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AIDS:
doi: 10.1097/QAD.0b013e3283471cce
Epidemiology and Social

The hepatitis C epidemic among HIV-positive MSM: incidence estimates from 1990 to 2007

van der Helm, Jannie Ja; Prins, Mariaa,b; del Amo, Juliac; Bucher, Heiner Cd; Chêne, Genevièvee; Dorrucci, Mariaf; Gill, Johng; Hamouda, Osamahh; Sannes, Mettei; Porter, Kholoudj; Geskus, Ronald Ba,k; on behalf of the CASCADE Collaboration

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Author Information

aCluster of Infectious Diseases, Public Health Service Amsterdam

bDepartment of Internal Medicine, Center for Immunity and Infection Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

cInstituto de Salud Carlos III, Madrid, Spain

dBasel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland

eINSERM U897, University Victor Ségalen, Bordeaux, France

fIstituto Superiore di Sanitá, Rome, Italy

gDepartment of Medicine, University of Calgary, Calgary, Alberta, Canada

hRobert Koch Institute, Berlin, Germany

iUlleval University Hospital, Oslo, Norway

jMRC Clinical Trials Unit, London, UK

kDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

Received 9 November, 2010

Revised 23 February, 2011

Accepted 24 March, 2011

Correspondence to Jannie J. van der Helm, Cluster of Infectious Diseases, Public Health Service Amsterdam, Nieuwe Achtergracht 100, 1018 WT Amsterdam, The Netherlands. Tel: +31 20 5555061; fax: +31 20 5555533; e-mail: jvdhelm@ggd.amsterdam.nl

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Abstract

Background: Outbreaks of acute hepatitis C virus (HCV) infection among HIV-infected MSM have been described since 2000. However, phylogenetic analysis suggests that the spread of HCV started around 1996. We estimated the incidence of HCV in HIV-infected MSM with well estimated dates of HIV seroconversion from 1990 to 2007.

Methods: Data from 12 cohorts within the Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE) Collaboration were used. HCV incidence was estimated using standard incidence methods and methods for interval-censored data. We accounted for the fact that routine HCV data collection in each cohort started in different calendar years.

Results: Of 4724 MSM, 3014 had an HCV test result and were included. Of these, 124 (4%) had only positive HCV test results, 2798 (93%) had only negative results and 92 (3%) had both. In 1990, HCV incidence ranged from 0.9 to 2.2 per 1000 person-years, depending on the analysis strategy used. HCV incidence increased up to 1995 when it was estimated to range between 5.5 and 8.1 per 1000 person-years. From 2002 onwards, it increased substantially to values between 16.8 and 30.0 per 1000 person-years in 2005 and between 23.4 and 51.1 per 1000 person-years in 2007.

Conclusion: Our data support phylodynamic findings that HCV incidence had already increased among HIV-infected MSM from the mid-1990s. However, the main expansion of the HCV epidemic started after 2002. Incidence estimates obtained from cohort studies may help identify changes in the spread of important infections earlier and should guide routine testing policies to minimize further disease burden.

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Introduction

Hepatitis C virus (HCV) infection is a major public health problem for HIV-infected individuals. HCV is primarily a blood-borne infection and is common in individuals who frequently received blood and blood products before 1991, as well as in IDU [1,2]. On the basis of studies in HCV-discordant heterosexual couples, sexual transmission of HCV was considered to be inefficient and was rarely reported, even in the presence of HIV co-infection [3,4]. Since 2000, however, outbreaks of sexually acquired HCV infection among HIV-infected men who have sex with men (MSM) have been described in several high-income countries, suggesting that the epidemiology of HCV infection is changing [5–10].

Recent phylogenetic analysis, using data from five countries, revealed the presence of international sexual HCV transmission networks among MSM. Interestingly, using a molecular clock analysis, the study also indicated that the spread started earlier than 2000, namely around 1996 [11]. The 4-year time lag in the detection of these HCV outbreaks may have been due to the fact that routine testing for HCV infection started mainly after the first acute cases of sexually acquired HCV infection in MSM were reported. Furthermore, because HCV testing was not implemented before 1991, as HCV test kits were not commercially available then, HCV incidence before that date could only be studied through retrospective testing in cohorts for whom stored blood samples were available.

Only a few longitudinal studies with data before and after 2000 have evaluated time trends in HCV incidence among MSM, but all are from single countries [12–14]. These studies used data from initially HCV-negative individuals with repeated tests to estimate incidence and, consequently, these estimates were based on very few HCV seroconverters (n = 26, 4 and 8, respectively). Using data from 12 large cohorts, we estimated the incidence and the timing of the spread of HCV in HIV-infected MSM with documented dates of HIV seroconversion over the last two decades. We used a standard incidence estimation method as well as a method that allowed us to also use data from HCV-infected individuals without previous HCV-negative test results.

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Methods

Study populations

Data from Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE), a collaboration of 25 HIV seroconverter cohort studies in Europe, Australia, Canada and sub-Saharan Africa were used for this analysis. Details of CASCADE have been described elsewhere; in short, all cohorts included HIV-infected persons for whom a date of HIV seroconversion could be estimated reliably [15]. Analyses were restricted to MSM, who are assumed to have become HIV-infected sexually, from 11 cohorts in eight European countries and one in Canada that collected information on HCV. HCV positivity was defined as detection of anti-HCV antibodies and/or HCV-RNA according to individual laboratory procedures. Each cohort provided information about the start date of routine HCV data testing and collection in their respective country/cohort. Routine HCV data collection is defined by testing all individuals for HCV according to the prevailing guidelines so that testing is irrespective of HCV status.

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Statistical analyses

Two of the 12 cohorts provided HCV test results for all participants from the start of these cohorts. For the other 10 cohorts, the start of routine HCV testing was later than the start of the cohort [which differed by cohort, earliest January 1991 (Table 1)]. HCV incidence was estimated using three methods. We used two variations of standard incidence estimation techniques. A third method was based on a nonparametric estimation method for interval-censored data.

Table 1
Table 1
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Standard estimation of hepatitis C virus incidence

HCV incidence per year was calculated as the number of HCV seroconversions divided by total person-years under observation for all MSM at risk, with HCV seroconversion date defined as the midpoint between the last HCV-negative and first HCV-positive test dates. We consider individuals to be at risk from the latest date of routine HCV testing, HIV seroconversion or cohort entry. Standard application of this method is hampered by the fact that the first information with respect to HCV status may have been obtained after the date that an individual became at risk (e.g. at risk in 1999, first HCV test result in 2000). Individuals with only HCV-positive test results after becoming at risk were excluded, although their HCV infection may have occurred while they were at risk. Hence, this is likely to give an underestimation of HCV incidence. To correct for these excluded individuals, an alternative approach was used as well. In this approach, only data from initially HCV-negative MSM with at least two HCV test results were included, and they were only considered at risk from the latest date of first HCV-negative test after routine HCV data collection, HIV seroconversion or cohort entry. However, this approach is only valid if the reason to test is independent of HCV status. As an HCV-negative test result may make it less likely to perform HCV tests earlier in time, this assumption may be violated, which can result in an overestimation of HCV incidence. Incidence rate curves were modeled using Poisson regression with calendar year as a continuous variable, allowing for smoothly varying trends via restricted cubic splines [16].

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Estimation of hepatitis C virus incidence based on interval-censored data

The information with respect to HCV seroconversion was, in fact, interval censored, that is, the moment of HCV infection was not known exactly. We calculated the nonparametric maximum likelihood estimate for the cumulative HCV incidence [17] based on the interval-censored HCV status information. For individuals who remained HCV negative during follow-up, the date of last HCV-negative test was used; for individuals for whom only HCV-positive test results were available, the date of first HCV-positive test was used; and for individuals who seroconverted to HCV during follow-up, the dates of the last negative HCV test and the date of the first positive HCV test were used. Cumulative HCV incidence was estimated from 1990 until May 2007. Most individuals, however, were not in follow-up and at risk from the beginning of this period as they either seroconverted for HIV after 1990 or were enrolled into the cohort after 1990 or because routine HCV testing had begun at a later date. As the current version of the statistical program used has no option to correct for such left-truncated data, we performed separate analyses for the calendar periods 1990–1994, 1995–1999 and 2000–2007, only including persons who were at risk and in follow-up in at least part of each period.

For individuals who only had test information available before the date of becoming at risk, data handling can be done in different ways (see below).

Inclusion strategy for interval-censored data method:

For individuals with HCV test information available before they became at risk and without test results after that date, we employed four strategies. Individuals testing HCV positive before they became at risk and who remained in follow-up after that date were included in the risk set from the date they became at risk. For individuals testing negative before the date of routine HCV testing and without a positive test result, but with follow-up after date of routine HCV testing, two strategies were also used of excluding them (nM, ‘negative missing’) or of assuming they remained HCV negative until they became at risk and including them (nI, ‘negative include’).

For those who tested HCV positive, but with no follow-up after date of routine HCV testing, two strategies were applied of either excluding (pM, ‘positive missing’) or including them (pI, ‘positive include’). Strategy pM is based on the idea that individuals who had tested positive before they became at risk and who had no follow-up after that date would have been missed and their information would not have been included. Under this scenario, individuals who only had a negative test result and without follow-up after becoming at risk were also excluded. Strategy pI is based on the idea that individuals who tested HCV positive and died before the date of routine HCV testing do contribute to the HCV incidence. Their date of first HCV-positive test is set to the date of becoming at risk, even though they had no follow-up. When strategy pI was applied, individuals who only had a negative test result and left the study before becoming at risk were also either included or excluded.

Strategy nM overestimates HCV incidence, as individuals testing positive before the date of routine HCV testing and with follow-up after that date are included, whereas those testing negative before that date were not. On the contrary, strategy nI may underestimate HCV incidence, as some of the individuals who only had HCV-negative test results before the date of routine HCV testing may have, in fact, seroconverted between their last negative test date and that date. If the interval between those two dates is small, strategy nI is preferable to strategy nM. Hence, the four strategies used were strategy 1 (pM-nM), strategy 2 (pI-nM), strategy 3 (pM-nI) and strategy 4 (pI-nI).

In the chosen strategy 3 (pM-nI), we excluded individuals who did not have follow-up after the date of becoming at risk. For individuals who were followed after the date of routine testing and only had test results before this date, their result was set at the date of becoming at risk. This strategy might give an underestimation of the HCV incidence, as some of the individuals who only had HCV-negative test results before the date of becoming at risk may have seroconverted between their last negative test date and the date they became at risk. The precise details are described in the above section together with three other strategies of data handling for these individuals. On the basis of the estimates of the cumulative incidence, the hazard of HCV infection over calendar time was estimated using kernel smoothing methods [18].

Compared with the standard incidence estimation method, the advantage of this nonparametric method for interval-censored data is that the individuals who only had an HCV-positive test result could be included. A disadvantage is that we are not sure whether HCV infection occurred after they became at risk. Particularly, HCV infection may have occurred before HIV infection. Also, standard errors and confidence intervals (CIs) cannot be obtained.

The basic analyses were performed using SPSS version 17.0 (SPSS Inc., Chicago, Illinois, USA). R version 2.10.1 [19] was used for the standard methods to estimate HCV incidence trends, and the Icens package in R [20] was used for the estimates based on interval-censored data.

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Results

Of 4724 MSM from the 12 eligible cohorts in CASCADE, 3020 had an HCV test result available. The earliest enrolment date was July 1981 and the most recent March 2007. Most MSM were tested for HCV during prospective follow-up, that is, after HIV seroconversion and after cohort entry, but 288 only had HCV-negative test results shortly before cohort entry [median time between last testing and enrolment, 0.9 months; interquartile range (IQR), 0.3–4.4 months], 16 only had positive HCV test results before cohort entry (median time between last testing and enrolment, 0.6 months; IQR, 0.3–12.5 months) and 23 only had negative HCV test results before HIV seroconversion (median, 16.0 months; IQR, 9.5–32.1 months). Six MSM had a positive HCV test before HIV seroconversion and were, therefore, excluded from further analyses.

The median age at HIV seroconversion for the 3014 MSM included was 31.6 years (IQR, 26.5–38.1). Their median year of HIV seroconversion was 1996 (IQR, 1992–2002) and 2127 individuals initiated HIV antiretroviral therapy during follow-up. Ethnicity was known for 63%, of whom 95% were white and 2% were black. Characteristics of the MSM in three calendar periods are shown in Table 2. The median age at HIV seroconversion and the ethnicity distribution remained stable over time, although the median age at the start of each calendar period slightly increased. As expected, uptake of HIV antiretroviral therapy expanded after 1995.

Table 2
Table 2
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Hepatitis C virus test results

Of the 3014 MSM, 124 (4%) had at least one positive HCV test result and no HCV-negative results, 2798 (93%) had at least one negative result and no HCV-positive results and 92 (3%) had a negative test result followed by a positive result and, thus, had a documented HCV seroconversion (characteristics are shown in Table 3). Those who only had HCV test results before routine HCV testing began (N = 770) were treated according to the four strategies described in the ‘Inclusion strategy for interval-censored data method’ section. Of these 770 individuals, 189 were only followed before routine HCV testing began and, thus, had HCV results only before this date. Of 2825 individuals followed after routine HCV testing began, 581 only had HCV test results before this date (median time between last HCV test result and routine HCV testing was 1.1 years; IQR, 0.3–2.6). The results from strategy 3 are presented, but did not differ substantially from the other three strategies (data not shown). Among MSM who tested HCV positive, 30 (14%) had their first positive test between 1990 and 1994, 59 (27%) between 1995 and 1999 and 127 (59%) from 2000 onwards.

Table 3
Table 3
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Hepatitis C virus incidence

In the standard incidence estimation method, 1354 MSM were included and the number of person-years of follow-up for the periods 1990–1994, 1995–2000 and 2000–2007 was 645.15, 950.04, and 1779.83, respectively; after the correction for which we required at least two HCV test results, the number included decreased to 774 and the number of person-years of follow-up was 517.98, 758.23 and 1211.49, respectively. The number of MSM included in each of the three calendar periods 1990–1994, 1995–1999 and 2000–2007 when using the estimation method for interval-censored data were 904, 1646 and 2565, respectively. Figure 1 shows the HCV incidence according to the two standard approaches and according to the interval-censored method. The temporal trend in HCV incidence is comparable for the three estimates over the total study period 1990–2007. In 1990, HCV incidence was low and estimated to be 0.9 (95% CI, 0.05–15.2), 1.4 (95% CI, 0.09–20.4) and 2.2 per 1000 person-years, depending on the method used. In 1995, HCV incidence was already slightly increased and estimated to be 5.5, 5.9 (95% CI, 2.7–13.0) and 8.1 (95% CI, 3.7–19.0) per 1000 person-years, whereas in 2000, HCV incidence was estimated to be 8.0, 10.6 (95% CI, 6.0–18.8) and 13.7 (95% CI, 8.0–23.7) per 1000 person-years. HCV incidence increased substantially after 2002 and was estimated to be 16.8 (95% CI, 10.3–27.4), 21.2 and 30.0 (95% CI, 18.6–48.3) per 1000 person-years in 2005, and 23.4 (95% CI, 8.2–66.9), 41.9 and 51.1 (95% CI, 19.5–134.0) per 1000 person-years in 2007.

Fig. 1
Fig. 1
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Discussion

Since 2000, outbreaks of HCV infection have been reported in HIV-infected MSM [5–10]. We have estimated the incidence of HCV over the last two decades in a large group of HIV-infected MSM with documented dates of HIV seroconversion in Europe and Canada. Our data show that, regardless of the estimation method applied, HCV incidence had already increased in the period before 2000 and has continued to do so since. These results are in agreement with a recent phylogenetic study in which the divergence of currently circulating HCV viral strains was used to reconstruct the history of the HCV epidemic among HIV-positive MSM. Of all transmission events in that study, 15% was estimated to have occurred before 1996, 22% in the period 1996–2000 and 63% after 2000 [11]. The few longitudinal studies on the incidence of HCV in HIV-infected MSM that evaluated time trends have limited statistical power owing to the small numbers of observed HCV seroconversions or dichotomized calendar period. The HCV incidence among MSM in the French PRIMO cohort was higher after 2003, 8.3 per 1000 person-years compared with 1.2 per 1000 person-years before (study period 1996–2005) [13]. In the UK, a significantly higher HCV incidence of 4.6 per 1000 person-years was found after 2000 compared with less than 1 per 1000 person-years before (study period 1997–2002) [12], which is in line with a study from the Netherlands that found a higher HCV incidence of 8.7 per 1000 person-years after 2000 compared with 1.8 per 1000 person-years before (study period 1984–2003) [14]. The sharpest increase in HCV incidence in our study was found after 2002. The HCV incidence estimates that these studies found before 2000 are comparable with the estimates we found around 1990. In 1995, we estimated a slightly higher incidence than reported by others, ranging between 5.5 and 8.1 per 1000 person-years. The HCV incidence in HIV-negative MSM is still low, varying between 0 and 0.4 per 1000 person-years [21]. One cohort from the UK reported HCV incidence up to 5.8 per 1000 person-years [22]; however, this study had some methodological limitations, which might explain this finding. In high-income countries, HCV incidence in IDUs is still high, ranging between 1 and 25 per 100 person-years, but decreased in the last decade in some countries [8,23–25].

None of the three estimation approaches could completely capture the data structure with respect to HCV infection, but differences in outcome were small. Like the two standard incidence estimation methods in our study, the method used in the French HIV PRIMO cohort [13] and in the Amsterdam Cohort studies [14] excluded MSM who tested HCV positive at study enrolment. In the French study, 19 men were detected with anti-HCV antibodies at inclusion and were excluded, whereas only four men seroconverted for HCV during follow-up. As the excluded men might have become HCV-infected around the date of their HIV infection, only HCV incidence during established HIV infection was estimated. Although the method based on interval-censored data also had problems with respect to the definition of the risk set, we prefer the latter one because individuals only having HCV-positive test results could also be included and, therefore, it makes better use of the available data. A problem is that HCV infection may have occurred before HIV infection, but as HCV prevalence in HIV-negative MSM remains low [21], this is not very likely.

The HCV epidemic is changing and sexual transmission of HCV seems to have become more important, as the majority of the recently HCV-infected MSM denied injecting drug use. However, they more often reported specific sexual techniques, such as fisting and group sex, often in the context of recreational drug use [21]. In our study, all participants are assumed to have become HIV-infected sexually, although we cannot exclude that some HCV infections were acquired through routes other than sex, as we do not have data on HCV transmission routes in these MSM. The availability of HAART since 1996 is associated with a prolonged survival and increased sexual risk behavior in MSM [26,27]. This suggests that, with a stable or even increasing HIV incidence, the pool of HIV-infected MSM at risk of HCV infection becomes larger [21]. Within this context, both concurrent sexually transmitted infections and serosorting (i.e. choosing to have unprotected anal intercourse with sexual partners based on concordant HIV serostatus) [28,29], which is practised as a risk reduction strategy, might have contributed to the spread of HCV [30].

Although follow-up started already in 1981, we were not able to estimate HCV incidence before 1990 reliably, as only two of the 12 cohorts had retrospectively and routinely tested their participants before that date. Including nonroutinely collected data can introduce serious bias [31]. Missing data after the date at which routine HCV testing was introduced varied between 4 and 66% across cohorts in our study. This high rate is in line with findings from a recent UK study [32], concluding that it is of concern that even nowadays not all HIV-infected individuals under care are tested for HCV, despite recommendations from guidelines. This is even more important for MSM given the recent outbreak. We assumed that after the routine HCV testing date, missing data did not depend on actual HCV status, but this assumption might not hold completely. If, for example, only those with elevated alanine transaminase values were tested and, therefore, those with a higher likelihood of being HCV negative were not tested, this will result in an overestimation of HCV incidence. As it is unlikely that this testing approach changed over time, our finding that HCV incidence already increased in the period 1990–1999 remains valid.

Despite the fact that HCV therapy became generally available in 2000, earlier identification of the increasing incidence of HCV among HIV-infected MSM could have limited the further spread through raising awareness of the risk of sexually acquired HCV among MSM. Incidence estimates might help to identify changes in the spread of important co-infections earlier, and might advance the response to these changes in the epidemic. For this, observational cohort studies with sufficient power and timely supply of data are necessary. As HIV-infected individuals are increasingly more likely to die from non-HIV-related causes [33,34] and HIV accelerates HCV disease progression [35], routine screening for acute HCV as recommended by the European AIDS treatment network (NEAT) consensus conference [36] is needed to diagnose HCV infection in the early phase because current data suggest that early treatment has the greatest chance of success [37]. In addition, raising awareness is necessary to minimize further spread of HCV among HIV-infected MSM. As the HCV outbreak is not fully understood, further research on risk factors for sexually acquired HCV in MSM and the role of HIV infection itself is urgently needed for targeted prevention. Although HCV prevalence in the HIV-negative MSM population is still low [21], vigilance and surveillance is required to detect and minimize possible spillover.

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Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2011) under EuroCoord grant agreement number 260694.

G.C. had received speaker's honoraria from Boehringer-Ingelheim, fees for consultancy from Roche and a research grant from Gilead. K.P. had received speaker's honoraria from Tibotec.

The authors had full responsibility in the design of the study, collection of the data, the decision to submit the manuscript for publication and the writing of the manuscript.

CASCADE Collaboration

Steering Committee: J.D.A. (Chair), Laurence Meyer (Vice Chair), H.C.B., G.C., O.H., Deenan Pillay, M.P., Magda Rosinska, Caroline Sabin and Giota Touloumi.

Co-ordinating Centre: K.P. (Project Leader), Sara Lodi, Kate Coughlin, Sarah Walker and Abdel Babiker.

Clinical Advisory Board: H.C.B., Andrea De Luca, Martin Fisher and Roberto Muga.

Collaborators: Austria – Austrian HIV Cohort Study (Robert Zangerle); Australia – Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort (Tony Kelleher, Tim Ramacciotti, Linda Gelgor, David Cooper and Don Smith); Canada – South Alberta Clinic (J.G.); Denmark – Copenhagen HIV Seroconverter Cohort (Louise Bruun Jørgensen, Claus Nielsen and Court Pedersen); Estonia – Tartu Ülikool (Irja Lutsar); France – Aquitaine cohort (G.C., Francois Dabis, Rodolphe Thiebaut and Bernard Masquelier), French Hospital Database (Dominique Costagliola and Marguerite Guiguet), Lyon Primary Infection cohort (Philippe Vanhems), French PRIMO cohort (Marie-Laure Chaix and Jade Ghosn), SEROCO cohort (Laurence Meyer and Faroudy Boufassa); Germany – German cohort (O.H., Claudia Kücherer and Barbara Bartmeyer); Greece – Greek Haemophilia cohort (Giota Touloumi, Nikos Pantazis, Angelos Hatzakis, Dimitrios Paraskevis and Anastasia Karafoulidou); Italy – Italian Seroconversion Study (Giovanni Rezza, M.D. and Claudia Balotta), ICONA cohort (Antonella d'Arminio Monforte, Alessandro Cozzi-Lepri and Andrea De Luca); the Netherlands – Amsterdam Cohort Studies among homosexual men and drug users (M.P., R.B.G., J.J.v.d.H. and Hanneke Schuitemaker); Norway – Oslo and Ulleval Hospital cohorts (M.S., Oddbjorn Brubakk and Anne-Marte B. Kran); Poland – National Institute of Hygiene (Magdalena Rosinska); Spain – Badalona IDU hospital cohort (Roberto Muga and Jordi Tor), Barcelona IDU Cohort (Patricia G. de Olalla and Joan Cayla), Madrid cohort (J.D.A. and Jorge del Romero), Valencia IDU cohort (Santiago Pérez-Hoyos); Switzerland – Swiss HIV Cohort Study (H.C.B., Martin Rickenbach and Patrick Francioli); Ukraine – Perinatal Prevention of AIDS Initiative (Ruslan Malyuta); UK – Edinburgh Hospital cohort (Ray Brettle), Health Protection Agency (Gary Murphy), Royal Free Haemophilia Cohort (Caroline Sabin), UK Register of HIV Seroconverters (K.P., Anne Johnson, Andrew Phillips, Abdel Babiker and Valerie Delpech), University College London (Deenan Pillay), University of Oxford (Harold Jaffe).

African cohorts: Genital Shedding Study (USA – Charles Morrison, Family Health International and Robert Salata, Case Western Reserve University; Uganda – Roy Mugerwa, Makerere University; Zimbabwe – Tsungai Chipato, University of Zimbabwe); Early Infection Cohorts (Kenya, Uganda, Rwanda, Zambia, South Africa – Pauli Amornkul, International AIDS Vaccine Initiative).

Presented, in part, previously at the 46th Annual Meeting of the European Association for the Study of the Liver, Berlin, Germany on 30 March to 3 April 2011 (poster 1175); at the 17th Conference on Retroviruses and Opportunistic Infections, San Francisco, California, USA on 16–19 February 2010 (abstract 643); and at the 18th International Society for STD Research, London, UK on 28 June to 1 July 2009 (abstract P3.130).

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Keywords:

acute hepatitis C virus; co-infection; epidemiology; HIV; incidence; MSM; outbreak

© 2011 Lippincott Williams & Wilkins, Inc.

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