DISCUSSION: Twenty scientists from regions across the world developed this Expert Consensus Statement to address the use of HIV science by the criminal justice system. A detailed analysis of the best available scientific and medical research data on HIV transmission, treatment effectiveness and forensic phylogenetic evidence was performed and described so it may be better understood in criminal law contexts. Description of the possibility of HIV transmission was limited to acts most often at issue in criminal cases. The possibility of HIV transmission during a single, specific act was positioned along a continuum of risk, noting that the possibility of HIV transmission varies according to a range of intersecting factors including viral load, condom use, and other risk reduction practices. Current evidence suggests the possibility of HIV transmission during a single episode of sex, biting or spitting ranges from no possibility to low possibility. Further research considered the positive health impact of modern antiretroviral therapies that have improved the life expectancy of most people living with HIV to a point similar to their HIV-negative counterparts, transforming HIV infection into a chronic, manageable health condition. Lastly, consideration of the use of scientific evidence in court found that phylogenetic analysis alone cannot prove beyond reasonable doubt that one person infected another although it can be used to exonerate a defendant.
CONCLUSIONS: The application of up-to-date scientific evidence in criminal cases has the potential to limit unjust prosecutions and convictions. The authors recommend that caution be exercised when considering prosecution, and encourage governments and those working in legal and judicial systems to pay close attention to the significant advances in HIV science that have occurred over the last three decades to ensure current scientific knowledge informs application of the law in cases related to HIV.
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.
SETTING: Asian regional cohort incorporating 16 pediatric HIV services across 6 countries.
METHODS: Data from PHIVA (aged 10-19 years) who received combination antiretroviral therapy 2007-2016 were used to analyze LTFU through (1) an International epidemiology Databases to Evaluate AIDS (IeDEA) method that determined LTFU as >90 days late for an estimated next scheduled appointment without returning to care and (2) the absence of patient-level data for >365 days before the last data transfer from clinic sites. Descriptive analyses and competing-risk survival and regression analyses were used to evaluate LTFU epidemiology and associated factors when analyzed using each method.
RESULTS: Of 3509 included PHIVA, 275 (7.8%) met IeDEA and 149 (4.3%) met 365-day absence LTFU criteria. Cumulative incidence of LTFU was 19.9% and 11.8% using IeDEA and 365-day absence criteria, respectively. Risk factors for LTFU across both criteria included the following: age at combination antiretroviral therapy initiation <5 years compared with age ≥5 years, rural clinic settings compared with urban clinic settings, and high viral loads compared with undetectable viral loads. Age 10-14 years compared with age 15-19 years was another risk factor identified using 365-day absence criteria but not IeDEA LTFU criteria.
CONCLUSIONS: Between 12% and 20% of PHIVA were determined LTFU with treatment fatigue and rural treatment settings consistent risk factors. Better tracking of adolescents is required to provide a definitive understanding of LTFU and optimize evidence-based models of care.