) and government measures (11%), which affected ART access; 11% did not access health facilities due to fear of contracting COVID-19, government regulations and lack of personal protective equipment. Socioeconomic factors, food insecurity and government measures affected uptake of HIV/AIDS services; hence, the need for scaling up measures to increase access to HIV/AIDS services during the onset of pandemics.

From Sequence Data to Patient Result: A Solution for HIV Drug Resistance Genotyping With Exatype, End to End Software for Pol-HIV-1 Sanger Based Sequence Analysis and Patient HIV Drug Resistance Result Generation.

INTRODUCTION: With the rapid scale-up of antiretroviral therapy (ART) to treat HIV infection, there are ongoing concerns regarding probable emergence and transmission of HIV drug resistance (HIVDR) mutations. This scale-up has to lead to an increased need for routine HIVDR testing to inform the clinical decision on a regimen switch. Although the majority of wet laboratory processes are standardized, slow, labor-intensive data transfer and subjective manual sequence interpretation steps are still required to finalize and release patient results. We thus set out to validate the applicability of a software package to generate HIVDR patient results from raw sequence data independently. METHODS: We assessed the performance characteristics of Hyrax Bioscience's Exatype (a sequence data to patient result, fully automated sequence analysis software, which consolidates RECall, MEGA X and the Stanford HIV database) against the standard method (RECall and Stanford database). Exatype is a web-based HIV Drug resistance bioinformatic pipeline available at sanger.exatype.com. To validate the exatype, we used a test set of 135 remnant HIV viral load samples at the National HIV Reference Laboratory (NHRL). RESULT: We analyzed, and successfully generated results of 126 sequences out of 135 specimens by both Standard and Exatype software. Result production using Exatype required minimal hands-on time in comparison to the Standard (6 computation-hours using the standard method versus 1.5 Exatype computation-hours). Concordance between the 2 systems was 99.8% for 311,227 bases compared. 99.7% of the 0.2% discordant bases, were attributed to nucleotide mixtures as a result of the sequence editing in Recall. Both methods identified similar (99.1%) critical antiretroviral resistance-associated mutations resulting in a 99.2% concordance of resistance susceptibility interpretations. The Base-calling comparison between the 2 methods had Cohen's kappa (0.97 to 0.99), implying an almost perfect agreement with minimal base calling variation. On a predefined dataset, RECall editing displayed the highest probability to score mixtures accurately 1 vs. 0.71 and the lowest chance to inaccurately assign mixtures to pure nucleotides (0.002-0.0008). This advantage is attributable to the manual sequence editing in RECall. CONCLUSION: The reduction in hands-on time needed is a benefit when using the Exatype HIV DR sequence analysis platform and result generation tool. There is a minimal difference in base calling between Exatype and standard methods. Although the discrepancy has minimal impact on drug resistance interpretation, allowance of sequence editing in Exatype as RECall can significantly improve its performance.