Hidden drug resistant HIV to emerge in the era of universal treatment access in Southeast Asia.
ABSTRACT Universal access to first-line antiretroviral therapy (ART) for HIV infection is becoming more of a reality in most low and middle income countries in Asia. However, second-line therapies are relatively scarce.
We developed a mathematical model of an HIV epidemic in a Southeast Asian setting and used it to forecast the impact of treatment plans, without second-line options, on the potential degree of acquisition and transmission of drug resistant HIV strains. We show that after 10 years of universal treatment access, up to 20% of treatment-naïve individuals with HIV may have drug-resistant strains but it depends on the relative fitness of viral strains.
If viral load testing of people on ART is carried out on a yearly basis and virological failure leads to effective second-line therapy, then transmitted drug resistance could be reduced by 80%. Greater efforts are required for minimizing first-line failure, to detect virological failure earlier, and to procure access to second-line therapies.
Article: CLINICAL USE OF BOTULEMUM TOXINThe Lancet 11/1988; 332(8620):1139. · 39.21 Impact Factor
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ABSTRACT: Background. Antiretroviral therapy (ART) used as pre-exposure prophylaxis (PrEP) by human immunodeficiency virus (HIV)-seronegative individuals reduces the risk of acquiring HIV. However, the population-level impact and cost-effectiveness of using PrEP as a public health intervention remains debated. Methods. We used a stochastic agent-based model of HIV transmission and progression to simulate the clinical and cost outcomes of different strategies of providing PrEP to men who have sex with men (MSM) in New South Wales (NSW), Australia. Model outcomes were reported as incremental cost effectiveness ratios (ICERs) in 2013 Australian dollars per quality-adjusted life year gained ($/QALYG). Results. The use of PrEP in 10-30% of the entire NSW MSM population was projected to cost an additional $316-952 million dollars over the course of 10 years, and cost more than $400,000 per QALYG compared with the status quo. Targeting MSM with sexual partners ranging between more than 10 to more than 50 partners within six months cost an additional $31-331 million dollars, and cost more than $110,000 per QALYG compared with the status quo. We found pre-exposure prophylaxis is most cost-effective when targeted for HIV-negative MSM in a discordant regular partnership. The ICERs ranged between $8,399 and $11,575, for coverage ranging between 15% and 30%, respectively. Conclusion. Targeting HIV-negative MSM in a discordant regular partnership is a cost-effective intervention. However, this highly targeted strategy would not have large population-level impact. Other scenarios are unlikely to be cost-effective.Clinical Infectious Diseases 01/2014; · 9.42 Impact Factor
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ABSTRACT: The preventative effects of antiretroviral therapy for people with HIV have been debated since they were first raised. Models commenced studying the preventive effects of treatment in the 1990s, prior to initial public reports. However, the outcomes of the preventive effects of antiretroviral use were not consistent. Some outcomes of dynamic models were based on unfeasible assumptions, such as no consideration of drug resistance, behavior disinhibition, or economic inputs in poor countries, and unrealistic input variables, for example, overstated initiation time, adherence, coverage, and efficacy of treatment. This paper reviewed dynamic mathematical models to ascertain the complex effects of ART on HIV transmission. This review discusses more conservative inputs and outcomes relative to antiretroviral use in HIV infections in dynamic mathematical models. ART alone cannot eliminate HIV transmission.TheScientificWorldJournal. 01/2014; 2014:760734.
Hidden Drug Resistant HIV to Emerge in the Era of
Universal Treatment Access in Southeast Asia
Alexander Hoare1, Stephen J. Kerr1,2, Kiat Ruxrungtham2,3, Jintanat Ananworanich1,2,3, Matthew G.
Law1, David A. Cooper1, Praphan Phanuphak2,3, David P. Wilson1*
1National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia, 2The HIV Netherlands Australia Thailand Research
Collaboration, The Thai Red Cross AIDS Research Centre, Bangkok, Thailand, 3Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
Background: Universal access to first-line antiretroviral therapy (ART) for HIV infection is becoming more of a reality in most
low and middle income countries in Asia. However, second-line therapies are relatively scarce.
Methods and Findings: We developed a mathematical model of an HIV epidemic in a Southeast Asian setting and used it to
forecast the impact of treatment plans, without second-line options, on the potential degree of acquisition and transmission
of drug resistant HIV strains. We show that after 10 years of universal treatment access, up to 20% of treatment-naı ¨ve
individuals with HIV may have drug-resistant strains but it depends on the relative fitness of viral strains.
Conclusions: If viral load testing of people on ART is carried out on a yearly basis and virological failure leads to effective
second-line therapy, then transmitted drug resistance could be reduced by 80%. Greater efforts are required for minimizing
first-line failure, to detect virological failure earlier, and to procure access to second-line therapies.
Citation: Hoare A, Kerr SJ, Ruxrungtham K, Ananworanich J, Law MG, et al. (2010) Hidden Drug Resistant HIV to Emerge in the Era of Universal Treatment Access
in Southeast Asia. PLoS ONE 5(6): e10981. doi:10.1371/journal.pone.0010981
Editor: Mark Wainberg, McGill University AIDS Centre, Canada
Received March 3, 2010; Accepted May 11, 2010; Published June 8, 2010
Copyright: ? 2010 Hoare et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors acknowledge funding from the Australian Research Council (DP0771620, FT0991990), National Health and Medical Research Council
(CDA568705), and National Institutes of Health (U01-AI069907). The National Centre in HIV Epidemiology and Clinical Research is funded by the Australian
Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, University of New South Wales. The funders had no role in the study
design, data collection, analysis, decision to publish or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: Dwilson@nchecr.unsw.edu.au
HIV/AIDS arose in Asia in the early-to-mid 1980s. By the
1990s HIV epidemics had established in numerous countries;
among the worst affected were Thailand and Cambodia with HIV
prevalence levels of 1–2%. Currently Thailand, Cambodia, and
Myanmar have been experiencing declines in HIV prevalence
[1,2], however, countries such as Vietnam, Indonesia, Pakistan
and China have observed growth in their epidemics .
Effective antiretroviral therapy (ART) is currently being scaled
up in most countries in the region. In principle, anyone who is
treatment eligible, according to country-specific guidelines but
generally similar to the WHO treatment guidelines for resource
limited settings , can receive ART to slow disease progression
. But with greater treatment coverage there is concern about
the development of drug resistance, especially in countries where
second-line therapy is not widely available. The transmission of
drug-resistant strains can potentially lead to ineffective treatment
for individuals  and reduce their treatment options.
Transmitted drug resistance is a problem around the world,
including the Southeast Asia region. Documented rates of
transmitted drug resistance include 4% in 2003–2004 in Japan
 and increases in Taiwan from 6.6% in 1999–2003 to 12.7% in
2003–2006  and Thailand from ,1% in 2003 to 5.2% in 2006
. The vast majority of patients (,80%) in Asia start treatment
on AZT/d4T plus 3TC plus EFZ/NVP . This regimen is
likely to be the standard for the foreseeable future (perhaps with
tenofovir replacing AZT/d4T). If mutations that confer resistance
to this standard regimen become widespread, ART rollout
strategies could be compromised in a way that is not seen in
developed countries with more treatment options.
The primary means to detect transmitted drug resistance is to
perform blood tests on newly infected treatment-naı ¨ve individuals.
Resistance strains can be divided up into two broad categories,
namely, majority-resistant and minority-resistant variants. Major-
ity resistant strains are detected through conventional nucleotide
sequencing methods after polymerase chain reaction (PCR)
amplification, however, these methods are not sensitive enough
to detect minority-resistant strains that comprise less than ,25%
of the viral population . These minority-resistant variants can
be detected using advanced real time PCR assays [12,13]. There is
potential for these minority strains to go undetected in the
population, leading to under-estimates of transmitted resistance
We sought to estimate the potential levels of acquired and
transmitted (majority and minority) drug resistant strains of HIV
that could emerge in a typical Southeast Asian population. We do
this through the development of a biologically realistic mathemat-
ical transmission model. We use the situation in Thailand as a
representation for a general Asian epidemic and thus calibrated
PLoS ONE | www.plosone.org1June 2010 | Volume 5 | Issue 6 | e10981
the model to reflect the epidemic in Thailand. Thailand is a
leading example of treatment scale-up with the introduction of
ART through the National Access to Antiretroviral Program for
People who have AIDS by the Ministry of Public Health Access to
Care program [14,15] and extended to the government’s National
AIDS Program by the National Health Security Office in 2004
. Our mathematical model is parameterized using specific
clinical, demographic, biological, and behavioral data in and
around Bangkok, Thailand, before second-line therapy became
available. Although second-line therapy is rolling out in Thailand,
it is not available for many HIV-infected people in other countries.
Our model extends previous mathematical models of HIV drug
resistance applied to other settings (e.g. [17,18,19,20]) and models
that incorporate at-risk groups for the Southeast Asian setting .
Our model describes the unique nature of Asian HIV epidemics
whereby epidemics typically emerge and are initially driven by
injecting drug use and sex work. Waves of infection occurred in
these population groups, followed by infection among clients of sex
workers and their regular sexual partners which led to generalized
epidemics. In recent years HIV epidemics have emerged among
men who have sex with men. This epidemic pattern has been
observed in numerous Southeast Asian countries [22,23] and is
captured by our model (see Figure S1). To reflect disease
progression, we assumed that all HIV-infected people progress
from primary/acute HIV infection, to chronic/asymptomatic
infection, to a treatment-eligible stage, and then may receive
treatment (Fig. 1). Each disease stage is associated with a different
viral load and hence a different level of infectiousness [24,25].
Disease progression rates are assumed to be different in the
presence of a majority-resistant strain due to lower viral fitness, but
we assume minority-resistant strains have the same fitness as wild-
type virus. We assume that reduced viral fitness of majority-
resistant strains diminishes their replicative capacity and thus their
ability to be transmitted. A multiplying factor was used to model a
decrease in viral fitness between 5% and 50% [18,19].
Mathematical Details S1 contains more details about the
implementation of this viral fitness factor. Once on treatment,
we assume that patients will continue using their ART regimen,
even if treatment failure occurs, as limited second or third line
treatment options are available in many settings.
The level of adherence to ART is associated with clinical success
[26,27] as systemic drug concentrations determine the degree of
pressure to select for drug resistant strains [28,29,30,31,32].
Figure 1. Schematic diagram of our mathematical model. The natural progression of HIV infection captured by our model, with disease
progression illustrated vertically; the model is also divided into three arms: each arm governs a different type of virus (wild-type, majority-resistant
variants, minority-resistant variants).
Drug Resistant HIV in Asia
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Although there is variability in adherence between people, in our
model we do not explicitly model adherence to ART but based on
international clinical data [33,34,35] we assume that 3–5% of
people on first-line ART select for drug resistant mutations each
year and acquire drug-resistant strains. We track populations of
people infected with either wild-type HIV or strains of drug-
resistant HIV that are detectable or appear to have reverted to
wild-type. Those people who have strains that appear to revert to
wild-type have minority-resistant variants and it is assumed that
majority-resistant variants will quickly emerge under pressure of
ART. We use our model (and uncertainty and sensitivity analyses
[36,37]) to estimate the future trajectories of wild-type and drug-
resistant HIV epidemics, determine the biological, clinical, and
behavioral factors that are most important in giving rise to these
evolving epidemics and how they might change with time in order
to plan public health prevention and clinical practice strategies
most appropriately. Some mathematical modeling has been
carried out to forecast HIV epidemics in Southeast Asia ,
but no previous model has investigated the impact of drug
resistance in this region.
The model was then used to assess the impact of regular viral
load testing in a setting where second line treatment is available
and commenced once virological failure is detected. We assumed
that viral load tests could be performed at regular intervals on all
those who are receiving treatment. We simulated different
scenarios of frequency of viral load testing: once every 2 years,
every year, twice yearly, or quarterly. We also assumed that a
period of one week was required between the time of the test and
receiving the test results and starting the patient on effective
second-line treatment. Full technical detail of the model structure,
assumptions and parameter values can be found in the supporting
Emergence of Drug Resistance
After 10 years of universal ART without access to any second
line therapies, moderately high levels of drug resistance can be
expected in the HIV-infected population. People on ART will start
to acquire drug resistant strains of virus. If second and subsequent
lines of therapy are not widely available and failed regimens
continue to be used then the emergent drug-resistant strains can be
transmitted to susceptible individuals. Subsequently, the propor-
tion of newly-infected treatment-naı ¨ve HIV cases that have drug-
resistant strains could be substantial. Our model estimates that
after 10 years of universal ART without monitoring of treatment
failure and optimizing therapy ,24% of new infections could
include drug-resistant mutations (Fig. 2a). Approximately one-
Figure 2. Stacked column charts indicating proportions of HIV viral types. Proportions of all HIV infections that are predominantly wild-
type virus (blue), drug-resistant strains that are undetectable/minority-resistant variants (green), or drug-resistant strains that can be detected/
majority-resistant variants (red) for HIV-infected cases in (a) primary infection, (b) chronic infection, (c) treatment-eligible stage, and (d) on treatment.
Plots are over the time period since the introduction of universal access, and without any options for second-line therapy.
Drug Resistant HIV in Asia
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third of cases in the primary/acute stage of infection with drug-
resistant mutations could have majority-resistant variants of HIV
that are detectable and the remainder would have minority-
resistant variants (Fig. 2a).
Most subjects infected with transmitted resistant virus
appear to revert to wild type
In the absence of the pressure of ART, majority-resistant strains
of HIV tend to revert to become minority-resistant variants that
appear to be exclusively wild-type and not detected by standard
sequencing methods. According to our model, after 10 years of
universal access to ART without second-line options ,20% of
treatment-naı ¨ve cases in asymptomatic stage would have some
drug-resistant strains and ,17% of cases at treatment-eligible
stage of infection would have some drug-resistant strains (Fig. 2b,
c). However, it is likely that the vast majority of these cases would
have minority-resistant variants: only ,1% and ,1% of the
respective HIV cases would have detectable majority-resistant
variants after 10 years (Fig. 2b,c). Thus, drug-resistant HIV could
remain hidden and will only re-emerge when selective pressure of
ART is applied. Of course, the rate of reversion could differ
between different antiretroviral drug-based mutations. The re-
emergence of drug-resistant strains could be quick once treatment
is commenced by individuals. The vast majority (,95%) of
individuals on ART who have drug-resistant strains would have
majority-resistant variants (Fig. 2d). Based on our model we
estimate that after 10 years of universal treatment access ,20% of
all people that are on ART would have drug-resistant strains of
HIV (Fig. 2d).
Factors determining the prevalence of drug resistance
Key factors giving rise to the prevalence of drug resistance differ
between populations of treatment-naı ¨ve and treatment-experi-
enced individuals. Multivariate sensitivity analyses revealed that
the average time for resistant strains to appear to revert to wild-
type virus and the relative fitness of drug-resistant strains were the
most important parameters for determining the prevalence of
majority-resistant variants in treatment-naı ¨ve cases (Fig. 3a). The
relative fitness of viral strains with resistant mutations is a key
determinant in the prevalence of transmitted drug resistance. The
greater the fitness of these strains the larger the prevalence of
‘hidden’ resistance in the treatment-naı ¨ve population. Transmitted
drug resistance increases with fitter drug-resistant strains and
slower majority-to-minority variant reversion times. In contrast,
the average time for drug-resistant strains to re-emerge upon
pressure of ART (in individuals with minority-resistant variants;
that is, to become majority-resistant variants upon applying
pressure of ART) and the percentage of patients that acquire drug
resistance per year (in individuals with wild-type) were found to be
the most important factors in determining the proportion of
Figure 3. Series of response surfaces from sensitivity analyses. (a) A response surface plot of the proportion of treatment-naı ¨ve HIV-infected
cases with minority-resistant variants versus viral fitness of drug-resistant strains and the average time for majority-resistant variants to revert to
minority-resistant variants in the absence of ART. (b)–(d) Contour plots of the proportion of cases on ART that have majority-resistant variants
(colored contours) versus the rate at which people infected with wild-type acquire drug resistant virus (x-axis) and the average time for majority-
resistant variants to emerge for people infected with minority-resistant variants (y-axis) after (b) 1 year, (c) 5 years, and (d) 10 years of universal
Drug Resistant HIV in Asia
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treated individuals with majority-resistant variants (Fig. 3b–d).
Interestingly, the relative importance of these two factors changes
over time. To illustrate this, in Figure 3b–d we present a series of
contour plots of the prevalence of majority-resistant variants
among the treated population after 1 year (Fig. 3b), 5 years
(Fig. 3c), and 10 years (Fig. 3d) after commencing universal
treatment access. We found that the number of people receiving
treatment that have detectable drug resistance after one year of
universal access to treatment is almost completely dependent on
the percentage that acquire resistance per year, as indicated by the
close to vertical lines in Figure 3b. After five years, the dependence
has begun to shift such that the average time for resistance to
reemerge begins to have an impact on the prevalence of drug-
resistant HIV (Fig. 3c). After 10 years, the prevalence of detectable
drug resistance is now more dependent on the average time for
drug resistance to reemerge for transmitted drug-resistant strains
than on the rate of acquired resistance (Fig. 3d). When projected
even further, after 20 years the vast majority of drug-resistant cases
are due to transmitted resistance (see Figure S2). This suggests that
the nature of the drug-resistant HIV epidemic could change
considerably, initially being driven by acquired resistance and then
evolve to be dominated by cases who have transmitted (but
hidden) drug resistance.
Reducing transmitted drug resistance through viral load
In many Southeast Asian countries, treatment failure is often
realized due to clinical symptoms rather than the presence of
mutationsorvirologicalor immunological failure.Frequent viral load
testing is generally infeasible due to financial constraints. However,
viral load testing for monitoring patients’ responses to ART is
available in some settings and it could be expected that it will become
model to estimate the expected proportion of newly acquired HIV
infections to have drug-resistant strains versus the frequency of viral
load testing of individuals on ART (assuming that treated cases that
experience virological failure commence and are maintained on
second and subsequent lines of therapy that successfully suppresses
viral load). In Figure 4 we present the expected levels of transmitted
drug resistance versus the frequency of viral load testing. As the
testing frequency is increased, a substantial reduction in the
prevalence of transmitted drug resistance is observed. Providing a
test every two years will reduce the prevalence by more than 50%
compared to no viral load testing. With yearly testing, the proportion
of all new infections with transmitted resistance drops below 5% (that
is, an 80% relative reduction). According to our model, if viral load
testing is further increased to every three months, transmitted drug
resistance will make up only ,2.5% of all infections (reducing
transmitted resistance by 90% compared to the situation where no
testing is carried out).When compared to yearly testing, our model
28% and 44% in transmitted drug resistance levels, respectively.
Effective treatment with antiretroviral drugs reduces viral load
which improves the health of treated individuals and also
decreases infectiousness and the potential to transmit the virus to
others [24,25,38]. However, persons infected with drug-resistant
HIV have reduced therapeutic options for their survival [39,40].
Antiretroviral resistance was detected against the first drug used
against HIV, AZT, shortly after it was introduced .
Subsequently, resistance to every currently licensed antiretroviral
drug has been observed. Drug-resistant strains of HIV that are
acquired through use of ART can then be transmitted to
susceptible people. The first report of observed transmission of
drug-resistant HIV was in 1993 . The transmission of drug
resistance is becoming an increasing problem among many nations
with long histories of ART. Data on rates of transmitted and
acquired resistance in Southeast Asian countries is limited. In the
few areas in which HIV transmitted resistance have been
measured in Asia, already moderate levels (,4–5%) have been
observed in some countries [43,44,45]. In other regions of the
world, prevalence of drug resistant HIV among treatment-naı ¨ve
persons has been estimated to be up to 25% . It is important to
implement strategies in Southeast Asian countries to avoid the
Figure 4. Prevalence of transmitted drug resistance after 10 years with various viral load testing frequencies. Testing scenarios
include: no testing, once every two years, once every 1.5 years, yearly, twice yearly, and quarterly. Once tested, it is assumed that anyone failing
treatment is taken off the failed regimen and given access to new treatment.
Drug Resistant HIV in Asia
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high prevalence of transmitted drug resistance that has occurred
We demonstrated that if treatment options are limited for those
who fail first-line therapy then the prevalence of acquired and
transmitted drug resistant strains of HIV could be relatively large.
The prevalence of transmitted drug resistance could be ,24%
after ten years of universal treatment access if there is no viral load
monitoring and access to second-line therapy. However, most
(99%) of the drug resistance could remain ‘hidden’ as minority-
resistant variants that are not detectable by standard sequencing
methods. Majority-resistant variants are likely to emerge at
significantly faster rates than expected once treatment is initiated
. While there is some uncertainty about whether minority-
resistant strains have a substantial [12,48] or limited  impact
on the success of antiretroviral therapy, the impact of majority-
resistant strains on treatment is known to be significant. Majority-
resistant strains may be more likely to survive in the presence of
antiretroviral therapy than wild-type strains, however, they are
likely to have reduced replicative capacity leading to lower viral
loads in plasma and genital fluids and thus lower potential to be
transmitted to other people. Our model demonstrated the
importance of viral fitness whereby strains with higher fitness are
more likely to lead to higher population levels of transmitted drug
resistance (Figure 3a).
To reduce the prevalence of drug resistance among treatment-
naı ¨ve individuals it is recommended that treated cases are
regularly monitored and that second-line and subsequent lines of
therapy are made available for those who have failed first-line
regimens. We investigated the expected impact on transmitted
drug resistance of different frequencies of viral load monitoring
and access to second-line therapy when required. Even with a
modest testing frequency of once every two years for patients on
ART, the model demonstrates a large reduction in the amount of
transmitted drug resistance would be achieved. Testing as
frequently as quarterly could reduce the prevalence of transmitted
drug resistance by ,90%. In Thailand, since 2008 second-line
therapy with TDF/3TC/LPV/r has been widely available as well
as once yearly viral load monitoring and genotyping (for those with
viral load of more than 2000 copies per ml). However, there are
limited treatment options in Thailand and patients with TDF
resistance will have difficulties in finding effective second line
treatment options. Wide availability of third line treatments for
patients in this region will be unlikely in the near future.
Therefore, it is highly important to minimise drug resistance.
Based on our model, yearly testing can reduce transmitted drug
resistance to below 5%. It is important for countries in Southeast
Asia to procure access to second-line therapies and determine ways
of implementing regular viral load monitoring. It will then be
important to procure third-line and salvage therapies for patients
in this region, however, this is unlikely to be feasible in the near
future. Viral load testing is not widely available in many Asian
countries and the emergence of drug resistant HIV is not typically
assessed during patient consultation [49,50]. Without viral load or
genotypic monitoring, late detection of treatment failure may
facilitate the acquisition of numerous additional resistance
mutations . Monitoring of patients’ CD4 counts and viral
load levels is being carried out in the Treat Asia HIV
Observational Database (TAHOD) study . TAHOD and
other surveillance activities such as the Treat Asia Studies to
Evaluate Resistance (TASER) study are important foundations for
monitoring treatment success and detecting the development of
resistance to antiretrovirals. In some countries governments pay
for the first triple combination, but patients pay for other drugs if
the first regimen fails. This barrier to accessing second-line therapy
needs to be overcome else persistent use of sub-optimal or failed
regimens will occur. Continued use of a failed regimen may select
for increases in drug-resistant HIV strains that may then be
transmitted to others.
Limited combinations of antiretrovirals are available for first-
line treatment in most Southeast Asian countries. In Thailand,
first-line therapy is based on NNRTIs and usually consists of a
fixed dose combination of d4T/3TC/NVP, with a newer regimen
of ZDV/3TC/NVP recently rolled out . The prevalence of
resistance in Thailand to NNRTI and NRTI based drug
combinations can restrict second-line options in close to half of
patients . The World Health Organization has recently made
recommendations against use of Triomune (d4T/3TC/NVP) in
initiation of first line therapy [55,56]. New treatment guidelines for
Thailand will also be released shortly . These guidelines
recommend AZT- and TDF- with EFV or NVP and 3TC as
preferred first-line. There is a planned 2-year phase out of d4T for
patients already receiving d4T. Similar clinical approaches may
not be achievable in all resource-limited settings and the use of
Triomune is likely to continue. Obtaining access to more first-line
antiretroviral combinations will also assist with treatment options
and could prolong the time until second-line therapies are
required and reduce the risk of resistant strains being transmitted.
While first-line therapy continues to scale-up around Southeast
Asia it is important to plan for, and control, the emergence of
drug-resistant HIV, particularly as most drug-resistant cases in the
future could be ‘hidden’ as minority-resistant variants. Current
surveillance programs, which are based around testing newly
diagnosed subjects aged less than 25 years rather than genuinely
acute infections, will not detect the scale of the problem. Hidden
transmitted drug resistance has the potential to drive relatively
high levels of drug resistance over the next 5–10 years unless
treated cases are monitored regularly and initiate second-line
therapies soon after the failure of first-line options. Data from
TAHOD suggest that around half of patients beginning ART will
require second-line therapies 3 years after beginning treatment
. Diagnosing newly acquired infections is important for
understanding the true degree of transmitted drug resistance
[9,58] and should be prioritized as we approach the next phase of
HIV epidemics in an era of universal treatment access.
While our model is specifically constructed and calibrated to
reflect the unique epidemiology of HIV transmission in Southeast
Asia, the conclusions drawn from our study can also be applied to
other settings. Most countries in Southeast Asia still use d4T-based
first-line therapy, which is similar to Sub-Saharan Africa. Access to
antiretrovirals is similarly limited in both regions. Our results are
generally applicable to non resource-rich settings in which
suboptimal regimens are used and there are limited therapeutic
options. Our conclusions concerning the dangers of continued use
of failed treatment regimens and important value of regular viral
load monitoring coupled with access to second-line therapies may
assist countries in their scale-up of antiretroviral treatment.
Mathematical Details S1
Found at: doi:10.1371/journal.pone.0010981.s001 (0.54 MB
Detailed description of mathematical
model. Lines between groups indicate interactions for sexual
Found at: doi:10.1371/journal.pone.0010981.s002 (0.82 MB TIF)
The seven population subgroups contained within the
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plot shows the proportion of cases on ART that have majority-
resistant variants (colored contours) versus the rate at which people
infected with wild-type acquire drug resistant virus (x-axis) and the
average time for majority-resistant variants to emerge for people
infected with minority-resistant variants (y-axis) after 20 years of
universal treatment access.
Found at: doi:10.1371/journal.pone.0010981.s003 (0.32 MB TIF)
Response surface plot from sensitivity analysis. This
Conceived and designed the experiments: DPW. Performed the experi-
ments: AH. Analyzed the data: AH. Wrote the paper: AH SK KR JA ML
DAC PP DPW. Supervised the project: DPW. Provided data to inform the
mathematical model: SK. Provided advice and assisted in the interpreta-
tion and presentation of results: KR JA ML DAC PP.
1. Rojanapithayakorn W (2006) The 100% Condom Use Programme in Asia.
Reproductive Health Matters 14: 41–52.
2. (2009) Annual Repot 2008. NCHADS.
3. UNAIDS (2008) 2008 Report on the global AIDS epidemic. Geneva: UNAIDS.
4. WHO (2003) Scaling up antiretroviral therapy in resource-limited settings:
treatment guidelines for a public health approach; Geneva World Health
Organization; Available at http://www.who.int.
5. Chasombat S, McConnell MS, Siangphoe U, Yuktanont P, Jirawattanapisal T,
et al. (2009) National Expansion of Antiretroviral Treatment in Thailand, 2000–
2007: Program Scale-Up and Patient Outcomes. J Acquir Immune Defic Syndr
6. Yam WC, Chen JH, Wong KH, Chan K, Cheng VC, et al. (2006) Clinical
utility of genotyping resistance test on determining the mutation patterns in
HIV-1 CRF01_AE and subtype B patients receiving antiretroviral therapy in
Hong Kong. J Clin Virol 35: 454–457.
7. Gatanaga H, Ibe S, Matsuda M, Yoshida S, Asagi T, et al. (2007) Drug-resistant
HIV-1 prevalence in patients newly diagnosed with HIV/AIDS in Japan.
Antiviral Res 75: 75–82.
8. Chang SY, Chen MY, Lee CN, Sun HY, Ko W, et al. (2008) Trends of
antiretroviral drug resistance in treatment-naive patients with human immuno-
deficiency virus type 1 infection in Taiwan. J Antimicrob Chemother 61:
9. Apisarnthanarak A, Jirayasethpong T, Sa-nguansilp C, Thongprapai H,
Kittihanukul C, et al. (2008) Antiretroviral drug resistance among antiretrovi-
ral-naive persons with recent HIV infection in Thailand. HIV Med 9: 322–325.
10. Srasuebkul P, Calmy A, Zhou J, Kumarasamy N, Law M, et al. (2007) Impact of
drug classes and treatment availability on the rate of antiretroviral treatment
change in the TREAT Asia HIV Observational Database (TAHOD). AIDS Res
Ther 4: 18.
11. Schuurman R, Demeter L, Reichelderfer P, Tijnagel J, de Groot T, et al. (1999)
Worldwide evaluation of DNA sequencing approaches for identification of drug
resistance mutations in the human immunodeficiency virus type 1 reverse
transcriptase. J Clin Microbiol 37: 2291–2296.
12. Johnson JA, Li JF, Wei X, Lipscomb J, Irlbeck D, et al. (2008) Minority HIV-1
drug resistance mutations are present in antiretroviral treatment-naive
populations and associate with reduced treatment efficacy. PLoS Med 5: e158.
13. Peuchant O, Thiebaut R, Capdepont S, Lavignolle-Aurillac V, Neau D, et al.
(2008) Transmission of HIV-1 minority-resistant variants and response to first-
line antiretroviral therapy. AIDS 22: 1417–1423.
14. Chasombat S, Lertpiriyasuwat C, Thanprasertsuk S, Suebsaeng L, Lo YR (2006)
The National Access to Antiretroviral Program for PHA (NAPHA) in Thailand.
Southeast Asian J Trop Med Public Health 37: 704–715.
15. Bunjumnong O. Thailand: access to antiretroviral treatment under Universal
Health Care Scheme; 2002; Barcelona.
16. Maneesriwongul WL, Tulathong S, Fennie KP, Williams AB (2006) Adherence
to antiretroviral medication among HIV-positive patients in Thailand. J Acquir
Immune Defic Syndr 43 Suppl 1: S119–122.
17. Wilson DP, Kahn J, Blower SM (2006) Predicting the epidemiological impact of
antiretroviral allocation strategies in KwaZulu-Natal: the effect of the urban-
rural divide. Proc Natl Acad Sci U S A 103: 14228–14233.
18. Blower S, Bodine E, Kahn J, McFarland W (2005) The antiretroviral rollout and
drug-resistant HIV in Africa: insights from empirical data and theoretical
models. AIDS 19: 1–14.
19. Blower S, Ma L, Farmer P, Koenig S (2003) Predicting the impact of
antiretrovirals in resource-poor settings: preventing HIV infections whilst
controlling drug resistance. Curr Drug Targets Infect Disord 3: 345–353.
20. Sanchez MS, Grant RM, Porco TC, Gross KL, Getz WM (2005) A decrease in
drug resistance levels of the HIV epidemic can be bad news. Bull Math Biol 67:
21. Brown T, Peerapatanapokin W (2004) The Asian Epidemic Model: a process
model for exploring HIV policy and programme alternatives in Asia. Sex
Transm Infect 80 Suppl 1: i19–24.
22. Ruxrungtham K, Brown T, Phanuphak P (2004) HIV/AIDS in Asia. Lancet
23. Weniger BG, Limpakarnjanarat K, Ungchusak K, Thanprasertsuk S,
Choopanya K, et al. (1991) The epidemiology of HIV infection and AIDS in
Thailand. AIDS 5 Suppl 2: S71–85.
24. Quinn TC, Wawer MJ, Sewankambo N, Serwadda D, Li C, et al. (2000) Viral
load and heterosexual transmission of human immunodeficiency virus type 1.
Rakai Project Study Group. N Engl J Med 342: 921–929.
25. Wilson DP, Law MG, Grulich AE, Cooper DA, Kaldor JM (2008) Relation
between HIV viral load and infectiousness: a model-based analysis. Lancet 372:
26. King MS, Brun SC, Kempf DJ (2005) Relationship between adherence and the
development of resistance in antiretroviral-naive, HIV-1-infected patients
receiving lopinavir/ritonavir or nelfinavir. J Infect Dis 191: 2046–2052.
27. Wood E, Hogg RS, Yip B, Harrigan PR, O’Shaughnessy MV, et al. (2003)
Effect of medication adherence on survival of HIV-infected adults who start
highly active antiretroviral therapy when the CD4+ cell count is 0.200 to
0.350610(9) cells/L. Ann Intern Med 139: 810–816.
28. Tam LW, Chui CK, Brumme CJ, Bangsberg DR, Montaner JS, et al. (2008)
The relationship between resistance and adherence in drug-naive individuals
initiating HAART is specific to individual drug classes. J Acquir Immune Defic
Syndr 49: 266–271.
29. Bangsberg DR, Acosta EP, Gupta R, Guzman D, Riley ED, et al. (2006)
Adherence-resistance relationships for protease and non-nucleoside reverse
transcriptase inhibitors explained by virological fitness. AIDS 20: 223–231.
30. Bangsberg DR, Porco TC, Kagay C, Charlebois ED, Deeks SG, et al. (2004)
Modeling the HIV protease inhibitor adherence-resistance curve by use of
empirically derived estimates. J Infect Dis 190: 162–165.
31. Bangsberg DR, Charlebois ED, Grant RM, Holodniy M, Deeks SG, et al. (2003)
High levels of adherence do not prevent accumulation of HIV drug resistance
mutations. AIDS 17: 1925–1932.
32. Harrigan PR, Hogg RS, Dong WW, Yip B, Wynhoven B, et al. (2005) Predictors
of HIV drug-resistance mutations in a large antiretroviral-naive cohort initiating
triple antiretroviral therapy. J Infect Dis 191: 339–347.
33. Maggiolo F, Airoldi M, Kleinloog HD, Callegaro A, Ravasio V, et al. (2007)
Effect of adherence to HAART on virologic outcome and on the selection of
resistance-conferring mutations in NNRTI- or PI-treated patients. HIV Clin
Trials 8: 282–292.
34. Phillips AN, Dunn D, Sabin C, Pozniak A, Matthias R, et al. (2005) Long term
probability of detection of HIV-1 drug resistance after starting antiretroviral
therapy in routine clinical practice. AIDS 19: 487–494.
35. Phillips AN, Leen C, Wilson A, Anderson J, Dunn D, et al. (2007) Risk of
extensive virological failure to the three original antiretroviral drug classes over
long-term follow-up from the start of therapy in patients with HIV infection: an
observational cohort study. Lancet 370: 1923–1928.
36. Blower SM, Dowlatabadi H (1994) Sensitivity and Uncertainty Analysis of
Complex-Models of Disease Transmission: an HIV Model, as an Example.
International Statistical Review 62: 229–243.
37. Hoare A, Regan DG, Wilson DP (2008) Sampling and sensitivity analyses tools
(SaSAT) for computational modelling. Theoretical Biology and Medical
Modelling 5: 4.
38. Attia S, Egger M, Muller M, Zwahlen M, Low N (2009) Sexual transmission of
HIV according to viral load and antiretroviral therapy: systematic review and
meta-analysis. AIDS 23: 1397–1404.
39. Ruxrungtham K, Pedro RJ, Latiff GH, Conradie F, Domingo P, et al. (2008)
Impact of reverse transcriptase resistance on the efficacy of TMC125 (etravirine)
with two nucleoside reverse transcriptase inhibitors in protease inhibitor-naive,
nonnucleoside reverse transcriptase inhibitor-experienced patients: study
TMC125-C227. HIV Med 9: 883–896.
40. Hogg RS, Bangsberg DR, Lima VD, Alexander C, Bonner S, et al. (2006)
Emergence of drug resistance is associated with an increased risk of death among
patients first starting HAART. PLoS Med 3: e356.
41. Larder BA, Darby G, Richman DD (1989) HIV with reduced sensitivity to
zidovudine (AZT) isolated during prolonged therapy. Science 243: 1731–1734.
42. Ho DD, Moudgil T, Alam M (1989) Quantitation of human immunodeficiency
virus type 1 in the blood of infected persons. N Engl J Med 321: 1621–1625.
43. Choi JY, Kim EJ, Park YK, Lee JS, Kim SS (2008) National survey for drug-
resistant variants in newly diagnosed antiretroviral drug-naive patients with
HIV/AIDS in South Korea: 1999–2005. J Acquir Immune Defic Syndr 49:
44. Jittamala P, Puthanakit T, Chaiinseeard S, Sirisanthana V (2009) Predictors of
virologic failure and genotypic resistance mutation patterns in thai children
receiving non-nucleoside reverse transcriptase inhibitor-based antiretroviral
therapy. Pediatr Infect Dis J 28: 826–830.
45. Chetchotisakd P, Anunnatsiri S, Kiertiburanakul S, Sutthent R,
Anekthananon T, et al. (2006) High rate multiple drug resistances in HIV-
infected patients failing nonnucleoside reverse transcriptase inhibitor regimens
Drug Resistant HIV in Asia
PLoS ONE | www.plosone.org7 June 2010 | Volume 5 | Issue 6 | e10981
in Thailand, where subtype A/E is predominant. J Int Assoc Physicians AIDS
Care (Chic Ill) 5: 152–156.
46. Booth CL, Geretti AM (2007) Prevalence and determinants of transmitted
antiretroviral drug resistance in HIV-1 infection. J Antimicrob Chemother 59:
47. Tang JW, Pillay D (2004) Transmission of HIV-1 drug resistance. J Clin Virol
48. Van Laethem K, De Munter P, Schrooten Y, Verbesselt R, Van Ranst M, et al.
(2007) No response to first-line tenofovir+lamivudine+efavirenz despite optimi-
zation according to baseline resistance testing: impact of resistant minority
variants on efficacy of low genetic barrier drugs. J Clin Virol 39: 43–47.
49. Cohen GM (2007) Access to diagnostics in support of HIV/AIDS and
tuberculosis treatment in developing countries. Aids 21 Suppl 4: S81–87.
50. WHO (2008) Towards Universal Access: Scaling up priority HIV/AIDS
interventions in the health sector.
51. Kumarasamy N, Madhavan V, Venkatesh KK, Saravanan S, Kantor R, et al.
(2009) High frequency of clinically significant mutations after first-line generic
highly active antiretroviral therapy failure: implications for second-line options
in resource-limited settings. Clin Infect Dis 49: 306–309.
52. Zhou J, Kumarasamy N, Ditangco R, Kamarulzaman A, Lee CK, et al. (2005)
The TREAT Asia HIV Observational Database: baseline and retrospective
data. J Acquir Immune Defic Syndr 38: 174–179.
53. Sirivichayakul S, Phanuphak P, Pankam T, R OC, Sutherland D, et al. (2008)
HIV drug resistance transmission threshold survey in Bangkok, Thailand.
Antivir Ther 13 Suppl 2: 109–113.
54. Sungkanuparph S, Manosuthi W, Kiertiburanakul S, Piyavong B,
Chumpathat N, et al. (2007) Options for a second-line antiretroviral regimen
for HIV type 1-infected patients whose initial regimen of a fixed-dose
combination of stavudine, lamivudine, and nevirapine fails. Clin Infect Dis
55. (2009) Rapid advice Antiretroviral therapy for HIV infection in adults and
adolescents. Geneva: The World Health Organisation.
56. (2009) Meeting report: revision of WHO ART guidelines for adults and
adolescents. Geneva: The World Heath Organisation.
57. Sungkanuparph S, Techasathi W, Teeraratkul A, Chasombat S,
Bhakeecheepe S, et al. (2010) Thai National Guidelines for Antiretroviral
Therapy in HIV-1 Infected Adults and Adolescents 2010. Asian Biomedicine (in
58. Apisarnthanarak A, Mundy LM (2008) Antiretroviral drug resistance among
antiretroviral-naive individuals with HIV infection of unknown duration in
Thailand. Clin Infect Dis 46: 1630–1631.
Drug Resistant HIV in Asia
PLoS ONE | www.plosone.org8 June 2010 | Volume 5 | Issue 6 | e10981