Olga Morozova1, Robert E Booth2, Sergii Dvoriak3, Kostyantyn Dumchev4, Yana Sazonova5, Tetiana Saliuk6, Forrest W Crawford7. 1. Department of Biostatistics, Yale School of Public Health, 60 College St., New Haven, CT 06510, USA. Electronic address: olga.morozova@yale.edu. 2. Department of Psychiatry, University of Colorado Denver, 13001 East 17th Place, Aurora, CO 80045, USA. Electronic address: robert.booth@ucdenver.edu. 3. Academy of Labour, Social Relations and Tourism, 3-A Kiltseva doroha, Kyiv 03187, Ukraine; Ukrainian Institute on Public Health Policy, 5 Mala Zhytomyrska St., Office 61-А, Kyiv 01001, Ukraine. Electronic address: dvoryak@uiphp.org.ua. 4. Ukrainian Institute on Public Health Policy, 5 Mala Zhytomyrska St., Office 61-А, Kyiv 01001, Ukraine. Electronic address: dumchev@uiphp.org.ua. 5. Alliance for Public Health, 5 Dilova St., building 10-A, Kyiv 03150, Ukraine. Electronic address: sazonova@aph.org.ua. 6. Alliance for Public Health, 5 Dilova St., building 10-A, Kyiv 03150, Ukraine. Electronic address: salyuk@aph.org.ua. 7. Department of Biostatistics, Yale School of Public Health, 60 College St., New Haven, CT 06510, USA; Department of Ecology & Evolutionary Biology, Yale University, 165 Prospect St., New Haven, CT 06511, USA; Yale School of Management, Yale University, 165 Whitney Ave, New Haven, CT 06511, USA. Electronic address: forrest.crawford@yale.edu.
Abstract
BACKGROUND: Divergent estimates of HIV incidence among people who inject drugs (PWID) in Ukraine have been reported in modeling studies, longitudinal cohort studies, and recent infection assays used in cross-sectional surveys. Estimates range from 0.65 to 24.8 infections per 100 person-years with substantial regional variation. In this paper, we study the sources of this discrepancy. METHODS: We compared baseline characteristics of study subjects recruited in the cross-sectional integrated bio-behavioral surveillance surveys (IBBS) in 2011 and 2013, with those from the longitudinal network intervention trial (network RCT) conducted between 2010 - 2013, the study that found a remarkably high incidence of HIV among PWID in Ukraine. The analysis was conducted for two cities: Mykolaiv and Odesa. RESULTS: Significant differences were found in the characteristics of study subjects recruited in the IBBS surveys and the network RCT, in particular in Odesa, where the mismatch in the estimates of HIV incidence is greatest. In Odesa, recent syringe sharing was about three times as prevalent in the network RCT as in the IBBS; 39% of the network RCT and 16-18% of the IBBS participants indicated stimulants rather than opiates as their drug of choice; 97% of respondents in the network RCT and 45% in the IBBS-2013 reported injecting in a group over half of the time; and the average monthly number of injections in the network RCT was about twice that in the IBBS studies. CONCLUSIONS: Differences in study designs and sampling methodologies may be responsible for the substantial differences in HIV incidence estimates among PWID in Ukraine. The potential sources of selection bias differed between the studies and likely resulted in the recruitment of lower risk individuals into the IBBS studies compared to the network RCT. Risk stratification in the population of PWID may have implications for future surveillance and intervention efforts.
BACKGROUND: Divergent estimates of HIV incidence among people who inject drugs (PWID) in Ukraine have been reported in modeling studies, longitudinal cohort studies, and recent infection assays used in cross-sectional surveys. Estimates range from 0.65 to 24.8 infections per 100 person-years with substantial regional variation. In this paper, we study the sources of this discrepancy. METHODS: We compared baseline characteristics of study subjects recruited in the cross-sectional integrated bio-behavioral surveillance surveys (IBBS) in 2011 and 2013, with those from the longitudinal network intervention trial (network RCT) conducted between 2010 - 2013, the study that found a remarkably high incidence of HIV among PWID in Ukraine. The analysis was conducted for two cities: Mykolaiv and Odesa. RESULTS: Significant differences were found in the characteristics of study subjects recruited in the IBBS surveys and the network RCT, in particular in Odesa, where the mismatch in the estimates of HIV incidence is greatest. In Odesa, recent syringe sharing was about three times as prevalent in the network RCT as in the IBBS; 39% of the network RCT and 16-18% of the IBBSparticipants indicated stimulants rather than opiates as their drug of choice; 97% of respondents in the network RCT and 45% in the IBBS-2013 reported injecting in a group over half of the time; and the average monthly number of injections in the network RCT was about twice that in the IBBS studies. CONCLUSIONS: Differences in study designs and sampling methodologies may be responsible for the substantial differences in HIV incidence estimates among PWID in Ukraine. The potential sources of selection bias differed between the studies and likely resulted in the recruitment of lower risk individuals into the IBBS studies compared to the network RCT. Risk stratification in the population of PWID may have implications for future surveillance and intervention efforts.
Keywords:
HIV incidence; HIV surveillance; People who inject drugs (PWID); Respondent-driven sampling (RDS); Sampling methods in hidden populations; Ukraine
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