A longitudinal cohort study of HIV ‘treatment as prevention’ in gay, bisexual and other men who have sex with men: the Treatment with Antiretrovirals and their Impact on Positive And Negative men (TAIPAN) study protocol
Callander et al. BMC Infectious Diseases
A longitudinal cohort study of HIV 'treatment as prevention' in gay, bisexual and other men who have sex with men: the Treatment with Antiretrovirals and their Impact on Positive And Negative men (TAIPAN) study protocol
D. Callander 0
S. Liaw 15
D. P. Wilson 8
A. Grulich 0
D. A. Cooper 0
A. Pedrana 13
B. Donovan 0 14
J. McMahon 12 13
G. Prestage 0 9
M. Stoové 8
A. Carr 7
J. F. Hoy 12 13
K. Petoumenos 0
M. Hellard 8 12
J. Elliot 12 13
D. J. Templeton 0 10 11
M. Holt 5
C. K. Fairley 6 13
N. McKellar-Stewart 3
S. Ruth 4
J. Asselin 8
P. Keen 0
C. Cooper 1
B. Allan 2
J. M. Kaldor 0
R. Guy 0
0 The Kirby Institute, UNSW Australia , Wallace Wurth Building, Sydney, NSW 2052 , Australia
1 PositiveLife New South Wales , Sydney, NSW , Australia
2 Living Positive Victoria , Melbourne, VIC , Australia
3 ACON Northern Rivers , Lismore, NSW , Australia
4 Victorian AIDS Council , Melbourne, VIC , Australia
5 Centre for Social Research in Health, UNSW Australia , Sydney, NSW , Australia
6 Melbourne Sexual Health Centre , Melbourne, VIC , Australia
7 St Vincent's Hospital , Sydney, NSW , Australia
8 Burnet Institute , Melbourne, VIC , Australia
9 Australian Research Centre in Sex, Health and Society, La Trobe University , Melbourne, VIC , Australia
10 Central Clinical School, The University of Sydney , Sydney, NSW , Australia
11 RPA Sexual Health, Community Health , Sydney Local Health District, Sydney, NSW , Australia
12 Alfred Hospital , Melbourne, VIC , Australia
13 Monash University , Melbourne, VIC , Australia
14 Sydney Sexual Health Centre, Sydney Hospital , Sydney, NSW , Australia
15 School of Public Health and Community Medicine, UNSW Australia , Sydney, NSW , Australia
Background: Australia has increased coverage of antiretroviral treatment (ART) over the past decade, reaching 73% uptake in 2014. While ART reduces AIDS-related deaths, accumulating evidence suggests that it could also bolster prevention efforts by reducing the risk of HIV transmission ('treatment as prevention'). While promising, evidence of community-level impact of treatment as prevention on reducing HIV incidence among gay and bisexual men is limited. We describe a study protocol that aims to determine if scale up of testing and treatment for HIV leads to a reduction in community viraemia and, in turn, if this reduction is temporally associated with a reduction in HIV incidence among gay and bisexual men in Australia's two most populous states. Methods: Over the period 2009 to 2017, we will establish two cohorts making use of clinical and laboratory data electronically extracted retrospectively and prospectively from 73 health services and laboratories in the states of New South Wales and Victoria. The 'positive cohort' will consist of approximately 13,000 gay and bisexual men (>90% of all people living with HIV). The 'negative cohort' will consist of at least 40,000 HIV-negative gay and bisexual men (approximately half of the total population). Within the negative cohort we will use standard repeat-testing methods to calculate annual HIV incidence. Community prevalence of viraemia will be defined as the proportion of men with a viral load ≥200RNA copies/mm3, which will combine viral load data from the positive cohort and viraemia estimates among those with an undiagnosed HIV infection. Using regression analyses and adjusting for behavioural and demographic factors associated with infection, we will assess the temporal association between the community prevalence of viraemia and the incidence of HIV infection. Further analyses will make use of these cohorts to assess incidence and predictors of treatment initiation, repeat HIV testing, and viral suppression. Discussion: This study will provide important information on whether 'treatment as prevention' is associated with a reduction in HIV incidence at a community level among gay and bisexual men.
HIV; Treatment as prevention; Cohort; Gay men
Since 1996, combination antiretroviral therapy (ART) for
HIV infection has been used to treat HIV by reducing the
progression to AIDS and preventing AIDS-related deaths.
In recent years, ART has been acknowledged as a key
biomedical component in reducing onward HIV transmission.
Known as ‘treatment as prevention’, the potential for this
public health approach to control HIV transmission was
evident in the landmark HIV Prevention Trials Network
(052) randomised control trial, which in 2011 observed a
96% reduction in HIV transmission to heterosexual
partners of HIV-positive individuals allocated to early ART
compared with those with delayed therapy . More
recently, observational cohorts of both same and opposite
sex couples have provided further supporting evidence,
with no linked HIV transmissions among those with
sustained viral suppression despite thousands of acts of
condomless sex [2, 3]. These findings have formed the basis of
international recommendations to employ treatment as
prevention as an additional strategy to eliminate HIV .
For treatment as prevention to have greatest impact,
HIV testing and treatment coverage must be high and
treatment must be initiated soon after an infection is
diagnosed . National estimates from 2014 showed that
73% of people diagnosed with HIV in Australia were on
ART  and observational research suggests that
treatment coverage has increased over time . Such
increases in treatment coverage likely reflect changes to
HIV treatment guidelines. While earlier guidelines only
recommended ART initiation for people with CD4 cell
count below 350 cells/mm3 in 2012 they were updated
to include consideration for those with counts below
500 cells/mm3 and most recently recommended
treatment initiation as soon as possible after diagnosis
independent of CD4 cell count . Additionally, a number of
policy and structural barriers to HIV treatment were
addressed, including the removal of CD4 cell count criteria
for medication reimbursement through the national
health scheme  and in the state of New South Wales
the removal of upfront co-payments associated with
treatment dispensing .
Alongside treatment, efforts have been made to
increase HIV testing in Australia through a number
largescale health promotion campaigns and new initiatives to
improve access to testing services. Community surveys
of gay and bisexual men in 2014 found that 90% had
ever received an HIV test with two-thirds tested within
the previous year, proportions that have been generally
stable over the past ten years . Among men at
highest risk of infection, Australian guidelines recommend at
least six-monthly HIV testing  but clinical data show
only about half of higher-risk men in 2014 returned for
a follow-up test within six months (up from 40% in
2009) . Thus, there have been some improvements
in HIV testing among gay and bisexual men but to a
lesser degree than for treatment.
Despite improvements in HIV treatment and testing
coverage, annual HIV notifications in Australia increased
by 22% between 2004 and 2012 . In response, many
Australian jurisdictions moved to expand ‘treatment as
prevention’ initiatives and in 2014 all jurisdictional
health ministers committed to a target of virtual HIV
elimination by 2020. In recent years, there has been an
increased focus on testing and treatment initiatives,
implemented through partnerships between governments,
clinicians, community organisations and researchers.
These changes represent a major effort nationally to
advance treatment as prevention.
This paper describes a study titled ‘TAIPAN’
(Treatment with Antiretrovirals and their Impact on Positive
And Negative Men), which aims to establish two large
longitudinal cohorts between 2009 and 2017 to evaluate
if the scale up HIV testing and treatment leads to a
reduction in community viraemia and if this reduction is
temporally associated with a reduction in HIV incidence
among gay and bisexual men.
The primary aim of the study is to determine the
temporal association between the community prevalence of
HIV viraemia and the incidence of HIV infection among
gay and bisexual men at a community-level. The
secondary aims are: i) to assess the association between changes
in guidelines and policies and earlier uptake of HIV
treatment among gay and bisexual men, ii) to identify
incidence and predictors of repeat HIV testing among
HIV negative gay and bisexual men, and iii) to identify
incidence and predictors of supressed HIV viral load
among HIV positive gay and bisexual men.
Two study cohorts will be established in the two
Australian states where approximately 65% of gay and bisexual
men in Australia live: New South Wales (population
~7.6 million) and Victoria (population ~5.9 million).
Study cohorts will be established using de-identified data
extracted from electronic patient medical records. These
data will be collected via an existing health sentinel
surveillance network of clinics and laboratories known as
the Australian Collaboration for Coordinated Enhanced
Sentinel Surveillance of Sexually Transmissible Infections
and Blood Borne Viruses (ACCESS). The existing
network will be expanded from 50 health services and
pathology laboratories in New South Wales and Victorian to
a total of 73, including: 39 publicly-funded sexual health
clinics, 10 general practice clinics with medium to high
caseloads of gay and bisexual men (50 or more patients
per year), six hospital HIV outpatient clinics, four
community-led HIV testing services, and 14 private and
public pathology laboratories.
Expansion of the surveillance network will aim to
capture 95% or more of all HIV viral load tests conducted
in both states as well as 100% of HIV diagnoses. These
targets will be achieved by recruiting all laboratories that
conduct HIV viral load testing as well all reference
laboratories responsible for confirmatory HIV Western
Blot testing. Table 1 outlines the service types and
criteria used to identify health services and laboratories
relevant to TAIPAN.
Using de-identified data extracted from ACCESS sites,
two patient cohorts of gay and bisexual men will be
established: one comprising HIV positive men (‘positive
cohort’) and the other HIV negative men (‘negative
cohort’). The positive cohort will consist of approximately
13,000 HIV positive gay and bisexual men
(approximately 90% of all gay and bisexual men with HIV in
both states) and the negative cohort will consist of at
least 40,000 HIV negative gay and bisexual men
(approximately half of the population).
Both cohorts will be limited to men aged 16 years and
older for whom there is at least once record indicating a
history of sexual contact with other men. Indicators of
same sex contact can be behavioural (i.e., self-reporting
same sex partners), identity-based (i.e., recorded sexual
orientation as gay or bisexual), or procedural (i.e.,
collection of an anal swab for STI testing). The positive cohort
will include patients recorded as HIV positive or those
who receive an HIV diagnosis during the study period.
The negative cohort will include patients whose first
Table 1 Health service and pathology laboratory types and
criteria for the TAIPAN project (n = 73)
Criteria (any) ≥50 HIV gay/bisexual men Any confirmatory HIV
≥20 HIV positive male patients Any HIV viral load
≥5 HIV diagnoses annually
record of HIV testing during the study period is
negative. If during the course of the study a person is
diagnosed with HIV, they will be reclassified to the positive
cohort. Follow-up during the study period will be based
on records from the participating services as well as the
pathology conducted by participating laboratories.
The community prevalence of viraemia is defined as the
proportion of gay and bisexual men (diagnosed and
diagnosed) with a viral load of ≥200 RNA copies/mm .
A viral load of ≥200 was selected as this is a
commonlyused clinical marker of viral suppression and a recent
meta-analysis found no transmission of HIV among
individuals with less than 200 RNA copies/mm3 .
Community prevalence of viraemia was selected as it has
been demonstrated to have the strongest correlation
with HIV incidence over other measures (e.g., mean
viral, treatment coverage) . Our measure of viraemia
will comprise the following four components:
1. Annual prevalence of viraemia: will be calculated
within the positive cohort using the annual
prevalence of viral load test results of ≥200 RNA
copies/mm3 (‘viraemia’) at each patients last viral
load test within a calendar year. We will conduct
sensitivity analyses to include any viral load test
≥200 RNA copies/mm3 in a year and also using a
higher threshold of ≥1000 RNA copies/mm .
2. Annual prevalence of diagnosed HIV infection
among gay and bisexual men: will be estimated using
population prevalence techniques developed by and
used for Australia’s national HIV surveillance .
This approach produces a prevalence estimate using
data on HIV diagnoses from Australia’s National
HIV Registry, adjusting for duplicate entries, deaths,
and migration outside of Australia. For this estimate
we will focus on HIV diagnoses where homosexual
contact is identified as the route of transmission.
3. Annual prevalence of undiagnosed HIV infection
among gay and bisexual men: will be estimated using
standard back-project models  and validated
against a separate bio-behavioural survey conducted
in 2013–2014 and to be repeated in 2017 .
4. Prevalence of viraemia in gay and bisexual men with
undiagnosed HIV infection: will be calculated using
an estimate of undiagnosed infection obtained from
the back-projection models coupled with the
assumption that all undiagnosed men have viral
loads of ≥200 RNA copies/mm3. We will also
Table 2 Overview of TAIPAN research aims, study cohorts involved and outcome indicators
Determine the relationship between viraemia and incidence of new
HIV infections among gay and bisexual men
1. Assess the association between changes in guidelines and policies and earlier uptake of HIV treatment among gay and bisexual men
2. Identify incidence and predictors of repeat HIV testing among HIV negative gay and bisexual men
3. Identify incidence and predictors of supressed HIV viral load among HIV positive gay and bisexual men
consider different viral load levels among
undiagnosed men by using data from the National HIV
Registry and stratifying viral load at diagnosis by
HIV testing history (i.e., reported time since HIV
test prior to diagnosis).
The combination of these components to generate
community viral load is depicted in Fig. 1. We will
calculate an annual community prevalence of viraemia in
gay and bisexual men (diagnosed and undiagnosed) by
combining (i) the annual prevalence of viraemia among
those who have been diagnosed with the estimates of
HIV prevalence, and (ii) the annual prevalence of
viraemia among undiagnosed men with the estimates of
HIV incidence will be calculated using repeat testing
among the negative cohort,  which will consider
Incidence of treatment initiation
Incidence of viral suppression
patients with two or more HIV tests for whom the first
test was negative. We expect that more than 80% of gay
and bisexual men will have at least two tests over the
study period. An incident infection will be defined as an
HIV diagnosis following a negative test and time at risk
will be calculated as the time between each patient’s first
and last test or a patient’s first test and HIV diagnosis.
The number of incident infections will be divided by the
person time (in years) at risk.
Data from the positive cohort will also be used to
calculate the incidence of ART initiation (i.e., the
point at which ART is initiated) with the follow-up
period defined as the time after HIV diagnosis
(person years of infection). This variable will be restricted
only to men diagnosed with HIV during the study
Fig. 1 Method for calculating the prevalence of HIV viraemia among diagnosed and undiagnosed gay and bisexual men
Data from the negative cohort will be used to calculate
the incidence of repeat diagnostic HIV testing. The
incident event is defined as the point at which a patient
achieves a second HIV test within six weeks to 12 months
of a previous test, with follow-up time defined as the
period between a patient’s first HIV test and last clinical
encounter. Follow-up time will cease if a patient has no
recorded service event of any kind within a two year
period but will resume at the point of future service events
(i.e., reengages with a participating service). Follow-up will
also cease if a patient is diagnosed with HIV.
Covariates considered for this study’s analyses will include
patient demographic variables (area of residence, age,
indigenous status, country of birth, if Australia’s public health
insurance scheme ‘Medicare’ was recorded), clinical
information (HIV status, STI diagnoses, CD4 cell count and
viral load results, hepatitis B and C co-infection),
behavioural information (gender(s) of sexual partner, condom
use, injecting drug use, recent sex work, and sexual
partner numbers) and service provision - related
variables (clinic location - urban vs regional/remote, service
type - general practice, sexual health clinic, hospital,
community-led service). Additionally, treatment
information and treatment type will be used to assess the use of
HIV antiretrovirals among the negative cohort as
preand/or post-exposure prophylaxis (‘PrEP’ and ‘PEP’). The
only variables likely to be missing from a substantial
number of records relate to sexual risk behaviour. For this
information we will draw on records from multiple sources
and use a recorded diagnosis of rectal chlamydia and
gonorrhoea as a surrogate marker of risk . Not all
covariates will be relevant to every analysis.
Routine and de-identified patient data will be extracted
from participating service databases, encrypted, and
transmitted electronically to a secure server using customised
software known as GRHANITE™ . These extractions
will provide the data relevant to the co-variate and study
outcomes described above. The accuracy of GRHANITE™
has been assessed via internal reliability checks, which
showed that the software correctly classified all pathology
results as positive or negative, and by comparing extracts
with external laboratory data, which found 92–95%
Data quality checks will be conducted biannually and
will include a review of testing numbers to identify
monthly totals exceeding one standard deviation from the
mean. We will also compare data between service types
(i.e., laboratory tests recorded at participating health
services compared to tests reported by the laboratories
relevant to that service) and by comparing the number of
HIV and STI diagnoses recorded in patient medical record
systems to those reported to the jurisdictional health
departments. We will also work with participating sites to
compare aggregate outputs produced by their systems
internally with those extracted via GRHANITE™.
The GRHANITE™ extraction software de-identifies
patient data by performing one-way cryptographic
transformation of patient details using a secure hash algorithm.
The resultant ‘hashes’ are, therefore, based on patient
details but completely anonymous; they are generated before
data are transmitted from a health service or laboratory to
ensure that potentially identifying details are not extracted
from a participating service . Patient hashes are
generated using four complex algorithms that combine
identifiable patient details (e.g., given and surnames, date of
birth) to generate unidentifiable strings of code. Using a
combination of one or more of these codes, patients will
be linked probabilistically between and within health
services and laboratories. Matching patients on four out of
four hashes represents the highest quality match or what
might be considered near certainty while matching on
fewer hashes suggests less certainty. All matches will be
assessed by comparing available demographic data
between services (e.g., widely disparate ages for one patient
between multiple services).
TAIPAN will undertake four separate analyses to address
the study aims (Table 2).
TAIPAN’s primary aim will be addressed by examining
the temporal relationship between community prevalence
of viraemia and incidence of HIV infection in gay and
bisexual men. For each year of follow up, the community
prevalence of HIV viraemia as determined by the calendar
year will be entered as an independent variable in the
regression. In addition to estimating the effect of
community prevalence of viraemia, we will control at the
individual level for other demographic, clinical and
behavioural determinants of acquisition of new HIV infection,
and recent sexual risk practices. We will use random
effects Poisson models to undertake multi-level analyses
that will allow us to include group-related variables
(community prevalence of viraemia), individual variables
(demographic, clinical, and behavioural) and time.
The study period will be divided into three-year
periods defined by treatment guidelines and policy. The
first period will encompass 2009–2011 and serve as a
‘before’ treatment as prevention period. The second
period will encompass 2012–2014 and represent a
transition period given that several Australian jurisdictions
began to expand treatment as prevention initiatives
during this time. And the third period will encompass
2015–2017, representing the full implementation of
treatment as prevention given that early ART initiation
was recommended for both individual and public health
purposes. In regards to time lags, we assume that HIV
incidence is affected by the estimated prevalence of
virological suppression from the preceding year.
The second analysis will examine the temporal
relationship between the three time periods described above
and the incidence of treatment initiation among men
newly diagnosed with HIV (Secondary Aim 1). Using the
study periods described above in a regression analysis,
incidence of treatment initiation among men newly
diagnosed with HIV will be the outcome variable while
controlling for clinical, demographic and behavioural
factors. Given its historical role in determining when to
initiate treatment, CD4 cell count at diagnosis and HIV
viral load will also be included in the multivariate model.
The third analysis will determine incidence and
predictors of repeat HIV testing (Secondary Aim 2). To calculate
annual estimates we will allocate follow-up time and the
incident of repeat testing (i.e., the point at which a second
test is achieved) to the calendar year in which it occurs.
With this approach it is possible that a patient might
achieve multiple incidents of repeat testing in one calendar
year. In addition to evaluating changes in the incidence of
repeat HIV testing over time, this analysis will employ a
regression analysis to identify demographic, behavioural and
clinical factors associated with repeat testing incidence
among gay and bisexual men in the negative cohort.
The fourth analysis will estimate the incidence of viral
suppression among those newly diagnosed and
predictors of incidence of viral suppression among the positive
cohort (Secondary Aim 3). This analysis will employ
Cox proportional hazards regression. Further, we will
estimate the median time from diagnosis to first viral
suppression by calendar year among those who are
diagnosed during the study period, stratified by CD4 cell
count at diagnosis. For this analysis and all others,
statistical significance will be set at p < 0.05.
Sample size calculations are based on the estimated number
of gay and bisexual men diagnosed with HIV annually in
New South Wales and Victoria,  and assuming a
modelling-derived 30% reduction in infections to 420 per
year in 2015–2017 (i.e., following the full implementation of
treatment as prevention) . For HIV incidence (Primary
Aim) an estimated 80% of men diagnosed annually will have
some HIV testing history, [23, 24] which equates to 336
incident cases annually and will provide 80% power to detect
annual declines in the incidence rate of at least 20% (hazard
ratio [HR] = 0.80). Regarding treatment initiation
(Secondary Aim 1), assuming a rate of treatment initiation of 36 per
100 person years (unpublished data from Australian HIV
Observational Database) and an estimated 420 men newly
diagnosed per year, our analysis will have 80% power to
detect annual relatives changes in treatment initiation after a
new HIV diagnosis of at least 36% (HR = 1.36).
For repeat HIV testing (Secondary Aim 2), it is
estimated that 80% of men in the negative cohort will be
tested at least once annually for HIV [23, 24] and that
25% will have one further test in the year . If the
cohort contains approximately 40,000 men then this
translates into 8000 repeat testers annually, which will
provide sufficient power to detect at least a 6% annual
increase in the incidence of repeat testing (HR = 1.06).
And for viral suppression (Secondary Aim 3), if we
assume that 90% of newly diagnosed men will start
treatment  then we will have 80% power to detect a 15%
increase in the annual incidence of viral suppression
(HR = 1.15). Trend tests over multiple years will have
greater power as will combining over multiple years as
per the three-year study periods relative to the
implementation of treatment as prevention (see Data
Although treatment as prevention has already been shown
to be highly effective among serodiscordant couples,
further evidence is required to determine its
communitylevel impact on HIV incidence among gay and bisexual
men. This issue is particularly relevant in the Australian
context, where testing and treatment coverage is high but
where there has been no decline in annual HIV diagnoses
. The two large cohorts established in this study will
provide detailed information on the level of testing and
treatment coverage that can be achieved and, in the turn,
the impact on HIV incidence.
While clinical trial results and modelling studies have
fostered optimism about the treatment as prevention’s
public health potential, the ultimate reduction of
incidence may be somewhat less than expected in gay and
bisexual men . In Australia, an estimated 12% of people
living with HIV are undiagnosed  with the average time
between infection and diagnosis estimated to be between
two and three years . Undiagnosed infections
contribute disproportionately to HIV transmission due to higher
viral loads and sexual practices . It is, therefore, a key
strength of this study that it will consider the roles of
diagnosed and undiagnosed HIV in onward transmission
among gay and bisexual men.
There have been only a few community-level studies
of treatment as prevention in gay and bisexual men [27–
30]. A consistent limitation in all these studies is the
indirect measurement of HIV incidence, calculated either
via mathematical modelling or derived from case
notifications. Although case notifications in a highly tested
population may be close to reflecting incidence, in
Australia nearly a quarter of diagnoses are considered
‘late’ (CD4 cell counts of <350/mm3)  and trends in
notifications can be influenced by fluctuations in
diagnostic testing. One large, community-level study of
heterosexuals in Africa measured HIV incidence directly
between 2009–2012 and demonstrated a strong
correlation between treatment coverage and HIV incidence at
a community-level . These findings, however, cannot
be applied to gay and bisexual men due to population
differences in sexual behaviour and HIV incidence. In
addition, the levels of HIV testing and treatment
coverage reported in this study were of the levels achieved in
Australia more than a decade ago. Furthermore, any
community-level evaluation of treatment as prevention
must account for potential confounders, including other
prevention and risk reduction strategies and notably the
uptake of PrEP.
Keys strengths of the TAIPAN study design are its
ability to directly measure HIV incidence among gay
and bisexual men, the inclusion of undiagnosed men in
assessing community prevalence of viraemia, and the
large patient cohorts. There are, however, some
limitations to consider. First, the HIV negative cohort will
include approximately half of all gay and bisexual men
across both states. Although very large, the cohorts are
unlikely to be fully representative of all gay and bisexual
men in New South Wales and Victoria. We believe it is
reasonable to assume, however, that any temporal
relationships and predictors of study outcomes we
detect in a cohort of this size will be applicable to the
general population of gay and bisexual men. Second,
during 2016 and 2017 access to PrEP has and will be
expanded in both New South Wales and Victoria.
This parallel prevention initiative may impact on HIV
incidence but we will be able to assess and control
for PrEP uptake in the multivariate analyses through
prescribing data in the HIV negative cohort. Third,
optimism associated with these new prevention
strategies may foster changes in men’s sexual behaviour
and potentially undermine the efficacy of treatment as
prevention. As TAIPAN is not able to collect detailed
sexual risk behaviour data, this question will be
explored via separate studies.
The TAIPAN study will contribute to the growing
body of literature that seeks to understand the impact of
HIV treatment as prevention in a range of settings and
population groups. These study outcomes will have
implications for policy and practice in resource-rich
countries where the epidemic mainly affects gay and bisexual
men. Considering there have been significant
investments in HIV testing and treatment initiatives in recent
years in Australia and overseas, it is vital to assess the
impact of treatment as prevention on HIV incidence.
ACCESS: Australian Collaboration for Coordinated Enhance Sentinel
Surveillance of Sexually Transmissible Infections and Blood Borne Viruses;
AIDS: Acquired immune deficiency syndrome; ART: Antiretroviral therapy;
HIV: Human immunodeficiency virus; PEP: Post-exposure prophylaxis;
PrEP: Pre-exposure prophylaxis; TAIPAN: Treatment with antiretrovirals and
their impact on positive and negative men
DC led the manuscript preparation in consultation with RG. The research was
conceived by RG and developed with all other co-authors. All authors provided
feedback on several drafts of the study protocol and this manuscript. All authors
read and approved the final manuscript.
Ethics approval and consent to participate
The ACCESS Project was reviewed and approved by the lead human research
ethics committees of St Vincent’s Hospital in Sydney (08/051) and the Alfred
Hospital in Melbourne (224/08). The secondary analysis of ACCESS data
proposed in this protocol was reviewed and approved by a low-risk review
panel at the University of New South Wales (HC16560).
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