Abstract
Background
As trans women are disproportionately affected by the HIV epidemic, and are still understudied, we aimed to identify and characterize the trans women in the Swiss HIV Cohort Study (SHCS).
Methods
A combination of criteria from pre-existing cohort data was used to identify trans women. Information on socioeconomic factors, clinical data, risk behaviors, and mental health was collected. We also described their phylogenetic patterns within HIV transmission networks in relation to other risk groups.
Results
We identified 89 trans women of a total 20 925 cohort participants. Trans women were much more likely to be Asian (30.3%) and Hispanic (15.7%) than men who have sex with men (MSM) (2.5% and 4.1%; P < .001) and cis heterosexual (HET) women (7.0% and 3.3%; P < .001). Trans women were more similar to cis HET women in some measures like educational level (postsecondary education attainment: 22.6% and 20.7% [P = .574] vs 46.5% for MSM [P < .001]), while being more similar to MSM for measures like prior syphilis diagnosis (36.0% and 44.0% [P = .170] vs 6.7% for cis HET women [P < .001]). 11.2% of trans women have been previously hospitalized for psychological reasons compared with 4.2% of MSM (P = .004) and 5.1% of cis HET women (P = .025). Analysis of transmission clusters containing trans women suggested greater affinity within the transmission networks to MSM compared with cis HET women.
Conclusions
Trans women are epidemiologically distinct in the setting of the Swiss HIV epidemic, warranting better identification and study to better serve this underserved risk group.
Keywords: epidemiology, HIV, phylogeny, public health, trans
We identified and characterized 89 trans women from the Swiss HIV Cohort Study. In terms of sociological and clinical data, and high-risk behaviors, they are epidemiologically distinct from cis heterosexual women and men who have sex with men, and are found in various transmission contexts.
“Trans” is an umbrella term referring to individuals who do not identify as their sex assigned at birth, in contrast to “cis” people. This includes individuals who underwent solely gender-affirming medical interventions, including surgery and/or hormone therapy; those who have solely transitioned to live as another gender (socially and/or legally); and individuals who did both. Some trans people identify as being male or female (binary trans persons), while others do not identify with these gender categories (nonbinary trans persons).
Several studies have observed a lower quality of life, higher unemployment, and worse mental well-being among trans people compared with cis people [1]. In Switzerland, Jellestad et al [2] found a lower quality of life for trans men, trans women, and nonbinary people when compared with the general Swiss population. While Switzerland is relatively progressive in lesbian, gay, bisexual, and transgender (LGBT) rights, progress in trans rights has been lagging—in 2020, the Swiss parliament finally passed a law to simplify the process for trans people to obtain legal documents to reflect their self-identified gender [3–5].
While such social and legal barriers have contributed to worse social and mental (and physical) well-being, trans women are also disproportionately affected by the human immunodeficiency virus (HIV) epidemic [6, 7]. Baral et al’s [8] meta-analysis found a pooled HIV prevalence of 19.1% in trans women, with a higher prevalence of 21.6% when restricted to high-income countries. Establishing these figures is complicated due to the difficulty of identifying trans women, even within pre-established cohorts of people living with HIV (PLHIV). Until recently, HIV cohort data often only had data on binary gender, without distinguishing sex assigned at birth, legal, or self-identified gender [9]. The HIV Cohorts Data Exchange Protocol (HICDEP), a protocol for streamlined data exchange among European HIV cohort studies, only started distinguishing sex assigned at birth and gender identity in the 2019 version [10]. It is thus critical to identify trans women to understand HIV transmission patterns to help reduce transmission events. Moreover, it is important to identify sexual partners of trans women as they were shown to share some characteristics associated with groups of individuals with high HIV prevalence, particularly men who have sex with men (MSM) (Figure 1) [11].
Figure 1.
Overview of risk group characteristics comparing trans women with MSM and cis HET women. The bar chart shows an overview of key characteristics, comparing trans women with MSM and cis HET women, with asterisks denoting where proportions significantly differ. Abbreviations: ART, antiretroviral therapy; HET, heterosexual; HIV, human immunodeficiency virus; MSM, men who have sex with men; Occ, occasional; Psych, psychiatric.
Our study’s primary aim was to identify trans women in the Swiss HIV Cohort Study (SHCS) using a variety of sources. Moreover, we aimed to better understand HIV transmission events, including in trans women. We also aimed to compare demographic, clinical, mental, and social well-being factors between trans women and MSM and cis heterosexual (HET) women in the SHCS, to improve our understanding of trans women as an epidemiologically distinct high-risk group.
METHODS
The Swiss HIV Cohort Study
The SHCS is a prospective multicenter study with continuing enrollment, which aims to include all PLHIV in Switzerland since 1988. Approximately half of all adult PLHIV reported to the Swiss health authorities are in the SHCS, as well as three-quarters of those receiving HIV antiretroviral treatment in the country [12]. As of August 2019, the SHCS has a cumulative total of 20 925 patients. Demographic information, mode of HIV transmission, treatment, clinical, mental health–related, social, behavioral, and other data are collected every 6 months per standard protocol. Questionnaires are used to collect nonclinical data in study staff interviews with the patients [13]. Additionally, resistance testing is systematically performed to detect any drug-resistance mutations that may affect treatment efficacy, thus providing partial pol viral sequences, enabling construction of a transmission phylogeny and subsequent phylogenetic analyses. Retrospective sequencing from biobank samples on such a large scale has been conducted in the past [14].
Ethics
The SHCS was approved by the participating institutions’ ethics committees (Kantonale Ethikkommission Bern, Ethikkommission des Kantons St Gallen, Comité Départemental d’Éthique des Spécialités Médicales et de Médecine Communautaire et de Premier Recours, Kantonale Ethikkommission Zurich, Repubblica e Cantone Ticino–Comitato Etico Cantonale, Commission Cantonale d’Éthique de la Recherche sur l’Être Humain, Ethikkommission beider Basel; all approvals are available at http://www.shcs.ch/206-%0Dethic-committee-approval-and-informed-consent). Written informed consent was obtained from all participants [12].
Identification of Trans Women in the Swiss HIV Cohort Study
As specific information on gender identity and sex assigned at birth had not been collected on newly registered patients in the SHCS until January 2020, trans women in this study were indirectly identified from other data available, as follows:
Patient Information Comments: In the sub-database on basic patient information, free-form comments written by the study physicians were scanned (through text search in the database) for any reference to being a trans woman or gender affirmation surgery.
Female “MSM”: Individuals identified by the basic patient information as being of the female sex but also listed as being “MSM” as the likely mode of transmission were identified as trans women.
Comments in Gynecological Data: In the sub-database on gynecological information, free-form comments by the studied physicians were scanned for any reference to being a trans woman.
Prescribed Hormones: The prescribed drug sub-database was screened for female hormone entries (ATC code G03-A, C, D, F; ie, hormonal contraceptives for systemic use, estrogen, and progesterone) taken by “male”/“MSM” patients, with the exception of the contraceptive implant etonogestrel (ATC code G03AC08), which was excluded from consideration. Self-identified women taking the androgen-blocker cyproterone acetate (“Androcur” [Bayer]; ATC code G03HA01) not indicated to be trans women by any other criterion above were selected for specific inquiry into the medical records by the medical study staff at their corresponding study center. Although there are other hormone-related medications used by trans women beyond those listed above, they are not as widely used and their broad usage outside of trans medicine made it unfeasible for their additional inclusion for this criterion.
To account for the effect of the use of these indicators in identifying trans women, we performed a sensitivity analysis, where trans women solely identified by criteria 2 or 4 above are excluded, while still including women who meet both criteria 2 and 4 in the total trans women population, to examine if this affects the overall characteristics among trans women.
Statistical Analyses
Data on the identified trans women’s demographic, socioeconomic, behavioral, mental health–related, and clinical traits were described and compared with MSM and cis HET women to analyze for any statistically significant contrasts (chi-square test, Fisher’s exact test, Kruskal-Wallis test). R version 3.6.1 was used (R Foundation for Statistical Computing).
Phylogenetic Analyses
HIV pol sequences were used to construct the transmission phylogeny. The sequences included all of protease and a minimum of reverse transcriptase codons 28–225. The earliest sequence of adequate length of each patient (n = 11 922) was used to construct a maximum-likelihood phylogenetic tree along with 11 390 Los Alamos HIV database background sequences, obtained by using the BLAST (Basic Local Alignment Search Tool) algorithm to find the best matches of the SHCS sequences against the database to help identify which clusters likely involved transmission within Switzerland [15]. The phylogenetic tree was constructed first using the program MUSCLE (MUltiple Sequence Comparison by Log-Expectation), which uses score optimization for sequence alignment against the HIV reference sequence HXB2. Then, insertions related to HXB2 as well as common resistance mutation positions were removed by the program TrimAL [16, 17, 18]. FastTree, which infers a maximum-likelihood phylogeny, was utilized for the final phylogeny reconstruction [19, 20].
Transmission clusters were extracted from the phylogeny, based on the genetic distance threshold of 3%. The clusters were analyzed to examine the proximity of trans women to other risk groups.
RESULTS
Identification of Trans Women
From the 20 925 patients in the SHCS, we identified 89 trans women, indicating a prevalence of 0.4%. Of these, 72 were identified via the patient information comments, 49 as being female and “MSM,” 37 from the recorded hormone usage among those with sex recorded as “male” in the database, and 31 from the gynecological information comments. The most commonly used hormones among the trans women are estradiol and cyproterone acetate, the former being used by over half of the trans women population (Supplementary Figure 1). The majority of the trans women joined the study since 2006 (Supplementary Figure 2).
Characteristics of the Trans Women Population
Overall, several demographic traits significantly differ between trans women and other risk groups (Table 1, Figure 1). Trans women registered into the SHCS at a similar age as cis HET women but at a younger age than MSM. They are less likely to be of White ethnicity than MSM, and more likely to be of Asian or Hispanic ethnicity compared with the other 2 groups. Nineteen of the 27 trans women of Asian background are from Thailand, the most represented foreign nationality (second-most represented is Brazil, with 14). Similar to cis HET women, trans women are significantly less likely to have obtained higher education compared with MSM.
Table 1.
Overview of Demographic Traits of Trans Women in the Swiss HIV Cohort Study
| Trans Women (n = 89) | MSM (n = 8161) | Cis HET Women (n = 3630) | |
|---|---|---|---|
| Age at study registration (mean), years | 34.6 | 38.7 | 34.9 |
| P < .001 | P = .742 | ||
| Ethnicity, n (%) | |||
| White | 45 (50.1) | 6533 (80.1) | 1588 (43.7) |
| Black | 2 (2.2) | 109 (1.3) | 1273 (35.1) |
| Hispanic | 14 (15.7) | 332 (4.1) | 121 (3.3) |
| Asian | 27 (30.3) | 208 (2.5) | 254 (7.0) |
| P < .001 | P < .001 | ||
| Self-reported sexual orientation, n (%) | … | … | |
| Homosexuala | 60 (67.4) | ||
| Heterosexual | 3 (3.4) | ||
| Bisexual | 23 (25.8) | ||
| Self-reported route of HIV infection, n (%) | … | … | |
| “MSM”a | 62 (69.7) | ||
| HET | 18 (20.2) | ||
| IDU | 3 (3.4) | ||
| Not in full-time work, n/N (%) | 7/11 (63.6) | 1102/2125 (51.9) | 684/999 (68.5) |
| P = .117 | P = .290 | ||
| Educational level, n/N (%) | |||
| No mandatory education | 15/84 (17.9) | 162/6831 (2.4) | 469/3229 (14.5) |
| HS/apprenticeship | 50/84 (59.5) | 3496/6831 (51.2) | 2091/3229 (64.8) |
| Higher education | 19/84 (22.6) | 3173/6831 (46.5) | 669/3229 (20.7) |
| P < .001 | P = .574 | ||
| SHCS center, n (%) | |||
| Zurich | 45 (50.6) | 3761 (46.0) | 904 (24.9) |
| Basel | 16 (18.0) | 811 (9.4) | 438 (12.1) |
| Geneva | 11 (12.4) | 1148 (14.1) | 597 (16.4) |
| Lausanne | 10 (11.2) | 1093 (13.4) | 783 (21.6) |
| Bern | 3 (3.4) | 850 (10.4) | 541 (14.9) |
| St Gallen | 3 (3.4) | 314 (3.8) | 252 (6.9) |
| Lugano | 1 (1.1) | 184 (2.3) | 115 (3.2) |
| P = .079 | P < .001 |
Table indicates demographic traits for trans women as well as of MSM and cis HET women, with statistical testing comparing if the distribution of traits is significantly different between trans women and the 2 other groups. Abbreviations: HET, heterosexual; HS, high school; IDU, injection drug user; MSM, men who have sex with men; SHCS, Swiss HIV Cohort Study.
aAs patient data collection prior to 2020 ignored gender identity, “homosexual” here often refers to transwomen who are attracted to men. This also explains the large proportion being originally listed in the “MSM” risk group.
With regard to certain clinical variables, there are more similarities between trans women and MSM: trans women, like MSM, are much more likely than cis HET women to have had a prior positive syphilis test (Table 2). As for HIV viral subtype, trans women hold an intermediate position between MSM and cis HET women: they are more likely to have a recombinant or non-B subtype compared with MSM, but less likely compared with cis HET women, a reflection of the differences in ethnic/geographic origin between the 3 groups.
Table 2.
Overview of HIV- and Sexually Transmitted Infection–Related Clinical Data of Trans Women
| Trans Women (n = 89) | MSM (n = 8161) | Cis HET Women (n = 3630) | |
|---|---|---|---|
| HIV subtype, n (%) | |||
| B (HIV-1, group M, non-recombinant) | 42 (73.7) | 4576 (88.9) | 1003 (40.4) |
| Other HIV-1, group M | 4 (7.0) | 184 (3.6) | 787 (31.7) |
| CRF 01_AE | 9 (15.8) | 154 (3.0) | 135 (5.4) |
| CRF 02_AG | 1 (1.8) | 53 (1.0) | 312 (12.6) |
| Other recombinant | 1 (1.8) | 180 (3.5) | 241 (9.7) |
| Other | 0 (0) | 1 (0.02) | 4 (0.2) |
| P < .001 | P < .001 | ||
| CD4 nadir, median (cells/µL, IQR) | 234 (81–343) | 211 (67–346) | 191 (70–304) |
| P = .444 | P = .112 | ||
| HIV viral setpoint, copies/mL (log10 transformed) | 3.448 | 4.127 | 3.827 |
| P = .060 | P = .285 | ||
| Missed at least 1 ART dose weekly in prior month, n/N (%) | 1/88 (1.1) | 98/7554 (1.3) | 105/3380 (3.1) |
| P = 1.00 | P = .523 | ||
| Any positive syphilis test, n/N (%) | 31/86 (36.0) | 2985/6779 (44.0) | 217/3223 (6.7) |
| P = .170 | P < .001 | ||
| Any positive hepatitis C test, n/N (%) | 7/84 (8.3) | 483/6559 (7.4) | 306/3144 (9.7) |
| P = .674 | P = .852 |
Overview of information of HIV- and sexually transmitted infection–related clinical data of trans women as well as of MSM and cis HET women, with statistical testing comparing if the distribution of traits is significantly different between trans women and the 2 other groups. Abbreviations: ART, antiretroviral therapy; HET, heterosexual; HIV, human immunodeficiency virus; IQR, interquartile range; MSM, men who have sex with men.
While trans women are more likely to report a recent occasional sex partner compared with cis HET women, they are less likely to engage in unprotected sex with them compared with MSM (Table 3). Trans women are also more likely to use nonintravenous drugs recreationally and to report depression or prior hospitalization on psychological grounds.
Table 3.
Overview of Risk Behavior, Psychological Health, and Incarceration Data of Trans Women
| Trans Women (n = 89) | MSM (n = 8161) | Cis HET Women (n = 3630) | |
|---|---|---|---|
| Recent occasional sex partner, n/N (%) | 33/84 (39.3) | 2635/6341 (41.6) | 151/3050 (4.95) |
| P = .758 | P < .001 | ||
| Unprotected sex with occasional partner, n/N (%) | 9/29 (31.0) | 1384/2400 (57.7) | 54/134 (40.3) |
| P = .007 | P = .472 | ||
| Heavy smoker, n/N (%) | 15/45 (33.3) | 1537/3699 (41.6) | 432/1276 (33.9) |
| P = .337 | P = 1 | ||
| Libido problems, n/N (%) | 16/48 (33.3) | 1106/3895 (28.4) | 776/1888 (41.1) |
| P = .553 | P = .351 | ||
| High alcohol consumption, n/N (%) | 9/76 (11.8) | 994/5400 (18.1) | 194/2467 (7.9) |
| P = .178 | P = .198 | ||
| History of recreational IV drug use, n/N (%) | 3/89 (3.4) | 239/8161 (2.9) | 42/3630 (1.2) |
| P = .746 | P = .092 | ||
| History of non-IV recreational drug use besides cannabis, n/N (%) | 38/89 (42.7) | 1971/8161 (24.2) | 109/3630 (3.0) |
| P < .001 | P < .001 | ||
| History of recreational drug use besides cannabis, n/N (%) | 38/89 (42.7) | 1994/8161 (24.4) | 119/3630 (3.28) |
| P < .001 | P < .001 | ||
| History of depression, n/N (%) | 43/78 (55.1) | 2352/5811 (40.5) | 1159/2706 (42.8) |
| P = .010 | P = .036 | ||
| Prior hospitalization for psychiatric reasons, n/N (%) | 10/89 (11.2) | 341/8161 (4.2) | 186/3630 (5.1) |
| P = .004 | P = .025 |
Overview of information of high-risk sexual behavior, mental health indicators, and incarceration history for trans women as well as of MSM and cis HET women, with statistical testing comparing if the distribution of traits is significantly different between trans women in comparison to the other 2 groups. Abbreviations: HET, heterosexual; IV, intravenous; MSM, men who have sex with men.
Two data criteria, hormone usage and identification as female “MSM,” are used to infer trans woman identity, as opposed to using the written comments of medical staff. Hence, a sensitivity analysis was performed excluding any trans women identified by either of these 2 criteria alone. This excluded 15 patients. Even with reduced statistical power, the overall characteristics were unchanged (Supplementary Table 1).
Analysis of Transmission Networks Including Trans Women
Of the 89 trans women identified, the 52 (58.4%) with viral sequence data are included in the transmission phylogeny, which is similar to MSM (4701, 57.6%; P = .876) and cis HET women (2281, 62.8%; P = .395). When considering all 3% genetic distance clusters containing 29 trans women, we observed that trans women can be found in various transmission contexts, as inferred from their closest neighbors in these clusters (Figure 2). Only 14 (27%) are closest to a non-SHCS sequence, suggesting that trans women are often within domestic transmission networks. Of these closest neighbors, most are male: 12 are male HETs (23%), 11 MSM (21%), and 5 are male intravenous drug users (10%); 6 are cis HET females (12%), while only 1 (2%) is closest to another other trans woman.
Figure 2.
Transmission clusters in the SHCS including trans women. The 26 transmission clusters (of maximum 3% genetic distance) containing trans women, indicating whether the individuals included are from inside the SHCS or outside (Los Alamos Sequences), are broken down by risk group. Abbreviations: HET, heterosexual; IDU, injection drug user; MSM, men who have sex with men; SHCS, Swiss HIV Cohort Study.
DISCUSSION
In our study, we identified 89 trans women, accounting for 0.4% of cohort patients. While Arcelus et al’s [21] meta-analysis estimates that only 0.003% of the population are trans women, we emphasize that such prevalence studies are based on clinical data and prevalence estimates have increased over time with greater visibility of the trans community and greater social and legal acceptance in certain countries. In contrast, 2 studies, one Belgian and another American, based on self-reported gender identity, estimated that 0.3% of adults are transgender women [22, 23]. Such discrepancies depend on case definition: prevalence study estimates dependent on medical diagnoses or interventions are significantly lower, while estimates based on self-reported gender identity yield higher numbers [24, 25]. Considering that trans women are overrepresented in the PLHIV population and yet only comprise 0.4% of the SHCS population, we are fairly certain that our estimate is an underestimation. From the new sex assigned at birth variable for new SHCS participants enrolled since 2020, we saw a prevalence of 1.6% trans women among newly enrolled cohort patients. While this is higher than our own study estimate, we must note that our 0.4% figure covers the prior 32 years of the cohort until 2020, thus including different phases of the epidemic—for example, the first phase with significantly more transmission due to intravenous drug use. We stress the importance of using self-reported data on gender identity and sex assigned at birth to accurately identify this group. We also note that gender identity is not always static; hence, longitudinally collected gender identity data would also be needed for increasing accuracy. Without taking such measures, conflations occur, such as trans women listed as “homosexual” despite being attracted to men or being listed as men/MSM. This is not only inaccurate, but also harmful, and may suppress participation of trans women in HIV studies.
Within our study, trans women exhibit characteristics distinct from both MSM and cis HET women, showing more similarity to cis HET women for some traits, and to MSM for others. Trans women, like cis HET women, are less likely to be of White ethnicity compared with MSM, especially being Asian or Hispanic. This points to cultural and migrational trends that warrant further investigation. A potential component may be the migration of Thai trans women, or kathoey, to European urban centers [26], which may explain the extremely high percentage (30.3%) of SHCS trans women of Asian background. The other overrepresented foreign nationality, Brazilian, can also be attributed to a similar country-specific cultural/situational component, in addition to sex trafficking, with Switzerland being a common destination for trafficked trans women from Brazil [27].
With regard to high-risk sexual behavior, our data suggest some overlap between MSM and trans women in terms of risk behaviors (such as having recent occasional sex partners and recreational drug use) and transmission networks. This is supported by our phylogenetic analysis, as the transmission clusters suggest more proximity between trans women and MSM than with cis HET women. While this could be used to superficially support the trend in HIV studies to group together MSM and trans women [28–30], trans women are, however, not reducible into being an epidemiological subset of MSM, as they exhibit both epidemiological differences from MSM and phylogenetic associations with other transmission groups (Figure 2).
The greatest disparity is in the mental health data. One in 10 trans women in our study reported prior mental health conditions, in line with other studies [31]. There may also be an association here with recreational drug use, as trans women are the most likely to have used recreational drugs, particularly nonintravenous drugs. This demands further study considering the growing interest in these epidemiological dynamics associating high-risk behavior, mental health conditions, recreational drug use, and HIV and sexually transmitted infection–related clinical outcomes [8, 32]. These factors amplify each other to worsen the overall physical and mental health situation for trans women—an epidemiological dynamic that can be described as a syndemic [33]. Poteat et al [34] similarly to our study, found in their review a higher rate of alcohol/drug use, unprotected sexual intercourse, depression, and victimization by violence among trans women. Our study is thus important in that it describes the overall trans women syndemic in the Swiss context, which is exceptional considering that other studies on trans PLHIV in Europe generally concentrate on a biased sample of sex workers [35–37].
A major limitation is that we mostly relied on comments written by study physicians and nurses and indirect data such as hormone drug information. However, while we presume there are further unidentified trans women, we are confident in the gender identity of those we did identify. The sensitivity analysis, which does not alter our overall findings, bolsters our confidence in the methodology.
The uniquely rich and systematic data of the SHCS allow us to characterize this understudied population in unprecedented detail and depth, as well as to highlight syndemic dynamics. It is essential that further steps are taken to understand this population, as well as trans men and nonbinary trans persons, to better tailor public health interventions.
Supplementary Data
Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments. The authors thank the patients who participated in the Swiss HIV Cohort Study; the physicians and study nurses, for the excellent patient care provided to participants; the resistance laboratories for high-quality genotyping drug-resistance testing; SmartGene (Zug, Switzerland), for technical support; Alexandra Scherrer, Susanne Wild, and Anna Traytel from the SHCS data center for data management; and Marianne Amstutz, Danièle Perraudin, and Mirjam Minichiello for administration.
Financial support. This work was financed in the framework of the Swiss HIV Cohort Study supported by the Swiss National Science Foundation (SNF) (Grant # 177499 and 201369), the Swiss HIV Cohort Study (Project P 863 to K. Kusejko and R. Kouyos), by SNF grant 179571 (to H.F. Günthard), by SNF Grant BSSGI0_155851 to R. Kouyos, The Swiss HIV Research Foundation, Yvonne Jacob Foundation (to H.F. Günthard), Sexuelle Gesundheit Zurich and Arud Zentrum für Suchtmedizin (both funded by the Swiss Federal Office of Public Health).
Potential conflicts of interest. B. Hampel reports grants/support from MSD, Gilead Sciences, and ViiV Healthcare, outside the submitted work. E. Bernasconi has received payment/honoraria for lectures and support for attending meetings to his institution from Gilead Science. Support for meetings to his institution was also received from ViiV Healthcare and Merck Sharpe and Dohme (MSD). E. Bernasconi also received support for attending meetings from Pfizer AG and Abbvie (personal payments). E. Bernasconi reports grants/support (paid to their institution) from MSD, Gilead Sciences, ViiV Healthcare, Pfizer AG, and Abbvie, outside the submitted work. A. Calmy received grants/supports from AbbVie, Gilead, MSD and ViiV Healthcare. M. Cavassini received grants/support and payment to his institution for expert testimony from Gilead Science, MSD, and ViiV Healthcare. M. Cavassini also received travel support and payment/honoraria to his institution for lectures from Gilead Science. H. Rudolph has received support for attending meetings from the City of Zurich, Switzerland, and has participated in voluntary work for the Transgender Network Switzerland; H. Rudolph reports employment with Checkpoint Zurich (Konradstrasse 1, 8005 Zurich), which is funded by Sexuelle Gesundheit Zurich and Arud Zentrum für Suchtmedizin, who are funded by Swiss Federal Office of Public Health; reports payment/honoraria for educational/speaking events and travel support from Stadt Zurich related to general transgender issues, outside the submitted work. H. F. Günthard has received consulting fees from, and has participated on advisory boards for, MSD, Gilead Science, and ViiV Healthcare. H. F. Günthard reports grants/contracts from the National Institutes of Health and Gilead Sciences, outside the submitted work. R. D. Kouyos reports grants/support from Gilead Sciences (paid to their institution), outside the submitted work. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
Swiss HIV Cohort Study Members. A. Anagnostopoulos, M. Battegay, E. Bernasconi, J. Böni, D. L. Braun, H. C. Bucher, A. Calmy, M. Cavassini, A. Ciuffi, G. Dollenmaier, M. Egger, L. Elzi, J. Fehr, J. Fellay, H. Furrer (Chairman of the Clinical and Laboratory Committee), C. A. Fux, H. F. Günthard (President of the SHCS), D. Haerry (deputy of “Positive Council”), B. Hasse, H. H. Hirsch, M. Hoffmann, I. Hösli, M. Huber, C. Kahlert, L. Kaiser, O. Keiser, T. Klimkait, R. D. Kouyos, H. Kovari, B. Ledergerber, G. Martinetti, B. Martinez de Tejada, C. Marzolini, K. J. Metzner, N. Müller, D. Nicca, P. Paioni, G. Pantaleo, M. Perreau, A. Rauch (Chairman of the Scientific Board), C. Rudin (Chairman of the Mother & Child Substudy), K. Kusejko (Head of Data Center), P. Schmid, R. Speck, M. Stöckle, P. Tarr, A. Trkola, P. Vernazza, G. Wandeler, R. Weber, and S. Yerly.
Contributor Information
Swiss HIV Cohort Study:
A Anagnostopoulos, M Battegay, E Bernasconi, J Böni, D L Braun, H C Bucher, A Calmy, M Cavassini, A Ciuffi, G Dollenmaier, M Egger, L Elzi, J Fehr, J Fellay, H Furrer, C A Fuc, H F Günthard, D Haerry, B Hasse, H H Hirsch, M Hoffmann, I Hösli, M Huber, C Kahlert, L Kaiser, O Keiser, T Klimkait, R D Kouyos, H Kovari, B Ledergerber, G Martinetti, B Martinez de Tejada, C Marzolini, K J Metzner, N Müller, D Nicca, P Paioni, G Pantaleo, M Perreau, A Rauch, C Rudin, K Kusejko, P Schmid, R Speck, M Stöckle, P Tarr, A Trkola, P Vernazza, G Wandeler, R Weber, and S Yerly
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