Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

Transcription

1 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM Recent HIV Infections among MSM in Sialon II Results from the Avidity Index Component of the Sialon II RDS survey

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3 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM Recent HIV Infections among MSM in Sialon II Results from the Avidity Index Component of the Sialon II RDS survey Co-funded by the Health Programme of the European Union This document is based on data from the Sialon II project, funded under the European Commission s (EC) Public Health Programme (Work Plan 2010). The sole responsibility lies with the authors of this report and the Commission is not responsible for any use that may be made of the information contained therein

4 Introduction 9 RITA assay 10 The HIV Avidity Index (AI) in SIALON II 12 Procedures 13 Index Respondent-driven Sampling (RDS) method Sample collection AI lab procedure Serum sample collection Results 15 AI results Results of the post-test counselling Conclusions 20 References 22 Annex 25 Protocol for the Avidity Index measurement using the Architect HIV Ag/Ab Combo Testing for the AI: Algorithm using Architect HIV Ag/Ab Combo HIV flowchart in RDS method

5 List of authors Barbara Suligoi Centro Operativo AIDS, Istituto Superiore di Sanità, Rome, Italy Vincenza Regine Centro Operativo AIDS, Istituto Superiore di Sanità, Rome, Italy Lorenzo Gios Azienda Ospedaliera Integrata di Verona, Verona, Italy Massimo Mirandola Azienda Ospedaliera Integrata di Verona, Verona, Italy Anna Rodella Spedali Civili di Brescia, Brescia, Italy Antonella Zorzi Azienda Ospedaliera Integrata di Verona, Verona, Italy

6 List of acronyms Ab Antibody AI Avidity Index AIDS Acquired Immune Deficiency Syndrome Ag Antigen ART Antiretroviral Therapy CD Compact Disk CLSI Clinical and Laboratory Standards Institute ECDC European Centre for Disease Prevention and Control EIA Enzyme Immunoassay EU/EEA European Union / European Economic Area G Guanidine hydrochloride HIV Human Immunodeficiency Virus HIV-1 Human Immunodeficiency Virus type 1 IDU Injecting Drug User IQC Internal Quality Control HBV Hepatitis B virus HCL Hydrochloric Acid HCV Hepatitis C virus HRP Human Reproduction Programme IQR Interquartile Range MSM Men who have sex with men NY New York PBS Phosphate-Buffered Saline RDS Respondent-driven Sampling RHI Recently-acquired HIV Infection RITA Recent Infection Testing Algorithms S/CO Sample/Cut-Off USA United States of America WB Western Blot WHO World Health Organization

7 Acknowledgments Authors would like to thank the colleagues from laboratories for their contribution in the context of the Sialon II RDS survey. Verona, Italy Giuseppe Cornaglia, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Antonella Zorzi, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Elisabetta Tonolli, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Giuliana Lo Cascio, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Teresa Todeschini, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Manuela Recchia, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Lorella Pattini, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Maria Rocca, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Alessandra Bighignoli, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Anita Galardi, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Loredana Martini, Azienda Ospedaliera Universitaria Integrata, Verona, Italy Bratislava, Slovakia Danica Staneková, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia Monika Hábeková, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia Tatiana Drobková, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia Zuzana Chabadová, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia Soňa Wimmerová, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia Maria Mojzesová, Slovak Medical University, NRC for HIV/AIDS prevention, Bratislava, Slovakia

8 Acknowledgments Vilnius, Lithuania Saulius Caplinskas, Centre for Communicable Diseases and AIDS, Vilnius, Lithuania Bucharest, Romania Alexandru Rafila, National Institute for infectious Diseases Prof. Dr. Matei Bals, University of Medicine and Pharmacy Carol Davila, Bucharest, Romania Daniela Pitigoi, National Institute for infectious Diseases Prof. Dr. Matei Bals, University of Medicine and Pharmacy Carol Davila, Bucharest, Romania Madalina Popa, National Institute for infectious Diseases Prof. Dr. Matei Bals Monica Likker, National Institute for infectious Diseases Prof. Dr. Matei Bals

9 Introduction In European countries (EU/EAA) the HIV infection is concentrated in three subgroups of population: men who have sex with men, migrants, and people who inject drugs. The introduction of antiretroviral therapy (ART) in the nineties improved life expectancy for people with HIV diagnosis. Improved life expectancy and the continuing HIV transmission has resulted increases in HIV prevalence and in new HIV diagnoses in all European countries. These changes in HIV epidemic in Europe make it increasingly important to understand the transmission dynamics of the HIV epidemic and monitor prevention efforts in populations most at risk. In addition, the identification of newly acquired HIV infection provides important information on the dynamics of the epidemic, transmission networks, and patterns of transmitted drug resistance, guides public health intervention programs, and identifies candidates for clinical trials and vaccine strategies targeting early infection. The gold standard for estimating HIV incidence is through prospective cohort studies of HIV-negative persons followed over time. Because of the high complexity and costs to implement such studies, HIV incidence is alternatively estimated using mathematical models that infer adult incidence based on HIV prevalence data from cross-sectional serologic surveys and mortality assumptions. HIV incidence can also be estimated using serologic assays that directly measure recent HIV infection in cross-sectional specimens. Tests to differentiate recent from established infections is known as Recent Infection Testing Algorithms (RITA), it have become an increasingly used approach to monitoring recent HIV infections and estimating HIV incidence in several countries. Several tests for recent infection has been developed over the last decade; each quantifies a different aspect of the natural history of an individual HIV infection. The literature provides several estimates in subpopulations, highlighting studies that have employed a RITA assay in order to produce estimates of HIV incidence (1). Considering a framework of HIV incidence studies in Europe ECDC has suggested the need to incorporate RITA assays as part of large-scale studies or surveillance systems. For this purpose European Centre for Disease Prevention and Control has developed a technical guide on how to integrate RITA as part of routine HIV surveillance (2). Some European countries have already applied RITA method to national surveillance data (3-6). Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 9

10 RITA assay The recent HIV infection testing algorithm (RITA) is a generic term for several laboratory techniques that can be used to differentiate recent from established infections with HIV. RITA methods have been developed, primarily for epidemiological purposes, although they also have a potentially important role in individual diagnosis. There are several other approaches that identify acute seroconverters, but RITA methods are distinguished by their ability to identify infections that occurred during an extended period of 4-6 months prior to sampling (1, 7). These methods are intended to be applied to individual specimens in which the presence of anti-hiv-1 antibody has already been confirmed. While the RITA techniques have been employed on an individual basis, their main usefulness lies in the potential of estimating the rate of acquisition of new HIV infection, or incidence, in a population by application to cross-sectional sero-surveys. RITA techniques facilitate the timely monitoring of the impact on HIV incidence of factors such as interventions, demographic factors and behavioural patterns. The ability to segregate recently-acquired human immunodeficiency virus type 1 (HIV-1) infections (RHI), i.e. infections acquired in the previous few months, from established ( prevalent ) infections is a valuable tool for real-time measurement of the changing patterns of HIV transmission (7). The key advantages of the laboratorybased method for measuring incidence are that laboratory assays do not require longitudinal follow-up of persons over time, the collection of serial blood specimens to estimate HIV-1 incidence, or assumptions about prevalence and mortality needed for mathematical models. These assays allow the incidence of HIV infection to be estimated in cross-sectional surveys, which are simpler to conduct, less expensive, shorter in time, and less resource intensive than the longitudinal studies usually used to investigate incidence (7, 8). The RITA approach offers a number of important advantages over other methods for determining HIV incidence. Unlike cohort studies which require repeated testing of individuals, and where results may be biased by people leaving the study, RITA testing can be carried out retrospectively on stored single specimens from cross-sectional sero-surveys. In comparison with cohort studies, applying the RITA approach is cheaper, quicker and simpler to perform. Furthermore, RITA testing can be performed on a real-time basis thus allowing a measure of recent infection at the time of a study as opposed to incidence derived from a cohort study, which cannot be ascertained until after the follow-up sample has been collected and tested. Several approaches have been described that distinguish recent from established infection: one of these assays is the avidity index (AI) for 10 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

11 antibodies against HIV (9-11). The inclusion of the AI in an EU bio-behavioural survey is crucial in both an epidemiological, prevention, and impact-evaluation level. Specifically, by correlating behavioural information with the AI result we can obtain more detailed information on HIV incidence among MSM, describe HIV trends in specific subgroups, make projections on future trends, improve contact tracing and partner notification, tailor prevention messages, and measure the efficacy of prevention programmes. Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 11

12 The HIV Avidity Index (AI) in Sialon II The AI is a marker of recent infection and is routinely used for several infectious diseases, including toxoplasmosis, rubella, and cytomegalovirus infection. Moreover, it has been applied for a number of other infectious agents, such as hepatitis C virus, hepatitis B virus, human herpes viruses 6 and 7, and varicella-zoster virus (12-16). The AI is based on the rationale that antibodies produced in the early phase of infection show a low avidity for the antigen. In fact, it is well known that antibody avidity increases progressively with time after exposure to an immunogen (2). The method used to measure the HIV AI in SIALON II was described by Suligoi et al. and is based on evidence that the HIV-antibody avidity/affinity for the HIV antigen is low in the first months of infection (0 to 12 months from infection) and increases with time until complete antibody maturation (9-11,17). Low HIV AI is indicative of recent infection (for more detailed information, see HRP Research Proposal: Project details). The AI is a relevant tool to monitor closely the HIV epidemic across Europe in MSM populations, as it allows to assessing not only HIV incidence among MSM but also changes in factors associated with the acquisition of HIV infection. By detecting emerging trends and identifying high-risk groups, the AI provides insights in prevention needs among MSM optimizing target interventions and resource allocation. Moreover, the results of the AI can be used to evaluate the impact of prevention programs on the rate of new HIV infections. The AI testing procedure that we propose is fully automated and has several advantages, such as increased throughput, higher reproducibility, no need for specific technical skills, and easy comparability of results obtained in different settings. The importance of this latter feature must be stressed, given that harmonizing data generated for the detection of recently acquired HIV infections in different European countries represents a priority for the control of HIV spread within and across Europe. This method is automated, easy to perform, practical, inexpensive, and reproducible in various settings. It provides a quantitative result (AI) with different levels of sensitivity and specificity depending on the selected cut-off. Moreover, the assay is an automated enzyme immunoassay that is commonly used in many countries, thus allowing results from different geographic areas to be compared. 12 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

13 Procedures Respondent-driven Sampling (RDS) method Serum samples for AI measurement were collected in the four cities that used the RDS method (i.e., Bratislava, Bucharest, Verona, and Vilnius). RDS method has been developed specifically for hard-to-reach populations and MSM in particular, where probabilistic sampling methods cannot be adopted. This specific approach was used in previous studies (18-22) targeting different sub-groups or populations (e.g.: MSM, sexual workers, IDUs) and has proven to be a good and reliable (even still experimental) method for gathering both behavioral and biological data in hidden or hard to reach populations. RDS methodology is based on long-chain recruitment whereby members of the target population participating in the study refer other members of the target population to the study. RDS allows researchers to recruit highly stigmatized groups who do not congregate in well-known places. Based on pre-existing contact with the study group, researchers recruited a handful of participants who served as the seeds (initial study participants) from the target population (6-12 people). RDS combines snowball sampling with a mathematical model that weights the sample to compensate for the fact that the sample is collected in a non-random way (23). RDS does not only provide a probabilistic method to reach the desired sample size, but also allows the research group to identify networks and the characteristics of those belonging to the networks. In the SIALON II project, respondents received an economic incentive for providing blood and for filling in the questionnaire. Sample collection For each participant, data on prevention needs, sexual behaviour, service access and ecological aspects of the environment were collected through an anonymous questionnaire and linked to the serum sample. Respondents made an appointment in a health facility where a blood sample was taken for serological testing (syphilis, HBV, HCV) and validation of rapid tests (for HIV and syphilis) according to a testing algorithm agreed with WHO (see Annex). This serum sample was used also to measure the AI. Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 13

14 AI lab procedure Serum samples collected from individuals with a Western Blot-confirmed HIV-positive test were shipped from the participating cities to the Microbiology and Virology reference laboratory located in the Spedali Civili in Brescia. Serum samples were stored in the same refrigerator at -20 C until testing. Each sample was thawed, and two aliquots of 50 µl each were subjected to a pre analytic dilution. One aliquot was diluted 1:10 with the dilution buffer included in the assay (phosphate buffered saline solution) (aliquot B), and the other aliquot was diluted 1:10 with a 1 M solution of guanidine hydrochloride (8 Molar Guanidine HCL Pierce Industries, NY, USA) (aliquot G). After incubation at room temperature for 20 min, the aliquots were assayed by the automated Architect HIV Ag/Ab Combo (Abbott Diagnostics, Wiesbaden, Germany) since assay is fully automated, only the sample preparation step was modified with the pre analytic dilution, whereas the subsequent steps were not altered. After obtaining the sample/cutoff (S/CO) value for aliquots B and G, the AI of the HIV antibodies was calculated using the following formula: AI =(S/COaliquot G)/(S/COaliquot B). Based on previous reports, serum samples with an AI 0.80 were classified as recent infections and those with an AI > 0.80 were classified as established infections. (9-11). AI procedure is described in detail in the attached Protocol. A training course on avidity index principles and testing procedure for laboratory personnel and infectious disease specialists was carried out in Verona in 2013 (see attached CD). Serum sample collection In the RDS arm, 96 individuals tested HIV-positive: 20 in Bratislava, 36 in Bucharest, 32 in Verona, and 8 in Vilnius. Unfortunately, the eight samples collected in Vilnius could not be used. These samples were regularly labelled and stored at the end of December 2014 by the Lithuanian Subcontractor that performed laboratory testing. When the Lithuanian Airfreight Operations company - that was responsible for sample shipping from Vilnius to Verona - contacted the Lithuanian Subcontractor on , the Subcontractor informed that 5 out of 8 samples were thawed because of an electric power outage during a storm and that it would be inappropriate to refrigerate them again. The Vilnius partner knew of this loss when they contacted the Lithuanian Airfreight Operations company for sample shipping at the end of January 2015 and then informed the project coordinator. Subsequently, the project coordinator decided that the cost for shipping the remaining three frozen serum samples would be too high and therefore this shipment was cancelled. In Bucharest, seven samples were not analysed for AI for the following reasons: three samples were lost, three samples were mislabelled, and one sample was not suitable for AI testing because of hemolysis of the whole-blood specimen. The remaining 81 samples from Bratislava, Bucharest and Verona were tested for AI. 14 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

15 Results AI results The AI was performed in 81 serum samples from 81 individuals with a positive HIV test confirmed with Western Blot. The median age of HIV positive individuals was 40 years (interquartile range ) in Verona, 29.5 years (IQR 26-35) in Bratislava, and 29 years (IQR 25-35) in Bucharest. Overall, 64.9% used drugs during last sexual intercourse, 40.0% used drugs but not alcohol, and 16.2% used a party drug. Ten samples out of 81 were classified as recent (acquired in the 6 months before blood drawing) HIV infection; the remaining 71 samples were classified as established (acquired more than 6 months before blood drawing) infection. The highest proportion (20%) of recent infections was observed in Bratislava, whereas the proportion was lower and similar in Bucharest and Verona (approximately 10%). Table 1 Number and percentage of recent and established infections according to AI among HIV-positive individuals, by city. City N. of individuals with Recent infection (%) N. of individuals with Established infection (%) Denominator (N. of HIV-positive individuals) Bratislava 4 (20.0%) 16 (80.0%) 20 Bucharest 3 (10.3%) 26 (89.7%) 29 Verona 3 (9.4%) 29 (90.6%) 32 Vilnius In Bucharest, information on age was available for 28 individuals. When stratifying by age group (<25 years vs. 25+ years), the small number of recent infections in the strata hampered any substantial comment. However, Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 15

16 if interpreted with the appropriate caution, available data show that the proportion of recent infections was higher among individuals younger than 25 years whereas more than 80% of older individuals had established infections. Table 2 Number and percentage of recent and established infections according to AI among HIV-positive individuals, by city and age. City Age N. of individuals with Recent infection (%) N. of individuals with Established infection (%) Denominator (N. of HIVpositive individuals) <25 1 (66.7%) 2 (33.3%) 3 Bratislava (17.6%) 14 (82.7%) 17 <25 0 (0.0%) 6 (100.0%) 6 Bucharest (13.6%) 19 (86.4%) 22 <25 1 (33.3%) 2 (66.7%) 3 Verona (6.9%) 27 (93.1%) 29 < VILNIUS The proportion of new HIV diagnoses was higher in Bratislava (45%) compared to Bucharest and Verona (25%), reflecting the distribution of new HIV diagnoses among MSM reported by the ECDC that shows higher rates in Slovakia compared to Romania and Italy (ref). The SIALON II questionnaire investigated the knowledge of one s HIV serostatus and this information was crosschecked with recency of infection based on the AI results. Table 3 Percentage of recent and established infections according to AI among HIV-positive individuals, by city and HIV status knowledge. City HIV status knowledge Recent infection (%) Established infection (%) Denominator (N. of HIV positive individuals) Known HIV-positive V positive 0 (0.0%) 4 (100.0%) 4 Bratislava Newly diagnosed HIV-positive 2 (22.2%) 7 (77.8%) 9 Indeterminate knowledge HIV positive 2 (28.6%) 5 (71.4%) 7 16 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

17 Known HIV-positive V positive 1 (9.1%) 10 (90.9%) 11 Bucharest Newly diagnosed HIV-positive 1 (14.3%) 6 (85.7%) 7 Indeterminate knowledge HIV positive 1 (9.1%) 10 (90.9%) 11 Known HIV-positive V positive 2 (10.0%) 18 (80.0%) 20 Verona Newly diagnosed HIV-positive 1 (12.5%) 7 (87.5%) 8 Indeterminate knowledge HIV positive 0 (0.0%) 4 (100.0%) 4 Known HIV-positive VILNIUS Newly diagnosed HIV-positive Indeterminate knowledge HIV positive Overall, 42.5% (34/80) and 57.5% (46/80) of HIV-positive participants reported being aware and unaware/ indeterminate knowledge, respectively, of being HIV-positive before SIALON II testing. Among the 46 participants who were newly diagnosed with HIV or reported an indeterminate knowledge of HIV serostatus, 84% (39/46) had an established infection according to the AI result. This finding indicates that that a large proportion of participants unaware of being infected were infected since a long time. The small number of known HIV-positive individuals with a low AI classified as having a recent infection (1 in Bucharest and 2 in Verona) seems conflicting: this misclassification of the AI is to be associated most probably with antiretroviral treatment, which is known to lower the AI in a proportion of cases (24). Results of the post-test counselling Besides the information collected with the SIALON II self-administered questionnaire, additional individual information was collected in the post-test counselling among the 96 participants who were found to be HIVpositive in the RDS arm. Information collected in the post-test counselling included HIV status knowledge and HIV testing before participation in SIALON II. Answer to the question Were you aware of your HIV serostatus? was available for 90 out of 96 participants. A proportion of individuals unaware of being HIV-positive higher than 50% was observed in Bratislava and Vilnius, whereas a lower proportion was observed in Bucharest and Verona. Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 17

18 Table 4 Distribution of HIV-positive individuals by HIV status knowledge declared in the post-test counselling, by city City N. of individuals unaware of their HIV status (%) N. of individuals aware of their HIV status (%) Denominator (N. of HIV-positive individuals) Bratislava 14 (70.0%) 6 (30.0%) 20 Bucharest 17 (56.7%) 13 (43.3%) 30 Verona 13 (40.6%) 19 (59.4%) 32 VILNIUS 6 (75.0%) 2 (25.0%) 8 Table 5 Distribution of HIV-positive individuals unaware of their HIV serostatus in the post-test counselling, by history of previous HIV testing and city City N. of individuals never tested for HIV (%) N. of individuals previously tested for HIV (%) Denominator (N. of HIV-positive individuals unaware) Bratislava 6 (42.9%) 8 (57.1%) 14 Bucharest 7 (41.2%) 10 (58.8%) 17 Verona 3 (23.1%) 10 (76.9%) 13 VILNIUS 1 (16.7%) 5 (83.3%) 6 Answer to the question Have you ever been tested for HIV? was available for 93 out of 96 participants. Among the 50 participants unaware of being HIV-positive, more than half reported having been tested previously for HIV, ranging from a minimum in Bratislava (57.1%) to a maximum in Vilnius (83.3%). The proportion of those never been tested for HIV was higher in Bratislava and Bucharest. Table 6 Distribution of HIV-positive individuals unaware of their HIV serostatus in the post-test counselling, by recency of infection according to AI and city City N. of established infection (%) N. of recent infection (%) Denominator (N. of HIV-positive individuals unaware) Bratislava 11 (78.6%) 3 (21.4%) 14 Bucharest 10 (76.9%) 3 (23.1%) 13* Verona 12 (92.3%) 1 (7.7%) 13 VILNIUS *13 out of 17 samples were tested for AI because 3 samples were mislabelled, and one sample was not suitable for AI testing because of hemolysis of the whole-blood specimen 18 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

19 Among individuals who declared being unaware of their HIV-positivity in the post-test counselling, the finding of a high (more than 75%) proportion of individuals with an established infection confirms the results presented in Table 3. In fact, in the self-administered questionnaire, 84% of participants unaware of being HIV positive (i.e., newly diagnosed with HIV or reported an indeterminate knowledge of HIV serostatus) had an established infection. Table 7 Information collected in the post-test counselling among HIV-positive individuals City Proportion of unaware among HIV- positive individuals Proportion of never tested for HIV among unaware Proportion of established infection among unaware Bratislava 70.0% 42.9% 78.6% Bucharest 56.7% 41.2% 76.9% Verona 40.6% 23.1% 92.3% VILNIUS 75.0% 16.7% - In summary, the post-test counselling conducted among HIV-positive individuals showed a high proportion of participants unaware of being infected. Among these, a relevant percentage of individuals never underwent HIV testing previously and more than ¾ had an established infection. Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 19

20 Conclusions These results showed several advantages of the AI. On a methodological level, the procedure is inexpensive and quite simple to perform, and since the automated EIA is routinely used for HIV-antibody detection in all European countries and in many non-european countries, it is readily available. The fact that the assay is automated guarantees a better reproducibility of the results, greatly reducing intra-lot variation and minimising inter-laboratory variation, which is essential for comparing or pooling the results obtained in different laboratories. The AI is a quantitative and not a qualitative variable, thus providing more information on the antibody response and, depending on the purpose, allowing for the definition of different cut-offs which may improve either the sensibility or the specificity of the test. For the SIALON II project, a cutoff of 0.80 was used to discriminate recent from established infections, which is useful for epidemiological purposes providing the best accuracy in terms of sensitivity and specificity. On a clinical level, AI allows to identify persons at an early stage of infection who would mostly benefit from early treatment. On a prevention level, AI gives support for an appropriate contact tracing and partner notification avoiding the risk of attributing to a recent partner the source of an established infection; moreover, AI is used in the evaluation of prevention programmes focused on the reduction of HIV transmission by monitoring the proportion of recent HIV infections. In SIALON II, AI allowed to comparing the proportion of recent HIV infections across countries. The highest proportion of both new diagnoses and recent infections was observed in Bratislava, reflecting the high rate of new HIV infections among MSM also reported by the ECDC in Slovakia (25). Based on the results of the AI, more than three-fourth of HIV-positive participants with a new HIV diagnosis or an indeterminate knowledge of HIV serostatus had an established infection, accounting for a longer time being unaware of being infected compared to those with a recent infection. This relevant proportion of individuals with an established infection and unaware of being HIV positive was confirmed also in the posttest counselling, where a more in-depth history was collected from HIV-positive participants. In the post-test counselling, more than half of those unaware of being infected reported having been tested for HIV previously: nevertheless, the timing of HIV testing probably was not appropriate or frequent enough to detect early HIV infection. These findings suggest that MSM, despite being informed about behaviours at risk for HIV and other 20 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

21 sexually transmitted infections, are not so keen to undergo periodical HIV testing even when exposing to behaviours at risk. In this study, a limitation to the interpretation of the results of the AI is the lack of individual information on antiretroviral treatment, which has been shown to affect the AI increasing the proportion of false recent infections. In fact, the finding of a small number of known HIV-positive individuals with a low AI - therefore classified as having a recent infection - is expected and must be interpreted as a misclassification of the AI in individuals most probably under antiretroviral treatment. In conclusion, the AI in the context of the SIALON II study provided a number of findings, which are crucial for better understanding the HIV epidemic among MSM in Europe and planning focussed prevention campaigns. Specifically: The proportion of HIV-positive participants infected in the previous 6 months ranged between 10% and 20%, depending on the city; the remaining proportion of HIV-positive individuals acquired the infection years before; HIV is still actively circulating among young (<25 years) MSM; More than half of HIV-positive participants were unaware of being infected before being tested in SIALON II, and among these 8 out of 10 had a long-term infection Even when undergoing HIV testing, the frequency or timing of testing is not appropriate to early detect HIV infection among MSM. These findings suggest that a more active information campaign should be conducted among MSM, covering various aspects, such as: at-risk behaviours (from unprotected sexual intercourse to use of party drugs), use of condom irrespectively of antiretroviral treatment or partner s serostatus, and routine testing for HIV and other sexually transmitted infections. Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 21

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24 21. Johnston LG, Sabin K, Prybylski. Update for sampling most-at-risk and hidden populations for HIV biological and behavioral surveillance. Journal of HIV/AIDS Surveillance & Epidemiology Johnston LG, Sabin K. (2010). Sampling hard-to-reach populations with respondent driven sampling. Methodological Innovations Online (2010) 5(2) Kendall C, Kerr L, Gondim CC, Werneck GL, Macena R, Pontes M, Johnston LG, Sabin K, McFarland, W. An empirical comparison of respondent-driven sampling, time location sampling, and snowball sampling for behavioral surveillance in men who have sex with men, Fortaleza, Brazil AIDS and Behavior. 12(Suppl 1): References 24. Keating SM1, Hanson D, Lebedeva M, Laeyendecker O, Ali- Napo NL, Owen SM, Stramer SL, Moore RD, Norris PJ, Busch MP. Lower-sensitivity and avidity modifications of the vitros anti-hiv 1+2 assay for detection of recent HIV infections and incidence estimation. J Clin Microbiol Dec;50(12): European Centre for Disease Prevention and Control/ WHO Regional Office for Europe. HIV/AIDS surveillance in Europe Stockholm: European Centre for Disease Prevention and Control; available in europa.eu/en/publications/_layouts/forms/publication_ DispForm.aspx?List=4f55ad51-4aed-4d32-b960- af70113dbb90&id=1217

25 Annex Protocol for the Avidity Index (AI) measurement using the Architect HIV Ag/Ab Combo With regards to the Avidity Index, only serum samples obtained from individuals positive (and confirmed with WB) for HIV antibodies can be assayed for the AI. The AI is automated, easy to perform, practical, inexpensive, and reproducible in various settings. Prerequisite: Only serum samples obtained from individuals positive (and confirmed with WB) for HIV antibodies can be assayed for the AI. Phase 1 - Serum collection and storage 100 µl of serum will be collected for every individual and will be stored at 20 C until processing. Phase 2 - AI testing procedure Guanidine: use 8M Guanidine-HCl solution Pierce (product number 24115) or Amresco (code M113-4L) to be diluted (1:8) when needed, using 10 ml of guanidine and 70 ml of distilled water. PBS: use the Concentrated Wash Buffer, that is a PBS (4 x 1L, code 6C5458 or 10L, code 6C5488) provided by the Architect kit as consumable. This buffer comes in packages of 4 x 1L or 10L, therefore there is no need to order additional buffer. The wash buffer is provided at a 1.5M concentration and must be diluted to 0.15M for use in routine testing: therefore, a 1 in 10 dilution with distilled water (1L concentrated tampon 1.5M + 9L distilled H2O) will be performed before running the assay. Each sample will be thawed and two aliquots of 50 µl each will be subjected to a pre-analytic dilution as Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 25

26 follows: one aliquot will be diluted 1 in 10 with guanidine hydrochloride (G), using 50 µl of serum µl of G. one aliquot will be diluted 1 in 10 with phosphate buffered saline (PBS), using 50 µl of serum µl of PBS. vortex and incubate at room temperature for 5-10 minutes. place prepared sample cups into an Architect sample carrier. Aliquots will then be assayed by the automated Architect HIV Ag/Ab Combo (Abbott Diagnostics, Wiesbaden, Germany) without modifying the protocol recommended by the manufacturer. for each aliquot a S/CO value will be obtained: one for the G aliquot and the other for the PBS aliquot. If the volume of serum available is less than 100 µl, the pre-test dilution can be performed using 20 µl of serum µl of G, and 20 µl of serum µl of PBS. The same procedure can be applied when using AxSYM HIV 1/2gO. Control preparation Procedural controls: Add at least 5 drops each of the controls included in the kit to separate sample cups, according to the Architect work list. The Positive and Negative Controls must be within the ranges specified in the package insert. IQC: Prepare a low avidity (AI: ) and a high avidity (AI: ) control by pooling appropriate serum or plasma specimens. Prepare 10 aliquots of 500 µl each of each control and store them at -20 C or colder. The day before running the assay, thaw one aliquot of each control by bringing the tube to +4 C, mix accurately and run each control level in singlicate in every run. Calculate the AI for each control and report the values in appropriate Quality Control charts in order to evaluate values shifts over time according to the Westgard rules and take appropriate corrective actions if necessary. Phase 3 - AI calculation The AI of HIV antibodies will be calculated by dividing the S/CO* G aliquot by the S/CO* PBS aliquot as follows: S/CO* G aliquot AI = S/CO* PBS aliquot * Sample/Cut-off The AI can be calculated only if at least one of the two aliquots has a value greater than the assay cutoff. Based on previous results, we define a recent infection ( 6 months from seroconversion) when AI 0.80, and an established infection (>6 months from seroconversion) when AI>0.80. Precision studies performed according to a CLSI protocol, using AxSYM HIV 1/2gO, AxSYM HIV Ag/Ab Combo, and Architect HIV Ag/Ab Combo showed an imprecision of the AI always lower than 10%. 26 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

27 Appropriateness of testing for the AI when using the Architect HIV Ag/Ab Combo: The possible scenarios of Ag-Ab results Results of the tests Scenario Architect Combo p24/ HIV-RNA 3 rd gen EIA WB Can we test for the AI? Scenario NO Scenario NO Scenario YES Scenario YES Scenario or + - or + - or indeterminate NO Results of the G and PBS aliquots and interpretation of the AI In terms of results and interpretation of the AI, the following items will be taken into account: G S/CO 3.57; PBS S/CO 8.44; AI 3.57/8.44 = 0.43 (recent infection) G S/CO 12.22; PBS S/CO 13.08; AI 12.22/13.08 = 0.93 (established infection) G S/CO 0.33; PBS S/CO 0.57; AI not calculable. The cut-off of the Architect assay is 1. The signal obtained in both aliquots is lower than the CO of the assay; therefore, the result is negative in both aliquots. G S/CO 0.87; PBS S/CO 1.78; AI 0.77/1.78 = 0.43 (recent infection). The G aliquot shows a signal lower than the CO of the assay but the PBS aliquot shows a signal greater than the CO of the assay; therefore, the result is acceptable. G S/CO 23.44; PBS S/CO 21.97; AI 23.44/21.97 = 1.10 (established infection). The AI value looks awkward being greater than 1. However, this may occur in case of an old infection with high antibody values; moreover, the 10% imprecision of the method can contribute to this result. G S/CO 15.71; PBS S/CO 19.67; AI 15.71/19.67 = The AI suggests a recent infection; however, due to the above-mentioned 10% imprecision of the method, the results around the threshold ( ) should be considered as laying in a grey zone. Retesting the sample and calculating the average of the results obtained can be an option Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 27

28 Testing for the AI: Algorithm using Architect HIV Ag/Ab Combo Serum sample tested with Architect HIV Ag/Ab Combo Serum sample tested with Architect HIV Ag/Ab Combo Negative Positive 3rd gen EIA Negative Ag+ Positive Ab+ Test p24 or HIV-RNA WB Positive (early infection) Positive Negative or indeterminate Repeat blood test after 7 days AVIDITY INDEX using Architect Ag/Ab Combo Repeat blood test after 7 days AI 0.80 AI > 0.80 Recent infection Established infection 28 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM

29 HIV flowchart in RDS method Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM 29

30 Capacity building in combining targeted prevention with meaningful HIV surveillance among MSM Recent HIV Infections among MSM in Sialon II Results from the Avidity Index Component of the Sialon II RDS survey Co-funded by the Health Programme of the European Union This document is based on data from the Sialon II project, funded under the European Commission s (EC) Public Health Programme (Work Plan 2010). The sole responsibility lies with the authors of this report and the Commission is not responsible for any use that may be made of the information contained therein.