Background In the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality.Methods We engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts.Findings Modelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuber culosis incidence by 38% (95% Bayesian credible intervals 27-43) in India, 31% (25-41) in Kenya, and 27% (17-41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private healthcare sector in India, missed diagnosis in health care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on highquality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis.Interpretation Linked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality.

Introduction Isoniazid preventive therapy (IPT) taken by People Living with HIV (PLHIV) protects against active tuberculosis (TB). Despite its recommendation, data is scarce on the uptake of IPT among PLHIV and factors associated with treatment outcomes. We aimed at determining the proportion of PLHIV initiated on IPT, assessed TB screening practices during and after IPT and IPT treatment outcomes. Methods A retrospective cohort study of a representative sample of PLHIV initiated on IPT between July 2015 and June 2018 in Kenya. For PLHIV initiated on IPT during the study period, we abstracted patient IPT uptake data from the National data warehouse. In contrast, we obtained information on socio-demographic, TB screening practices, IPT initiation, follow up, and outcomes from health facilities' patient record cards, IPT cards, and IPT registers. Further, we assessed baseline characteristics as potential correlates of developing active TB during and after treatment and IPT completion using multivariable logistic regression. Results From the data warehouse, 138,442 PLHIV were enrolled into ART during the study period and initiated 95,431 (68.9%) into IPT. We abstracted 4708 patients’ files initiated on IPT, out of which 3891(82.6%) had IPT treatment outcomes documented, 4356(92.5%) had ever screened for TB at every clinic visit, and 4,243(90.1%) had documentation of TB screening on the IPT tool before IPT initiation. 3712(95.4%) of patients with documented IPT treatment outcomes completed their treatment. 42(0.89%) of the abstracted patients developed active TB,16(38.1%) during, and 26(61.9%) after completing IPT. Follow up for active TB at 6-month post-IPT completion was done for 2729(73.5%) of patients with IPT treatment outcomes. Sex, Viral load suppression, and clinic type were associated with TB development (p<0.05). Levels 4, 5, FBO, and private facilities and IPT prescription practices were associated with IPT completion (p<0.05). Conclusion IPT initiation stands at two-thirds of the PLHIV, with a high completion rate. TB screening practices were better during IPT than after completion. Development of active TB during and after IPT emphasizes the need for a keen follow up.

Background The dual challenge of low diagnostic sensitivity of microscopy test and technical challenge of performing a TB culture test poses a problem for case detection and initiation of Tuberculosis (TB) second-line treatment. There is thus need for a rapid, reliable and easily accessible assay. This comparative analysis was performed to assess diagnostic performance characteristics of GeneXpert MTB/RIF and Line Probe Assay (LPA). Methods Three hundred twenty nine sputum samples of patients across the 47 counties in Kenya suspected to have drug resistant TB were picked and subjected to GeneXpert, LPA and Culture MGIT at the National TB Reference Laboratory. Sensitivity, specificity and predictive values were then determined to assess the performance characteristics of the various assays. Results Against culture MGIT as the gold standard for TB diagnosis, GeneXpert had a sensitivity, specificity, positive predictive value, and negative predictive value of 78.5, 64.9, 59.4 and 82.2% respectively while LPA had 98.4, 66.0, 65.4 and 98.4%. For diagnosis of rifampicin mono-resistance GeneXpert had a moderate agreement (Kappa 0.59, P < 0.01) (sensitivity 62.50%, specificity 96.50%) while LPA that had almost perfect agreement (Kappa = 0.89, p < 0.01) with a (sensitivity 90.0% and specificity 99.1%). Conclusion LPA has a better performance characteristic to GeneXpert and an alternative to culture with regards to detection of RIF’s mono-resistance.

IntroductionWe aimed to quantify health outcomes and programmatic implications of scaling up cervical cancer (CC) screening and treatment options for women living with HIV in care aged 18–65 in Kenya.MethodsMathematical model comparing from 2020 to 2040: (1) visual inspection with acetic acid (VIA) and cryotherapy (Cryo); (2) VIA and Cryo or loop excision electrical procedure (LEEP), as indicated; (3) human papillomavirus (HPV)-DNA testing and Cryo or LEEP; and (4) enhanced screening technologies (either same-day HPV-DNA testing or digitally enhanced VIA) and Cryo or LEEP. Outcomes measured were annual number of CC cases, deaths, screening and treatment interventions, and engaged in care (numbers screened, treated and cured) and five yearly age-standardised incidence.ResultsAll options will reduce CC cases and deaths compared with no scale-up. Options 1–3 will perform similarly, averting approximately 28 000 (33%) CC cases and 7700 (27%) deaths. That is, VIA screening would yield minimal losses to follow-up (LTFU). Conversely, LTFU associated with HPV-DNA testing will yield a lower care engagement, despite better diagnostic performance. In contrast, option 4 would maximise health outcomes, averting 43 200 (50%) CC cases and 11 800 (40%) deaths, given greater care engagement. Yearly rescreening with either option will impose a substantial burden on the health system, which could be reduced by spacing out frequency to three yearly without undermining health gains.ConclusionsBeyond the specific choice of technologies to scale up, efficiently using available options will drive programmatic success. Addressing practical constraints around diagnostics’ performance and LTFU will be key to effectively avert CC cases and deaths.

BACKGROUND: TB is the leading cause of mortality among people living with HIV (PLHIV), for whom isoniazid preventive therapy (IPT) has a proven mortality benefit. Despite WHO recommendations, countries have been slow in scaling up IPT. This study describes processes, challenges, solutions, outcomes and lessons learned during IPT scale‐up in Kenya.METHODS: We conducted a desk review and analyzed aggregated Ministry of Health (MOH) IPT enrollment data from 2014 to 2018 to determine trends and impact of program activities. We further analyzed IPT completion reports for patients initiated from 2015 to 2017 in 745 MOH sites in Nairobi, Central, Eastern and Western Kenya.RESULTS: IPT was scaled up 75‐fold from 2014 to 2018: the number of PLHIV covered increased from 9,981 to 749,890. The highest percentage increases in the cumulative number of PLHIV on IPT were seen in the quarters following IPT pilot projects in 2014 (49%), national launch in 2015 (54%), and HIV treatment acceleration in 2016 (158%). Among 250,069 patients initiating IPT from 2015 to 2017, 97.5% completed treatment, 0.2% died, 0.8% were lost to follow‐up, 1.0% were not evaluated, and 0.6% discontinued treatment.CONCLUSIONS: IPT can be scaled up rapidly and effectively among PLHIV. Deliberate MOH efforts, strong leadership, service delivery integration, continuous mentorship, stakeholder involvement, and accountability are critical to program success.

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 two 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. Base calling comparison between the two 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 one 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.

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.

15Introduction: Isoniazid preventive therapy (IPT) taken by People Living with HIV (PLHIV) protects 16 against tuberculosis (TB). Despite its recommendation, there is scarcity of data on the uptake of 17 IPT among PLHIV and factors associated with treatment outcomes. We aimed to determine the 18 proportion of PLHIV initiated on IPT, IPT treatment outcomes and screening for TB during and 19 after IPT. 20Methods: A retrospective cohort study of a representative sample of PLHIV initiated on IPT 21 between July 2015 and June 2018 in Kenya. We abstracted information on socio-demographic, 22TB screening practices, IPT initiation, follow up, and outcomes from health facilities' patient 23 record cards, IPT cards and IPT registers. Further, we assessed baseline characteristics as 24 potential correlates of developing TB during and after treatment and IPT completion using 25 multivariable logistic regression. 26 Results: We enrolled 138,442 PLHIV into ART during the study period and initiated 95,431 27 (68.9%) into IPT. Abstracted files for 4708 patients initiated on IPT, out of which 3891(82.6%) 28 had IPT treatment outcomes documented, 4356(92.5%) had ever been screened for TB at every 29 clinic visit and 4,243(90.1%) had documentation of TB screening on the IPT tool before IPT Page | ii 30 initiation. 3712(95.4%) of patients with documented IPT treatment outcomes completed their 31 treatment. 42(0.89%) of the abstracted patients developed active TB ,16(38.1%) during and 32 26(61.9%) after completing IPT. Follow up for TB at 6-month post-IPT completion was done for 33 2729(73.5%) of patients with IPT treatment outcomes. Sex, Viral load suppression and clinic 34 type were associated with TB development (p<0.05). Levels 4, 5, FBO, and private facilities 35and IPT prescription practices were associated with IPT completion (p<0.05). 36Conclusion: Two-thirds of PLHIV were initiated on IPT, with a high completion rate. TB screening 37 practices were better during IPT than after completion. Development of TB during and after IPT 38 emphasises need for keen follow up.