Hidden population size estimation and diagnostics using two respondent-driven samples with applications in Armenia.

Estimating the size of hidden populations is essential to understand the magnitude of social and healthcare needs, risk behaviors, and disease burden. However, due to the hidden nature of these populations, they are difficult to survey, and there are no gold standard size estimation methods. Many different methods and variations exist, and diagnostic tools are needed to help researchers assess method-specific assumptions as well as compare between methods. Further, because many necessary mathematical assumptions are unrealistic for real survey implementation, assessment of how robust methods are to deviations from the stated assumptions is essential. We describe diagnostics and assess the performance of a new population size estimation method, capture-recapture with successive sampling population size estimation (CR-SS-PSE), which we apply to data from 3 years of studies from three cities and three hidden populations in Armenia. CR-SS-PSE relies on data from two sequential respondent-driven sampling surveys and extends the successive sampling population size estimation (SS-PSE) framework by using the number of individuals in the overlap between the two surveys and a model for the successive sampling process to estimate population size. We demonstrate that CR-SS-PSE is more robust to violations of successive sampling assumptions than SS-PSE. Further, we compare the CR-SS-PSE estimates to population size estimations using other common methods, including unique object and service multipliers, wisdom of the crowd, and two-source capture-recapture to illustrate volatility across estimation methods.

Population Size Estimations Among Hidden Populations Using Respondent-Driven Sampling Surveys: Case Studies From Armenia.

BACKGROUND: Estimates of the sizes of hidden populations, including female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID), are essential for understanding the magnitude of vulnerabilities, health care needs, risk behaviors, and HIV and other infections. OBJECTIVE: This article advances the successive sampling-population size estimation (SS-PSE) method by examining the performance of a modification allowing visibility to be jointly modeled with population size in the context of 15 datasets. Datasets are from respondent-driven sampling (RDS) surveys of FSW, MSM, and PWID from three cities in Armenia. We compare and evaluate the accuracy of our imputed visibility population size estimates to those found for the same populations through other unpublished methods. We then suggest questions that are useful for eliciting information needed to compute SS-PSE and provide guidelines and caveats to improve the implementation of SS-PSE for real data. METHODS: SS-PSE approximates the RDS sampling mechanism via the successive sampling model and uses the order of selection of the sample to provide information on the distribution of network sizes over the population members. We incorporate visibility imputation, a measure of a person's propensity to participate in the study, given that inclusion probabilities for RDS are unknown and social network sizes, often used as a proxy for inclusion probability, are subject to measurement errors from self-reported study data. RESULTS: FSW in Yerevan (2012, 2016) and Vanadzor (2016) as well as PWID in Yerevan (2014), Gyumri (2016), and Vanadzor (2016) had great fits with prior estimations. The MSM populations in all three cities had inconsistencies with expert prior values. The maximum low prior value was larger than the minimum high prior value, making a great fit impossible. One possible explanation is the inclusion of transgender individuals in the MSM populations during these studies. There could be differences between what experts perceive as the size of the population, based on who is an eligible member of that population, and what members of the population perceive. There could also be inconsistencies among different study participants, as some may include transgender individuals in their accounting of personal network size, while others may not. Because of these difficulties, the transgender population was split apart from the MSM population for the 2018 study. CONCLUSIONS: Prior estimations from expert opinions may not always be accurate. RDS surveys should be assessed to ensure that they have met all of the assumptions, that variables have reached convergence, and that the network structure of the population does not have bottlenecks. We recommend that SS-PSE be used in conjunction with other population size estimations commonly used in RDS, as well as results of other years of SS-PSE, to ensure generation of the most accurate size estimation.

Optimizing HIV/AIDS resources in Armenia: increasing ART investment and examining HIV programmes for seasonal migrant labourers.

INTRODUCTION: HIV prevalence is declining in key populations in Armenia including in people who inject drugs (PWID), men who have sex with men, prison inmates, and female sex workers (FSWs); however, prevalence is increasing among Armenians who seasonally migrate to work in countries with higher HIV prevalence, primarily to the Russian Federation. METHODS: We conducted a modelling study using the Optima model to assess the optimal resource allocation to meet targets from the 2013 to 2016 national strategic plan to minimize HIV incidence and AIDS-related deaths by 2020. Demographic, epidemiological, behavioural, and programme cost data from 2000 through 2014 were used to inform the model. The levels of coverage that could be attained among targeted populations with different investments, as well as their expected outcomes, were determined. In the absence of evidence of the efficacy of HIV programmes targeted at seasonal labour migrants, we conducted a sensitivity analysis to determine the cost-effective funding threshold for the seasonal labour migrant programme. RESULTS: The optimization analysis revealed that shifts in funding allocations could further minimize incidence and deaths by 2020 within the available resource envelope. The largest emphasis should be on antiretroviral therapy (ART), with the optimal investment to increase treatment coverage by 40%. Optimal investments also involve increases in opiate substitution therapy and FSW programmes, as well as maintenance of other prevention programmes for PWID and prevention of mother-to-child transmission. Additional funding for these increases should come from budgets for general population programmes. This is projected to avert 17% of new infections and 29% of AIDS-related deaths by 2020 compared to a baseline scenario of maintaining 2013 spending. Our sensitivity analysis demonstrated that, at current spending, coverage of annual testing among migrants of at least 43% should be achieved to warrant continuation of funding for this programme. CONCLUSIONS: Optimization of HIV/AIDS investment in Armenia, with a main priority for scaling-up ART, and less emphasis on primary prevention in the general non-key population could significantly reduce incidence and deaths by 2020.

HIV Type 1 Subtype A1 Dominates in Armenia.

OBJECTIVE: There is scarce information about the molecular epidemiology of HIV-infection in Armenia (former USSR). The objective of this work was to estimate the distribution of HIV-1 subtypes in this country and get any information about HIV drug resistance in naÏve patients. DESIGN: A joint study involving 78 patients was carried out in Yerevan, Armenia and Moscow, Russia in 2009-2013. The cohort studies included mostly IDUs (28.2%) and heterosexuals (69.2%). RESULTS: The phylogenetic analyses based on population sequencing of partial pol gene found subtype A1 being the most prevalent (92.3%), followed by subtype B (3.9%). The HIV-1 tropism inferred from env V3-loop sequences was determined in 27 samples, among them R5-tropic viruses were found in 13 (48.1%) patients and X4- variants--in 14 (51.9%) patients. The prevalence of drug resistance in naïve patients was low (1.5%) with the only one mutation K219Q found. CONCLUSION: The composition and distribution of HIV-1 genetic variants in Armenia are evidently influenced by the Russian and other FSU countries epidemic, due to the significant volume of Armenian migrant/re-emigrant flows. Continued surveillance of HIV-1 circulating subtypes and drug resistance in Armenia is important for the proper management of HIV infection in this country.

Access to antiretroviral therapy and survival in eastern Europe and central Asia: a case study in Armenia.

INTRODUCTION: Antiretroviral therapy (ART) substantially improves the health of people living with HIV and contributes to preventing new infections. While HIV incidence is decreasing in most regions, the epidemic in eastern Europe continues to rise, as new infections currently outnumber the rate of ART initiation. In this study, we assess ART use in Armenia and its impact on the number of AIDS diagnoses and mortality. METHODS: National surveillance data were obtained from the National Centre for AIDS Prevention, Armenia. Cox-proportional hazard models were used to determine the effect of demographic and clinical risk factors, including access to ART, on AIDS and mortality. RESULTS: Among people diagnosed with HIV since 2005, approximately 40% per year were diagnosed with CD4<200 cells per mL. Overall, 232 people (57.1%) with AIDS or a low CD4 count had not received ART by the end of 2010. Mortality was 34.1% among people living with HIV who did not initiate ART, and 0.3% among people who received ART. Among people diagnosed with HIV from 1996 to 2010, age at diagnosis, no use of ART, likely mode of transmission, likely place of transmission, low baseline CD4 count and no STI diagnosis at last contact are significantly associated with death. DISCUSSION: In Armenia, HIV is frequently diagnosed at a late stage of disease, indicating low testing rates. Of people diagnosed with HIV and in need of ART, a large proportion (approximately 60%) either do not provide consent for treatment, or are who migrants who cannot be located. CONCLUSIONS: Globally, the scale-up of ART has resulted in substantial reductions in mortality among individuals initiating therapy. However, in an era of momentum for treatment as prevention, treatment levels are not at adequate levels for preventing morbidities and mortality in some settings. Particular focus should be placed on key at-risk subgroups.