METHODS: We developed a linear optimisation model to estimate efficiency gains that could be achieved based on current procurement of OAT. We also developed a dynamic, compartmental population model of HIV transmission that included both injection and sexual risk to estimate the effect of OAT scale-up on HIV infections and mortality over a 10-year horizon. The compartmental population model was calibrated to HIV prevalence and incidence among PWID for 23 administrative regions of Ukraine. Sources for regional data included the SyrEx database, the Integrated Biological and Behavioral Survey, the Ukrainian Center for Socially Dangerous Disease Control of the Ministry of Health of Ukraine, the Public Health Center of the Ministry of Health of Ukraine, and the Ukrainian Census.
FINDINGS: Under a status-quo scenario (OAT coverage of 2·7% among PWID), the number of new HIV infections among PWID in Ukraine over the next 10 years was projected to increase to 58 820 (95% CI 47 968-65 535), with striking regional differences. With optimum allocation of OAT without additional increases in procurement, OAT coverage could increase from 2·7% to 3·3% by increasing OAT doses to ensure higher retention levels. OAT scale-up to 10% and 20% over 10 years would, respectively, prevent 4368 (95% CI 3134-5243) and 10 864 (7787-13 038) new HIV infections and reduce deaths by 7096 (95% CI 5078-9160) and 17 863 (12 828-23 062), relative to the status quo. OAT expansion to 20% in five regions of Ukraine with the highest HIV burden would account for 56% of new HIV infections and 49% of deaths prevented over 10 years.
INTERPRETATION: To optimise HIV prevention and treatment goals in Ukraine, OAT must be substantially scaled up in all regions. Increased medication procurement is needed, combined with optimisation of OAT dosing. Restricting OAT scale-up to some regions of Ukraine could benefit many PWID, but the regions most affected are not necessarily those with the highest HIV burden.
FUNDING: National Institute on Drug Abuse.
METHODS: The Filipino β-deletion was identified using gap-polymerase chain reaction (PCR) in the parents of transfusion dependent β-thalassaemia patients who were homozygous for the Filipino β-deletion in the indigenous population of Sabah, Malaysia. Hb subtypes were quantified on the BioRad Variant II Hb analyser. Concurrent α-thalassaemia was identified by multiplex gap-PCR for deletions and amplification refractory mutation system (ARMS)-PCR for non-deletional mutations.
RESULTS: The mean HbA2 level for Filipino β-thalassaemia trait was 5.9 ± 0.47 and with coinheritance of α-thalassaemia was 6.3 ± 0.44 (-α heterozygous) and 6.7 ± 0.36 (-α homozygous). The HbA2 levels were all >4% in keeping with the findings of classical β-thalassaemia trait and significantly higher than levels seen in non-deletional forms of β-thalassaemia.
CONCLUSION: The HbA2 level measured on the BioRad Variant II Hb analyser was lower than the level in the first description of the Filipino β-thalassaemia. β-thalassaemia trait with coinheritance of α-thalassaemia (-α) is associated with significantly higher HbA2 level.
METHODS: The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline.
RESULTS: The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs ≥ 15% were confirmed via Sanger sequencing.
CONCLUSIONS: The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL.