Understanding the Potential Impact of a Combination HIV Prevention Intervention in a Hyper-Endemic Community.
ABSTRACT OBJECTIVES: Despite demonstrating only partial efficacy in preventing new infections, available HIV prevention interventions could offer a powerful strategy when combined. In anticipation of combination HIV prevention programs and research studies we estimated the population-level impact of combining effective scalable interventions at high population coverage, determined the factors that influence this impact, and estimated the synergy between the components. METHODS: We used a mathematical model to investigate the effect on HIV incidence of a combination HIV prevention intervention comprised of high coverage of HIV testing and counselling, risk reduction following HIV diagnosis, male circumcision for HIV-uninfected men, and antiretroviral therapy (ART) for HIV-infected persons. The model was calibrated to data for KwaZulu-Natal, South Africa, where adult HIV prevalence is approximately 23%. RESULTS: Compared to current levels of HIV testing, circumcision, and ART, the combined intervention with ART initiation according to current guidelines could reduce HIV incidence by 47%, from 2.3 new infections per 100 person-years (pyar) to 1.2 per 100 pyar within 4 years and by almost 60%, to 1 per 100 pyar, after 25 years. Short-term impact is driven primarily by uptake of testing and reductions in risk behaviour following testing while long-term effects are driven by periodic HIV testing and retention in ART programs. If the combination prevention program incorporated HIV treatment upon diagnosis, incidence could be reduced by 63% after 4 years and by 76% (to about 0.5 per 100 pyar) after 15 years. The full impact of the combination interventions accrues over 10-15 years. Synergy is demonstrated between the intervention components. CONCLUSION: High coverage combination of evidence-based strategies could generate substantial reductions in population HIV incidence in an African generalized HIV epidemic setting. The full impact could be underestimated by the short assessment duration of typical evaluations.
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ABSTRACT: The Joint United Nations Programme on HIV/AIDS (UNAIDS) recently updated its global targets for antiretroviral therapy (ART) coverage for HIV-positive persons under which 90 % of HIV-positive people are tested, 90 % of those are on ART, and 90 % of those achieve viral suppression. Treatment policy is moving toward treating all HIV-infected persons regardless of CD4 cell count-otherwise known as treatment as prevention-in order to realize the full therapeutic and preventive benefits of ART. Mathematical models have played an important role in guiding the development of these policies by projecting long-term health impacts and cost-effectiveness. To guide future policy, new mathematical models must consider the barriers patients face in receiving and taking ART. Here, we describe the HIV care cascade and ART delivery supply chain to examine how mathematical modeling can provide insight into cost-effective strategies for scaling-up ART coverage in sub-Saharan Africa and help achieve universal ART coverage.Current HIV/AIDS Reports 09/2014;
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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.
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ABSTRACT: Brazil holds approximately 1/3 of population living infected with AIDS (acquired immunodeficiency syndrome) in Central and South Americas, and it was also the first developing country to implement a large-scale control and intervention program against AIDS epidemic. In this scenario, we investigate the temporal evolution and current status of the AIDS epidemic in Brazil. Specifically, we analyze records of annual absolute frequency of cases for more than 5000 cities for the first 33 years of the infection in Brazil. We found that (i) the annual absolute frequencies exhibit a logistic-type growth with an exponential regime in the first few years of the AIDS spreading; (ii) the actual reproduction number decaying as a power law; (iii) the distribution of the annual absolute frequencies among cities decays with a power law behavior; (iv) the annual absolute frequencies and the number of inhabitants have an allometric relationship; (v) the temporal evolution of the annual absolute frequencies have different profile depending on the average annual absolute frequencies in the cities. These findings yield a general quantitative description of the AIDS infection dynamics in Brazil since the beginning. They also provide clues about the effectiveness of treatment and control programs against the infection, that has had a different impact depending on the number of inhabitants of cities. In this framework, our results give insights into the overall dynamics of AIDS epidemic, which may contribute to select empirically accurate models.PLoS ONE 09/2014; · 3.53 Impact Factor
Understanding the Potential Impact of a Combination
HIV Prevention Intervention in a Hyper-Endemic
Ramzi A. Alsallaq1*, Jared M. Baeten1,2,3, Connie L. Celum1,2,3, James P. Hughes4, Laith J. Abu-
Raddad5,7,8, Ruanne V. Barnabas1,2,6, Timothy B. Hallett9
1Global Health, University of Washington, Seattle, Washington, United States of America, 2Medicine, University of Washington, Seattle, Washington, United States of
America, 3Epidemiology, University of Washington, Seattle, Washington, United States of America, 4Biostatistics, University of Washington, Seattle, Washington, United
States of America, 5Statistical Center for HIV/AIDS Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America,
6Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America, 7Infectious Disease Epidemiology
Group, Weill Cornell Medical College - Qatar, Qatar Foundation - Education City, Doha, Qatar, 8Department of Public Health, Weill Cornell Medical College, Cornell
University, New York, New York, United States of America, 9School of Public Health, Imperial College London, London, United Kingdom
Objectives: Despite demonstrating only partial efficacy in preventing new infections, available HIV prevention interventions
could offer a powerful strategy when combined. In anticipation of combination HIV prevention programs and research
studies we estimated the population-level impact of combining effective scalable interventions at high population
coverage, determined the factors that influence this impact, and estimated the synergy between the components.
Methods: We used a mathematical model to investigate the effect on HIV incidence of a combination HIV prevention
intervention comprised of high coverage of HIV testing and counselling, risk reduction following HIV diagnosis, male
circumcision for HIV-uninfected men, and antiretroviral therapy (ART) for HIV-infected persons. The model was calibrated to
data for KwaZulu-Natal, South Africa, where adult HIV prevalence is approximately 23%.
Results: Compared to current levels of HIV testing, circumcision, and ART, the combined intervention with ART initiation
according to current guidelines could reduce HIV incidence by 47%, from 2.3 new infections per 100 person-years (pyar) to
1.2 per 100 pyar within 4 years and by almost 60%, to 1 per 100 pyar, after 25 years. Short-term impact is driven primarily by
uptake of testing and reductions in risk behaviour following testing while long-term effects are driven by periodic HIV
testing and retention in ART programs. If the combination prevention program incorporated HIV treatment upon diagnosis,
incidence could be reduced by 63% after 4 years and by 76% (to about 0.5 per 100 pyar) after 15 years. The full impact of
the combination interventions accrues over 10–15 years. Synergy is demonstrated between the intervention components.
Conclusion: High coverage combination of evidence-based strategies could generate substantial reductions in population
HIV incidence in an African generalized HIV epidemic setting. The full impact could be underestimated by the short
assessment duration of typical evaluations.
Citation: Alsallaq RA, Baeten JM, Celum CL, Hughes JP, Abu-Raddad LJ, et al. (2013) Understanding the Potential Impact of a Combination HIV Prevention
Intervention in a Hyper-Endemic Community. PLoS ONE 8(1): e54575. doi:10.1371/journal.pone.0054575
Editor: Edward White, Yale School of Public Health, United States of America
Received December 16, 2011; Accepted December 13, 2012; Published January 23, 2013
Copyright: ? 2013 Alsallaq 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: This project was supported by a grant from the National Institutes of Health (1R01AI083034). The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
Three decades into the fight to prevent new HIV infections, no
single intervention has been found to have sufficiently high
efficacy, acceptability, feasibility, and affordability to individually
control the generalized HIV epidemic in sub-Saharan Africa.
However, a growing number of interventions have been shown to
partially reduce HIV risk and have been demonstrated to be
deliverable at scale in Africa. These include reducing sexual risk
behaviour by increasing condom use and decreasing partner
acquisition rate, reducing the likelihood of HIV acquisition by
male circumcision for HIV uninfected men [1–4], and reducing
the infectiousness of persons with HIV by antiretroviral treatment
(ART) [5,6]. High coverage of these available, partially-effective
interventions, delivered in combination, could have substantial
effects on population-level HIV incidence.
HIV testing is the crucial entry point to effective HIV
prevention. For infected persons, knowledge of HIV status enables
referral to care and assessment for ART. Testing can also motivate
male circumcision for HIV uninfected men and reductions in risk
behaviour, particularly among newly diagnosed persons with HIV
[7–10]. However, a large proportion of adults in sub-Saharan
Africa do not know their HIV serostatus ; which impedes the
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delivery and uptake of combination HIV prevention intervention.
Among successful strategies that have been used to greatly increase
HIV testing in a community [12,13] is door-to-door household-
based testing and counselling (HBCT). HBCT programs in
Uganda and South Africa have demonstrated high testing
coverage, with 60–80% of adults learning their HIV serostatus
[14–17]. In one example, community HBCT was followed by
large increases in the frequency of condom use amongst HIV-
infected men , suggesting that wide-scale testing may also shift
Implementation and field evaluation of wide-scale HIV testing
coupled with combination HIV prevention interventions are
urgently needed. Program evaluations and clinical trials are
underway . In advance of results from those studies,
epidemiological and theoretical analyses are required to un-
derstand how different components of the HIV combination
interventions might operate at a population level and how
combination interventions should be designed.
Some previous model projections have suggested that ART
alone could achieve high impact on HIV incidence [19,20], but
have required extremely demanding assumptions such as universal
testing every year and perfect adherence on ART that may not be
attainable [21–27] and could be costly . Also, it is unlikely that
strategies based on ART alone would be enough due to the
difficulty of targeting people with primary HIV infection and
suboptimal adherence and retention in care .
In this article, we use a mathematical model of the HIV
epidemic in South Africa to study HIV incidence under rapid and
high testing coverage that is repeated every four years and the
following interventions: risk reduction following HIV diagnosis
(the first HIV-positive test), medical male circumcision, and ART
initiation following current WHO guidelines (CD4 count #350
cells/ml). First, the interventions are considered individually to
disentangle and characterize their impacts. Secondly, we estimate
the population-level impact of a feasible implementation of
a combination intervention and examine how trials to measure
these effects might be designed. Thirdly, we studied the
implications of expanding ART initiation to be upon HIV
diagnosis. Finally, we determine the factors that influence this
impact and quantify the interaction between the components in
the combined intervention at the short and the long terms. The
HIV settings of South Africa are ideal for our study because of
very high HIV prevalence (17% among 15–49 year-old men and
women) and because trials of a combination of deliverable
prevention interventions are being planned in similar settings.
The Mathematical Model
We constructed a compartmental mathematical model to
represent transmission of HIV in the heterosexual adult popula-
tion in KwaZulu-Natal (KZN), South Africa. A full technical
specification of the model and its parameterization is given in
Supplementary Material S1 and Table 1 (or Table 2 in
Supplementary Material S1) lists the main model inputs. Briefly,
the average sexual life span without HIV infection is 35 years
while the mean duration of the untreated HIV infection is 11 years
and is characterised by stages that vary by CD4 counts and
infectiousness (Figure 1 in Supplementary Material S1). In-
fectiousness varies over the course of infection in the manner
estimated by Hollingsworth et al. based on analyses of cohort data
from rural Uganda [30,31] (Table 1). Following others [32–34],
the modelled population is stratified according to sex, circumcision
status of men, and risk group, with the different risk groups
forming new sexual partnerships at different rates. The model is
fitted to HIV prevalence and incidence data from KZN,
generating a prediction for the time-course of the baseline HIV
incidence in KZN (Figure 1). The potential influence of the type of
model structure was assessed through comparison with published
model results that used different methods and predict the potential
[19,20,28,34,35]. We did not fit the model to sex specific HIV
The intervention scenarios investigated focused on three
partially-effective HIV interventions and were based on achieving
90% HIV testing of adults over one year (for example through
community home based counselling and testing (HBCT)) and
repeated every four years (in the text below we refer to this as
‘community testing’). The three interventions are –1) Risk
behaviour reduction for individuals newly diagnosed with HIV,
2) male circumcision for HIV uninfected men, and 3) ART
initiation for HIV infected persons. A combination prevention
intervention consists of the effects of these three interventions
acting together in KZN population and we studied two possible
combination interventions (Table 2). Estimated HIV incidence
values under individual and combined interventions are compared
against the HIV incidence under a scenario representing the
current standard of care (Table 2). The current standard scenario in
Table 2 reflects the status quo in South Africa where 20% of the
population is tested for HIV annually , 10% of men undergo
medical circumcision in 4 years, and ART threshold of initiation is
according to former South Africa guideline at CD4 count #200
cells/mm3but most treatment initiation occurs at CD4 count
,100 cells/mm3due to the low rate of testing [37,38]. Also in this
scenario men and women newly diagnosed with HIV increase
condom use by 12.5% and 6.25% and decrease partner
acquisition rate by 12.5% and 12.5%, respectively, and keep this
reduction in risk behaviour for a year on average.
Assumed coverage levels of the community testing and the
interventions were chosen to be optimistic but potentially achiev-
able. Community testing increases the proportion of adults that
‘know’ their HIV status to 90%; new rounds of community testing
are implemented every 4 years, allowing persons infected in the
interim or not tested in previous rounds to learn their status. No
testing is assumed to take place between the rounds of the four-
yearly community testing and sensitivity analyses incorporated
lower testing levels in each HIV testing. The model allows
retesting individuals and tracks whether they have been infected
since their last HIV test or remain uninfected (Figure 2 in
Supplementary Material S1). HIV-infected adults who are newly
diagnosed, unless otherwise noted, experience risk behaviour
changes by increasing their frequency of condom use and reducing
formation of casual partnerships [8,39]. We assumed no reduction
in risk behaviours for persons who test HIV negative. Newly
diagnosed HIV-positive men and women increase condom use by
25% and 12.5% and a decrease in partner acquisition rate by 25%
and 25% for an average duration of 3 years, respectively. A
spectrum of risk behaviour reduction with variable duration was
studied for sensitivity analysis.
Current KZN circumcision prevalence (27% ) is assumed in
all model simulations as the circumcision rate at adolescence.
Consistent with South African national targets for 2016 ,
circumcision intervention is represented by a proportion (70%) of
uncircumcised men getting circumcised over 2 years from the start
of the intervention campaign with sufficient circumcision opera-
tions in subsequent years to sustain this level of coverage. Lower
circumcision levels of coverage are considered in sensitivity
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analyses. Male circumcision is assumed to reduce the chance of
female-to-male transmission by 60% in each sex act [1–3].
HIV infected individuals who are aware of their HIV status are
implicitly assumed to have regular CD4 count monitoring and
thus access ART promptly after their CD4 cell count falls below
a chosen threshold (two thresholds are modelled: former South
Africa guideline to initiate ART at CD4 # 200/mm3and current
South Africa and WHO guidelines, to initiate ART at CD4 # 350
cells/mm3, as well as ART soon after their first positive HIV
test, irrespective of CD4 count). Individuals unaware of their HIV
status typically initiate ART according at CD4 count below 100
cells/mm3. Individuals receiving ART stop doing so (‘drop out’) at
a rate of 14.5% per year  which corresponds to reported ART
retention in South Africa . HIV-infected individuals on ART
are assumed to be 92% less infectious than individuals not on ART
Measuring the interaction between co-existing interventions: to
tease out any interaction between the interventions 1,2,3, …,n
when their effects coexist in a population (that is to say they are
combined) we introduce a measure of synergy through calculating
extra reduction in incidence. Let the incidence under current-
standard at time t be I0(t) and the incidence under the individual
interventions 1, 2, 3, …, n be I1(t), I2(t), I3(t),…, In(t), respectively.
If the incidence when the interventions are acting together is Ic,
The combined interventions have interaction if Synergy is non-
zero, have synergy if Synergy is positive, and otherwise they are
redundant: that is one or more of the components are preventing
what the rest of the components are already preventing. To be
noted here is that the above synergy measure is a time varying
quantity because incidence varies with time.
Figure 1. Calibration of model baseline projections by data from Kwazulu-Natal, South Africa. Sources of data used to calibrate the
baseline model were in A) HIV prevalence among women attending prenatal clinics  (dashed lines); HIV prevalence measurement in household-
based surveys (crosses) [36,47]; estimates of HIV incidence in household-based surveys  (dot). In B) district-wide ART coverage statistics  were
used to calibrate baseline trends of ART recruitment. Multiple sets of parameters that were consistent with these data were identified  and
generated model trajectories of baseline prevalence (red lines) and baseline incidence (grey lines) a sample of which is shown here (Supplementary
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First, we disentangle the time variation of the impact of the
three interventions mentioned above by having them acting alone
in the population of KZN. Secondly, we estimate the joint impact
when all of these interventions are in action (denoted as the
‘‘Combination I’’ intervention in Table 2) and quantify the
influence of key determinants of the short-term (at 4 years) and
longer-term (at 15 years) impact on population HIV incidence.
Thirdly, we examine the additional impact of extending the
combination intervention to include treatment upon HIV di-
agnosis irrespective of CD4 cell count – termed the ‘‘Combination
II’’ intervention. Model assumptions for these interventions are
summarized in Table 2. Finally, we study the interaction between
the interventions in Combination I and Combination II over time.
1. Model Fitting
An uncertainty range for the key results is presented below
between parentheses to reflect the uncertainties in calibrating
model parameters to the epidemiological context of KZN. To
reflect this uncertainty, model parameters that are difficult to
estimate reliably are randomly selected, using prior distributions,
from within credible limits based on local demographic data,
reported indicators of sexual behaviour (Table 1 in Supplementary
Material S1). This translates the uncertainty in the model
parameters to multiple model projections. Following a rejection-
sampling procedure  (Supplementary Material S1), we kept
only model projections consistent with: measurements of HIV
prevalence among women attending prenatal care  and in
household surveys [36,47], HIV incidence point estimate using
longitudinal HIV surveillance data from KZN  (Figure 1(A)),
and province-wide ART coverage statistics  (Figure 1(B)).
Thus, the uncertainty range of a scenario is obtained by running
the scenario over alternative model fits (Figure 1) and evaluating
the interquartile range of the results.
2. Individual Impact of Component Interventions
Here, we examine the impact of the individual interventions on
HIV incidence at an early time point (four years after initial
implementation); (Figure 2(A)). Risk behaviour reduction following
HIV diagnosis would be expected to have the greatest impact in
the first years following community testing, but its impact would
then wane, because this reduction in risk is not sustained. The
impact of circumcision grows over time, as more men become
circumcised and receive direct protection from HIV infection, and
as women begin to receive an indirect protection through lower
HIV prevalence in their male partners. In KZN, the impact of
male circumcision as a single intervention is limited (compared to
other settings) given the baseline 27% prevalence of circumcision
among men .
To disentangle the effect of ART from risk behaviour reduction
among newly-identified HIV-infected adults (in Figure 2), we
assume counterfactually that individuals newly diagnosed with
Table 1. Main model assumptions.
Assumption Parameter valueSources
Demography and sexual behaviour
Average sexual life span35 years Representative of adult
population of age (15–49)
Number of unprotected sexual acts per partnership in a partnership with
low sexual activity individual
100Based on estimated frequency
of sex in marital relationships in
South Africa 
Mean duration of infection (untreated HIV)11.0 years[30,74–76]
Excessive mortality (when initiating ART at CD4. .200) compared to non-
5.0 per 100 person-years
Excessive mortality (when initiating ART at CD4# #200) compared to non-
8.0 per 100 person-yearsRepresentative for heightened
morbidity in patients receiving
ART at CD4, ,200 compared to
patients starting ART at
CD4. .200 [78,79]
Multiplicative factor change in baseline HIV transmission probability
From population with acute infection 27
From females relative to from males0.5[80,81]
From HIV infected individuals at risk of opportunistic infections and
heightened viremia in late symptomatic infection stages
From individuals with AIDS0Estimated
From circumcised men1No effect
From individuals on ART0.08ART efficacy of reducing
onward transmission for
persons on ART versus persons
not on ART [5,6]
To circumcised men0.4[1–4]
Condoms both ways 0.1
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HIV do not reduce risk behaviour. The impact of ART alone,
initiated at CD4#350 cells/mm3on HIV incidence is initially
small but grows quickly as a substantial proportion of HIV-
diagnosed adults initiate ART and then reach later stages of
infection while being less infectious than they otherwise would be
. Among the individual interventions based on community
testing, ART as a sole intervention achieved the greatest impact;
by 4 years, HIV incidence was reduced by 33% (32%–34%) (from
2.3 (2.1–2.6) per 100 person-years (pyar) under the current
standard to 1.6 (1.4–1.7) per 100 pyar).
Different thresholds for ART initiation upon knowledge of
status were explored further (Figure 2(B)). Compared to the
current standard, in which low testing rates lead to late entry to
care and treatment initiation at CD4 cell counts mostly below 200
cells/mm3(Table 2), the high community testing rates and ART
initiation would generate progressively greater benefits if started at
higher CD4 counts, particularly if ART is initiated upon HIV
diagnosis. ART initiation at CD4 counts #350 cells/mm3slightly
improves the impact compared to ART at #200 cells/mm3(33%
(32%–34%) versus 24% (23%–25%) reduction in HIV incidence
at 4 years). In contrast, with immediate ART initiation upon
diagnosis the impact on HIV incidence would be more substantial;
our model predicts a 53% reduction in incidence at 4 years
compared to the current standard; growing to 66% at 10 years and
67% at 15 years (Figure 2(B)). The greater initial and long-term
impact of ART initiation upon diagnosis is due to substantially
more individuals readily starting ART, including some in the
highly infectious early phases of infection, with their infectiousness
immediately reduced. For all ART initiation strategies, the full
prevention benefits would not be achieved until 10–15 years after
the start of intervention, when averted infections have terminated
chains of further transmissions. However, for this ‘ART-only’
projection the model does not project HIV incidence to ever fall
below 0.5/100 pyar. This estimate is higher than other model
estimates for ‘Universal test and treat’ intervention [19,28],
because of the partial reduction in HIV infectivity assumed for
ART users [5,50] and due to assumptions about the drop-out from
ART programs and the suboptimal testing coverage of the four-
yearly community testing leading to delays in initiating ART. The
projections of incidence under individual interventions illustrate
the levels of coverage required for large impact to be attained.
3. The Impact of a Combination Intervention
Next, we examine the impact of implementing all three
components (reducing risk behaviour, male circumcision, and
initiating ART at CD4 count of 350) in a combination in-
tervention that is based on community testing (‘Combination I’ in
Table 2). The model indicates that the combination intervention
could reduce incidence, more than any individual intervention
component simulated in Figure 2(A). At 4 years from the start of
the combination prevention intervention incidence is reduced by
47% (43%–50%) to 1.2 (1.1–1.3) new infections per 100 pyar
(Figure 3(A)). With the periodic rounds of community testing
coupled with the interventions, the impact is maintained and
strengthened; otherwise the proportion that know they are infected
(and thus able to be on ART and/or maintain reduced risk
behaviours) declines, as additional people become infected. If the
community testing and the levels of the interventions are
continued, the HIV incidence rate is expected to eventually reach
0.96 per 100 pyar at 25 years, representing a reduction in
incidence of 59% compared to the incidence rate when the
Table 2. Model assumptions of efficacy and uptake for HIV testing, risk behaviour reduction, circumcision and ART in the current
standard and the combination interventions.
Intervention Scenario:Current standard‘‘Combination I’’ ‘‘Combination II’’
Nature of testing Continuously available via VCTCommunity testingCommunity testing
Coverage of HV testing (% of eligible adults) 20  9090
Interval before reaching the above coverage level (years)none11
Interval between rounds of testing (years)no rounds44
Risk Behaviour reductions following HIV diagnosis (Relative to being unaware of status)
Increase in condom use (men/women)12.5%/6.25%1
Decrease in partner acquisition rate (men/women)12.5%/12.5%1
Mean duration of keeping the above behaviour changes1 year1
3 years3 years
Circumcision effect reducing men’s susceptibility to HIV
per sex act
60% [1–3]60% [1–3]60% [1–3]
Proportion of uncircumcised men that are newly circumcised
(final levels are continued in the future)
10% over 4 years70% over 2 years70% over 2 years
ART efficacy of reducing infectiousness92%  92%  92% 
CD4 count threshold at which tested individuals start ART 200*
any CD4 count**
Drop out rate (per year) from ART initiated at any CD4 count 14.5% [44,84]14.5% [44,84]14.5% [44,84]
1Representative values , Baseline values of condom use are listed in Table S3 in Supplementary Material.
**Treatment initiation at HIV stages with CD4.100 cells/mm3is immediate when the individual is aware of status and meeting the guideline and is delayed when
unaware of status by an average duration that is calibrated to reflect current treatment programs [37,38].
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Figure 3(B) indicates the sensitivity of the short-term impact on
HIV incidence to the assumptions about the magnitude and
duration of risk reduction by individuals newly diagnosed with
HIV. Achieving a reduction in incidence of more than 50% in 4
years requires a 40% increase in condom use and a 40% decrease
in the rate of forming new partnerships sustainable for 4 years on
average, this represents more than three times the current levels
and would imply significant change in community norms. If risk
reduction upon HIV diagnosis amounted to a tripling in the
frequency of condom use and in the rate of formation of casual
partnership and lasted for six years on average, then the impact of
the entire combination package would be to reduce HIV incidence
by 53%. Without those risk reductions, the same package would
reduce incidence by only 43%. Thus, the short-term impact of the
combination intervention is most sensitive to the assumptions
about the risk behaviours following the community level HIV
testing campaign; shortly after the start of the intervention, the full
effects of the circumcision and ART components have not
Figure 3(C) shows how the long-term impact of Combination I
is affected by the failure to fully achieve the assumed coverage and
efficacy levels for its components (Table 2). The long-term impact
of Combination I at 15 years after the intervention starts is 52%
(45%–60%) reduction in incidence (from 2.1 (1.9–2.3) to 1.0 (0.9–
1.1) new infections per 100 pyar). With one-third less HIV testing
in each round of community testing, reducing the awareness of
status among the HIV infected individuals, the impact of the
combination intervention is substantially reduced from 52%
(45%–60%) to (33% (25%–41%); largely because ART initiation
would be decreased. By doubling drop-out from ART, the impact
of the combination intervention would also be reduced, to 44%
(36%–51%). Similarly a 50% reduction in the number of men
being circumcised would reduce the impact of Combination I on
HIV incidence to 44% (38%–51%). The long-term impact of the
combination intervention would drop by 12 percentage points
Figure 2. Projections of HIV incidence under implementations of single intervention components after one round of community
HIV testing. (A) The individual impacts of risk reduction following HIV diagnosis (behaviour change), ART, and circumcision acting alone as single
intervention components. ‘ART only’ designates initiating treatment at CD4 threshold of 350. (B) HIV incidence after implementation of ART initiation
at CD4 count threshold of 200, 350, and at any CD4 count for all individuals that have been tested. All Interventions are assumed to commence in
2014. In this figure we assume counterfactually that individuals newly diagnosed with HIV do not reduce risk behaviour except in panel (A) in which
the individual impact of risk reduction following HIV diagnosis is studied. Projections at year 15 are also displayed for comparison.
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Figure 3. Projections of the impact of Combination I intervention on HIV incidence. (A) A 15-year incidence projections with the
continuation of the intervention (arrows indicate the rounds of community HIV testing which are every four years) compared to incidence projections
under individual intervention components (B) Projected incidence rate ratio (IRR) (colour coded) in year 4 with respect to current practice incidence
at different assumptions of risk behaviour reduction following HIV diagnosis in the community testing relative to the risk behaviour reduction in the
current standard and average duration of sustainability of this behaviour change. A ratio of risk behaviour reduction of 1 indicates equal behaviour
change among newly HIV-diagnosed adults in community and in venue (current standard) testing. Incidence reductions of more than 50% (IRR,0.5)
are delineated and the star marks IRR value with risk behaviour change assumptions as in (A) and Table 2, (C) Projections of percentage reduction in
incidence of the Combination I intervention with respect to current standard incidence projection of 2.1 (1.9–2.3) per 100 pyar at year 15 with various
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(from 52% to 40%) if 10% of men compared to 70% were
circumcised in 2 years (Figure 3 in Supplementary Material S1). In
contrast, the long-term impact of the intervention is least affected
by risk reduction following new HIV diagnosis; the long-term
impact of the combination intervention is driven primarily by
ART and circumcision components.
4. The Impact of Universal ART as Part of a Combination
Finally, we investigate the impact of a combination intervention
that includes expanded access to ART by initiating ART upon
diagnosis (the ‘Combination II’ scenario). Under this scenario, the
reduction in incidence would be greater than under Combination
I at the short and long terms. At 4 years the reduction in incidence
is 63% (60%–65%) versus 47% (43%–50%) for Combination I,
and at 15 years the reduction in incidence is 76% (71%–81%)
versus 52% (45%–60%) for Combination I (Figure 4(A)). A
comparison between Figure 4(B) and Figure 3(B) shows that
Combination II impact immediately after the first round of testing
is less sensitive to risk behaviour reduction than the impact of
Combination I. Even with risk behaviour reduction as in the
current standard, Combination II is projected to achieve a 61%
reduction in incidence at 4 years. Similar to Combination I, the
long-term (predicted at year 15) impact of Combination II is
highly sensitive to reduced uptake of HIV testing: with one third
less HIV testing in each round of community testing, incidence
would be reduced by 46% (39%–54%) instead of 76%. The long-
term impact of Combination II is less sensitive to other
assumptions about uptake of circumcision and degree of risk
behaviour reduction (Figure 4(C)). The long-term impact of the
combination intervention would drop by 8 percentage points (from
76% to 68%) if 10% of men compared to 70% were circumcised
in 2 years (Figure 3 in Supplementary Material S1). The influence
of drop-out rate from ART is small because the model allows for
individuals that cease treatment after initiating at a CD4 cell count
.350 cells/mm3to re-initiate treatment when their CD4 cell
count declines below 350 cells/mm3.
The continuation of HIV community testing, immediate
initiation of ART, and circumcision in Combination II in-
tervention would achieve two major goals of HIV prevention
interventions. First, the rate of new HIV infections would
eventually be reduced to a low level: 0.3 new infections per 100
pyar after 25 years. Second, it would reduce the rate of HIV
deaths and simultaneously bring the rate of new HIV infections
below the rate of AIDS death - a point defined as the ‘AIDS
Transition’  within 6–8 years. The trajectory of the HIV
epidemic would continue to decline, potentially enabling the scale
of intervention effort to eventually be reduced.
5. The Interaction between the Intervention Components
of the Combination Interventions
At high levels of coverage for the interventions, the interaction
among them could lead to unneeded excessive protection; this is
the case for example when large numbers of individuals are
exposed to two interventions that reduce the same risk. Newly
diagnosed individuals with HIV can be exposed to ART and risk
reduction. Figure 5 shows that without risk behaviour reduction
after HIV diagnosis, circumcision and ART in Combination I and
II have synergy at all times. With a reduction in the risk behaviour
after HIV diagnosis, the combination interventions have short
periods of marginal redundancy before year 20 due to the
accumulation of large numbers of individuals who have reduced
risk behaviour and initiated ART. Over time, ART drop out and
the waning of behavioural risk reduction eliminate such re-
dundancy and bring back synergy among the intervention
components. At the longer term, and by continuing the
interventions, the substantial reduction in the rate of new
infections reduces the likelihood of such redundancy.
We mathematically modelled a combination prevention pack-
age based on the platform of testing 90% of adults in KwaZulu-
Natal, South Africa through community HIV testing campaigns
every four years coupled with risk behaviour reduction following
HIV diagnosis, ART initiation for HIV-infected adults according
to current WHO and South African guidelines at CD4 # 350
cells/mm3, and male circumcision for HIV-uninfected men. The
model is parameterized to the epidemiological context of KZN
and includes important pragmatic assumptions about initiating
treatment based on knowledge of HIV serostatus, repeating
community testing every four years to identify newly-infected
adults and those not previously tested, and assuming realistic drop-
out rates from ART, suboptimal viral suppression due to imperfect
adherence on ART, incomplete uptake of circumcision with
coverage consistent with targets in the South Africa’s national
plan, and modest and temporary changes in sexual risk behaviours
following HIV testing [5,50]. With high levels of coverage, our
analyses suggest that population HIV incidence could be reduced
by almost 50% within 4 years.
The combination of intervention components that act over
different time scales with different impact on HIV incidence. The
combined effects of these interventions reduce both the risk of
acquisition and transmission of HIV, and could generate rapid,
sustained, and substantial reductions in HIV incidence. Further,
our results suggest that high coverage HIV testing every four years
coupled with high uptake of circumcision and ART initiation upon
HIV diagnosis could reduce HIV incidence and death rates to as
low as 0.3% per year, significantly reducing the scale of the
epidemic. By utilizing a measure for synergy we showed that
although the effects of circumcision, ART, and risk behaviour
reduction coexist in the population as a result of the combination
intervention, the effects substantially strengthen each other
particularly if the assumed levels of coverage for these interven-
tions are maintained.
These findings have important implications for HIV prevention
prioritization and program planning. Large reductions in HIV
incidence in high prevalence settings in sub-Saharan Africa can be
attained with ambitious, but feasible, assumptions about scale-up
coverage and impact of HIV testing, male circumcision, and ART
initiation and retention. Our assumed ambitious levels of coverage
are premised on high coverage in pilot work and preliminary
studies; HIV testing rates in large scale HBCT programs in
Uganda and South Africa have exceeded 80% [14,17,52].
Although in HBCT and couples counselling interventions, sub-
stantial changes in risk behaviour are observed [7,8,39], the
projections of long-term impact of combination interventions in
assumptions of failure to achieve the uptake levels of the interventions in Table 2: (Ia) decreasing testing uptake to 60% in community testing rounds,
(Ib) doubling the drop out rate on treatment to 28% per year, (Ic) halving the uptake of circumcision to 35% of uncircumcised men, and (Id) assuming
no risk behaviour change following HIV diagnosis generated by testing.
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Figure 4. Projections of the impact of Combination II intervention on HIV incidence. (A) A 15-year incidence projections with the
continuation of the intervention (arrows indicate the rounds of community HIV testing which are every four years). (B) Projected Incidence rate ratio
(IRR) (colour coded) in year 4 with respect to current practice incidence at different assumptions of risk behaviour reduction following HIV diagnosis
in the community testing relative to the risk behaviour reduction in the current standard and average duration of sustainability of this behaviour
change. A ratio of risk behaviour reduction of 1 indicates similar extent of behaviour change among tested HIV-infected adults in community and in
venue (current standard) testing. Incidence reductions of more than 65% are delineated and the star marks IRR value with behaviour change
assumptions as in (A) and Table 2 (C) Projections of percentage reduction in incidence of the Combination II intervention with respect to current
standard incidence projection of 2.1 (1.9–2.3) per 100 pyar at year 15 with various assumptions of failure to achieve the uptake levels of the
interventions in Table 2: (IIa) decreasing community testing uptake to 60% in community testing rounds, (IIb) doubling the drop out rate on
treatment to 28% per year, (IIc) halving the uptake of circumcision to 35% of uncircumcised men, and (IId) assuming no risk behaviour change
following HIV diagnosis generated by the testing.
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our model do not rely heavily on risk-behaviour change
assumptions. A challenging key assumption of our model is high
linkage rates of newly identified HIV-infected persons to HIV care
and ART initiation, and subsequent high levels of retention in care
and adherence to treatment which have been shown, consistent
with our findings, to be critical for a long-lasting substantial impact
of treatment at the population level . A pilot of HBCT with
linkages to ART in Uganda has demonstrated that active follow-
up of HIV-infected persons after HBCT can achieve high linkage
with 89% of HIV-infected individuals successfully referred to HIV
We showed that maintaining high coverage levels of testing and
risk reduction, circumcision, and HIV treatment would not
compromise the synergy between these interventions. Optimizing
the prevention benefits of each and every intervention of these to
combat HIV is important due to the imperfections in the current
HIV population-level intervention programs such as the sub-
optimal coverage and adherence levels, the drop out from ART,
and the temporary nature of the reduction in sexual risk behaviour
after HIV diagnoses.
We have not incorporated the impact of circumcision provision
to HIV-infected men, because there is little evidence of direct
effect of circumcision on HIV transmission to women [55,56]. We
have not included risk compensation associated with ART
initiation; because several studies of sexual activity of individuals
initiating ART suggest that such risk compensation is limited [57–
Although there have been other model projections suggesting
single HIV interventions could achieve similar levels of impact,
these have required more demanding assumptions such as
universal testing every year and perfect adherence on ART that
may not be consistently attainable [21–27]. It is unlikely that
strategies based on ART alone would be enough due to the
difficulty of targeting people with primary HIV infection which
some models suggest account for a substantial minority of new
HIV transmissions , suboptimal adherence to ART and follow
up care [29,61,62].
The rapid increase in the numbers of individuals in need of HIV
care and circumcision services, in Combination I and II, demands
parallel increases in the capacity and the accessibility of HIV care
and circumcision clinics. A parallel increase in active follow up
would also be required to achieve ART timely initiation, high
circumcision uptake, and the sustainability of reduced risk
behaviours. The waiting period between the four-yearly testing
waves might facilitate task shifting to active follow up of persons
newly diagnosed with HIV. We have not investigated the financial
obligations and implications of any of our scenarios. Recent studies
have illustrated that among non-traditional counselling and testing
methods, door-to-door HIV counselling and testing in Ugandan
population has the lowest cost  and other studies have
illustrated the cost-effectiveness of starting ART at the new WHO
guideline . We have shown that the intervention components
in Combination I and Combination II have positive and
increasing synergy at the long-term and produce extra reduction
in incidence compared to when they are acting alone. Other
models have also shown that multiple interventions acting together
could drive greater reduction in HIV incidence than could be
feasible with single interventions [64–66].
Our findings have significant implications for studies that aim to
measure the impact of combination HIV prevention. First, the full
impact of combination prevention interventions will be achieved
over 10–15 years. Because most forms of impact evaluations of
combination HIV prevention interventions, including community-
randomized trials and programmatic assessments, are anticipated
to examine impact over a much shorter period (e.g. 2–3 years),
those studies could underestimate the full benefit of combination
packages. Second, our model found that a determinant of short-
term impact of a combination package is risk behaviour reduction
following HIV diagnosis as a product of community testing. If the
degree of risk reduction is less than we assumed, the ability to
measure the impact on HIV incidence in a short-term evaluation
is reduced. The time to see different effect magnitudes for
individual components is an important consideration in the
duration and interpretation of community-randomized trials of
combination prevention, and argues for longer periods of
observation, and monitoring intermediate biologic markers such
as community viral load and key process outcomes such as number
of men circumcised. The growing difference between the impacts
Figure 5. Calculated values of the synergy measure (‘Synergy’, Equation 1) indicating the interaction between circumcision, ART, and
risk behaviour reduction following HIV diagnosis in Combination I and Combination II. To show the synergy between ART and
circumcision, the effects of risk behaviour reduction following HIV diagnosis (RBR) are ignored in calculating the dotted lines. Synergy values that are
larger than zero (shaded region) indicate positive interaction between the interventions and that they are complementing each other in preventing
HIV transmission, while less than zero values indicate that the interventions have redundancy in prevention.
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of Combination I and Combination II over time indicates the
importance of longer periods in comparing the effectiveness of
different combination prevention packages. Lastly, the small
relative differences in the impact of single interventions at the
short-term (Figure 2(A)), could make step-wedge designs untenable
for impact evaluation of separate interventions or joint effects of
combined interventions (in community randomised control trials,
cRCT). To successfully evaluate these effects, it would be essential
to consider long intervals between the phasing of intervention
components, very large numbers of communities, and large sample
Although the efficacy of topical or oral pre-exposure pro-
phylaxis (PrEP) in reducing HIV risk has been demonstrated
[67,68], we have not included PrEP in our analysis pending
further research illustrating its deliverability in sub-Saharan
African settings. If PrEP is included it could strengthen the impact
of a combination intervention even further.
The goal of this model was to evaluate the population-level
impact on HIV incidence if high coverage levels of available
strategies are achieved in KZN, South Africa. The numerical
estimates presented are specific to KZN, and the impact of
interventions in different contexts might vary. In settings where
a lower proportion of men are already circumcised, the impact of
the combination intervention could be greater and more sensitive
to the uptake of circumcision. We have incorporated the
uncertainty in identifying the epidemiological context of KZN
using a rejection-sampling approach. Prioritizing interventions for
specific age, gender, or demographic group was not the focus of
this modelling exercise. Therefore, the model is not age-structured
and has no details about how sexual partnerships are formed
between members of different demographic groups [69–71]. The
model does not include explicit representations for overlapping
sexual partnerships. It does not account for the spread of HIV-
resistant strains, or for potential changes in behaviour in the wider
population following reductions in incidence and AIDS deaths.
The effects of these factors can be addressed by further modelling
as data become available on uptake, behaviour change, viral
suppression, resistance, and clinical outcomes of earlier ART
In summary, combination HIV prevention represents the best
hope for a significant impact in reducing population HIV
incidence in hyperendemic countries. These theoretical model
results indicate that achieving high coverage of evidence-based
combination HIV prevention interventions will have a greater
population impact than any of the individual interventions, and
could lead to large reductions in population HIV incidence in four
years with increased impact thereafter. It is now time to implement
this combination prevention approach in a high prevalence sub-
Saharan setting, with a rigorous evaluation conducted with
sufficient coverage levels and duration in order to assess the
impact on population HIV incidence.
Supplementary Material S1
We thank Drs. Ann Kurth, Elioda Tumwesigye and Judy Wasserheit for
useful discussion on these topics.
Conceived and designed the experiments: RAA TBH. Performed the
experiments: RAA. Analyzed the data: RAA TBH. Contributed reagents/
materials/analysis tools: JMB CLC TBH. Wrote the paper: RAA JMB
CLC JPH LJA RVB TBH.
1. Auvert B, Taljaard D, Lagarde E, Sobngwi-Tambekou J, Sitta R, et al. (2005)
Randomized, controlled intervention trial of male circumcision for reduction of
HIV infection risk: the ANRS 1265 Trial. PLoS Med 2: e298.
2. Bailey RC, Moses S, Parker CB, Agot K, Maclean I, et al. (2007) Male
circumcision for HIV prevention in young men in Kisumu, Kenya: a randomised
controlled trial. The Lancet 369: 643–656.
3. Gray RH, Kigozi G, Serwadda D, Makumbi F, Watya S, et al. (2007) Male
circumcision for HIV prevention in men in Rakai, Uganda: a randomised trial.
The Lancet 369: 657–666.
4. Weiss HA, Thomas SL, Munabi SK, Hayes RJ (2006) Male circumcision and
risk of syphilis, chancroid, and genital herpes: a systematic review and meta-
analysis. Sex Transm Infect 82: 101–109; discussion 110.
5. Donnell D, Baeten JM, Kiarie J, Thomas KK, Stevens W, et al. (2010)
Heterosexual HIV-1 transmission after initiation of antiretroviral therapy:
a prospective cohort analysis. Lancet 375: 2092–2098.
6. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, et al. (2011)
Prevention of HIV-1 Infection with Early Antiretroviral Therapy. N Engl J Med.
A v a i l a b l e :h t t p : / / w w w . n e j m . o r g / d o i / f u l l / 1 0 . 1 0 5 6 /
NEJMoa1105243#t=article. Accessed 2012 Dec 27.
7. Allen S, Tice J, Van de Perre P, Serufilira A, Hudes E, et al. (1992) Effect of
serotesting with counselling on condom use and seroconversion among HIV
discordant couples in Africa. BMJ 304: 1605–1609.
8. Nuwaha F, Tumwesigye E, Kasasa S, Asiimwe S, Wana G, et al. (2009)
Population-level Changes in Knowledge of HIV Status, Stigma, and HIV Risk
Behavior after District-wide Door-to-Door Voluntary Counseling and Testing:
Bushenyi District, Uganda. 16th Conference on Retroviruses and Opportunistic
Infections; 8–11 Feb; Montreal, Canada.
9. Fonner VA, Denison J, Kennedy CE, O’Reilly K, Sweat M (2012) Voluntary
counseling and testing (VCT) for changing HIV-related risk behavior in
developing countries. Cochrane Database Syst Rev 9: CD001224.
10. Denison JA, O’Reilly KR, Schmid GP, Kennedy CE, Sweat MD (2008) HIV
voluntary counseling and testing and behavioral risk reduction in developing
countries: a meta-analysis, 1990–2005. AIDS Behav 12: 363–373.
11. WHO (2011) Epidemic update and health sector progress towards Universal
Access. Progress Report. Available: http://www.who.int/hiv/pub/progress_
report2011/en/index.html. Accessed 2012 Jul 15.
12. Khumalo-Sakutukwa G, Morin SF, Fritz K, Charlebois ED, van Rooyen H, et
al. (2008) Project Accept (HPTN 043): a community-based intervention to
reduce HIV incidence in populations at risk for HIV in sub-Saharan Africa and
Thailand. J Acquir Immune Defic Syndr 49: 422–431.
13. Sweat M, Morin S, Celentano D, Mulawa M, Singh B, et al. (2011) Community-
based intervention to increase HIV testing and case detection in people aged 16–
32 years in Tanzania, Zimbabwe, and Thailand (NIMH Project Accept, HPTN
043): a randomised study. Lancet Infect Dis 11: 525–532.
14. Tumwesigye E, Baeten J, Tumwebaze H, Kurth A, Revall J, et al. (2011)
Potential of household-based HIV counseling and testing as a platform for
targeted referral to HIV prevention and care in Uganda. 6th IAS Conference on
HIV Pathogenesis, Treatment and Prevention. Rome, Italy, 17–20 July 2011.
15. Naik R, Tabana H, Binza W, Zemba W, Doherty T, et al. (2010) Acceptability
of home-based HIV counselling and testing in a rural district in South Africa.
XVIII International AIDS Conference 18–23 Jul. Vienna, Austria.
16. Menzies N, Abang B, Wanyenze R, Nuwaha F, Mugisha B, et al. (2009) The
costs and effectiveness of four HIV counseling and testing strategies in Uganda.
AIDS 23: 395–401.
17. Tumwesigye E, Wana G, Kasasa S, Muganzi E, Nuwaha F (2010) High uptake
of home-based, district-wide, HIV counseling and testing in Uganda. AIDS
Patient Care STDS 24: 735–741.
18. Padian NS, McCoy SI, Manian S, Wilson D, Schwartlander B, et al. (2011)
Evaluation of large-scale combination HIV prevention programs: essential
issues. J Acquir Immune Defic Syndr 58: e23–28.
19. Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG (2009) Universal
voluntary HIV testing with immediate antiretroviral therapy as a strategy for
elimination of HIV transmission: a mathematical model. Lancet 373: 48–57.
20. Montaner JS, Hogg R, Wood E, Kerr T, Tyndall M, et al. (2006) The case for
expanding access to highly active antiretroviral therapy to curb the growth of the
HIV epidemic. Lancet 368: 531–536.
21. Garnett GP, Baggaley RF (2009) Treating our way out of the HIV pandemic:
could we, would we, should we? Lancet 373: 9–11.
22. Cohen MS, Mastro TD, Cates W Jr (2009) Universal voluntary HIV testing and
immediate antiretroviral therapy. Lancet 373: 1077; author reply 1080–1071.
Modelling HIV Combination Intervention
PLOS ONE | www.plosone.org 11 January 2013 | Volume 8 | Issue 1 | e54575
23. Ruark A, Shelton JD, Halperin DT, Wawer MJ, Gray RH (2009) Universal
voluntary HIV testing and immediate antiretroviral therapy. Lancet 373: 1078;
author reply 1080–1071.
24. Epstein H (2009) Universal voluntary HIV testing and immediate antiretroviral
therapy. Lancet 373: 1078–1079; author reply 1080–1071.
25. Jurgens R, Cohen J, Tarantola D, Heywood M, Carr R (2009) Universal
voluntary HIV testing and immediate antiretroviral therapy. Lancet 373: 1079;
author reply 1080–1071.
26. Hsieh YH, de Arazoza H (2009) Universal voluntary HIV testing and immediate
antiretroviral therapy. Lancet 373: 1079–1080; author reply 1080–1071.
27. Assefa Y, Lera M (2009) Universal voluntary HIV testing and immediate
antiretroviral therapy. Lancet 373: 1080; author reply 1080–1081.
28. Dodd PJ, Garnett GP, Hallett TB (2010) Examining the promise of HIV
elimination by ‘test and treat’ in hyperendemic settings. AIDS 24: 729–735.
29. Lange JM (2011) ‘‘Test and treat’’: is it enough? Clin Infect Dis 52: 801–802.
30. Hollingsworth TD, Anderson RM, Fraser C (2008) HIV-1 transmission, by stage
of infection. J Infect Dis 198: 687–693.
31. Wawer MJ, Gray RH, Sewankambo NK, Serwadda D, Li X, et al. (2005) Rates
of HIV-1 transmission per coital act, by stage of HIV-1 infection, in Rakai,
Uganda. J Infect Dis 191: 1403–1409.
32. Anderson RM, Garnett GP (2000) Mathematical models of the transmission and
control of sexually transmitted diseases. Sex Transm Dis 27: 636–643.
33. Hallett TB, Gregson S, Mugurungi O, Gonese E, Garnett GP (2009) Assessing
evidence for behaviour change affecting the course of HIV epidemics: A new
mathematical modelling approach and application to data from Zimbabwe.
Epidemics 1: 108–117.
34. Alsallaq RA, Cash B, Weiss HA, Longini IM Jr, Omer SB, et al. (2009)
Quantitative assessment of the role of male circumcision in HIV epidemiology at
the population level. Epidemics 1: 139–152.
35. Hallett TB, Singh K, Smith JA, White RG, Abu-Raddad LJ, et al. (2008)
Understanding the impact of male circumcision interventions on the spread of
HIV in southern Africa. PLOS ONE 3: e2212.
36. Shisana O, Rehle TM, Simbayi LC, Zuma K, Jooste S, et al. (2009) South
African national HIV prevalence, incidence, behaviour and communication
survey 2008: A turning tide among teenagers? Cape Town: HSRC Press.
37. Mutevedzi PC, Lessells RJ, Heller T, Barnighausen T, Cooke GS, et al. (2010)
Scale-up of a decentralized HIV treatment programme in rural KwaZulu-Natal,
South Africa: does rapid expansion affect patient outcomes? Bull World Health
Organ 88: 593–600.
38. Keiser O, Anastos K, Schechter M, Balestre E, Myer L, et al. (2008)
Antiretroviral therapy in resource-limited settings 1996 to 2006: patient
characteristics, treatment regimens and monitoring in sub-Saharan Africa, Asia
and Latin America. Trop Med Int Health 13: 870–879.
39. Celum C, Wald A, Lingappa JR, Magaret AS, Wang RS, et al. (2010) Acyclovir
and transmission of HIV-1 from persons infected with HIV-1 and HSV-2.
N Engl J Med 362: 427–439.
40. Department of Health SA (2003) Demographic and Health Survey.
41. Department of Health SA (2012) HIV and AIDS and STI Strategic Plan for
South Africa, 2012–2016. Available: http://www.doh.gov.za. Accessed 2012
42. WHO (2010) Antiretroviral therapy for HIV infection in adults and adolescents
recommendations for a public health approach. Available: http://whqlibdoc.
who.int/publications/2010/9789241599764_eng.pdf. Accessed 2011 Dec 10.
43. The Epidemiology Unit of KwaZulu-Natal Department of Health:KwaZulu-
Natal Epidemiology Bulletin (2005). Available: http://www.kznhealth.gov.za/
epibulletin10.pdf.Accessed 2011 Dec 10.
44. Rosen S, Fox MP, Gill CJ (2007) Patient retention in antiretroviral therapy
programs in sub-Saharan Africa: a systematic review. PLOS Med 4: e298.
45. Robert CP, Casella G (2004) Monte Carlo Statistical Methods. New York:
46. Department of Health SA (2009) National Antenatal Sentinel HIV and Syphilis
Prevalence Survey 2008, South Africa. Available: http://journaids.org/images/
uploads/keydocs/08_antenatal_prevalence.pdf. Accessed 2011 Dec 10.
47. Welz T, Hosegood V, Jaffar S, Batzing-Feigenbaum J, Herbst K, et al. (2007)
Continued very high prevalence of HIV infection in rural KwaZulu-Natal,
South Africa: a population-based longitudinal study. AIDS 21: 1467–1472.
48. Barnighausen T, Wallrauch C, Welte A, McWalter TA, Mbizana N, et al. (2008)
HIV incidence in rural South Africa: comparison of estimates from longitudinal
surveillance and cross-sectional cBED assay testing. PLOS One 3: e3640.
49. Rehle T (2010) Personal comunication.
50. 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.
51. Over M (2010) The global AIDS transition: A feasible objective for AIDS policy
(Center for Global Development, Washington, DC, 2010). Available: http://
www.cgdev.org/content/publications/detail/1424143/. Accessed 2011 Dec 10.
52. Tumwesigye E, Asiimwe S, Muganzi E, Achom M, Kabatesi D, et al. (2008)
High HIV Prevalence among Males in Discordant Partnerships in a Full Access
Door–Door VCT Program in Rural Uganda. 15th Conference on Retroviruses
and Opportunistic Infections; 3–6 Feb; Boston, MA.
53. Bendavid E, Brandeau ML, Wood R, Owens DK (2010) Comparative
effectiveness of HIV testing and treatment in highly endemic regions. Arch
Intern Med 170: 1347–1354.
54. Tumwebaze H, Tumwesigye E, Baeten J, Kurth A, Revall J, et al. (2012)
Household-Based HIV Counseling and Testing as a Platform for Referral to
HIV Care and Medical Male Circumcision in Uganda: A Pilot Evaluation. PloS
one 7: e51620.
55. Gray RH, Kiwanuka N, Quinn TC, Sewankambo NK, Serwadda D, et al.
(2000) Male circumcision and HIV acquisition and transmission: cohort studies
in Rakai, Uganda. AIDS 14: 2371–2381.
56. Baeten JM, Donnell D, Kapiga SH, Ronald A, John-Stewart G, et al. (2010)
Male circumcision and risk of male-to-female HIV-1 transmission: a multina-
tional prospective study in African HIV-1-serodiscordant couples. AIDS 24:
57. Bunnell R, Ekwaru JP, Solberg P, Wamai N, Bikaako-Kajura W, et al. (2006)
Changes in sexual behavior and risk of HIV transmission after antiretroviral
therapy and prevention interventions in rural Uganda. AIDS 20: 85–92.
58. McClelland RS, Graham SM, Richardson BA, Peshu N, Masese LN, et al.
(2010) Treatment with antiretroviral therapy is not associated with increased
sexual risk behavior in Kenyan female sex workers. AIDS 24: 891–897.
59. Pearson CR, Kurth AE, Cassels S, Martin DP, Simoni JM, et al. (2007)
Modeling HIV transmission risk among Mozambicans prior to their initiating
highly active antiretroviral therapy. AIDS Care 19: 594–604.
60. Powers KA, Ghani AC, Miller WC, Hoffman IF, Pettifor AE, et al. (2011) The
role of acute and early HIV infection in the spread of HIV and implications for
transmission prevention strategies in Lilongwe, Malawi: a modelling study.
Lancet 378: 256–268.
61. Mugglin C, Althoff K, Wools-Kaloustian K, Sterne J, Nash D, et al. (2012)
Immunodeficiency at the Start of ART: Global View. 19th Conference on
Retroviruses and Opportunistic infections, March 5–8, 2012. Seattle, Washing-
62. Rosen S, Fox MP (2011) Retention in HIV care between testing and treatment
in sub-Saharan Africa: a systematic review. PLOS Med 8: e1001056.
63. Hontelez JA, de Vlas SJ, Tanser F, Bakker R, Barnighausen T, et al. (2011) The
impact of the new WHO antiretroviral treatment guidelines on HIV epidemic
dynamics and cost in South Africa. PLOS One 6: e21919.
64. Schwartlander B, Stover J, Hallett T, Atun R, Avila C, et al. (2011) Towards an
improved investment approach for an effective response to HIV/AIDS. Lancet
65. aids2031 (2010) Costs and Financing Working Group. The Long-Term Costs of
HIV/AIDS in South Africa. Washington, DC: Results for Development
Institute. Available: http://www.resultsfordevelopment.org/sites/
Accessed 2011 Dec 10.
66. Kaldor JM, Wilson DP (2010) How low can you go: the impact of a modestly
effective HIV vaccine compared with male circumcision. AIDS 24: 2573–2578.
67. Baeten JM, Donnell D, Ndase P, Mugo NR, Campbell JD, et al. (2012)
Antiretroviral prophylaxis for HIV prevention in heterosexual men and women.
N Engl J Med 367: 399–410.
68. Thigpen MC, Kebaabetswe PM, Paxton LA, Smith DK, Rose CE, et al. (2012)
Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in
Botswana. N Engl J Med 367: 423–434.
69. Morris M, Kretzschmar M (1997) Concurrent partnerships and the spread of
HIV. AIDS 11: 641–648.
70. Ghani AC, Garnett GP (2000) Risks of acquiring and transmitting sexually
transmitted diseases in sexual partner networks. Sex Transm Dis 27: 579–587.
71. Ghani AC, Swinton J, Garnett GP (1997) The role of sexual partnership
networks in the epidemiology of gonorrhea. Sex Transm Dis 24: 45–56.
72. Poole D, Raftery AE (2000) Inference for deterministic simulation models: The
Bayesian melding approach. Alexandria, VA: American Statistical Association.
73. Johnson LF, Dorrington RE, Bradshaw D, Wyk VP-V, Rehle TM (2009) Sexual
behaviour patterns in South Africa and their association with the spread of HIV:
Insights from a mathematical model. Demographic Research 21: 289–340.
74. Todd J, Glynn JR, Marston M, Lutalo T, Biraro S, et al. (2007) Time from HIV
seroconversion to death: a collaborative analysis of eight studies in six low and
middle-income countries before highly active antiretroviral therapy. AIDS 21
Suppl 6: S55–63.
75. Hollingsworth TD, Anderson RM, Fraser C (2008) HIV-1 transmission, by stage
of infection. The Journal of infectious diseases 198: 687–693.
76. Wandel S, Egger M, Rangsin R, Nelson KE, Costello C, et al. (2008) Duration
from seroconversion to eligibility for antiretroviral therapy and from ART
eligibility to death in adult HIV-infected patients from low and middle-income
countries: collaborative analysis of prospective studies. Sex Transm Infect 84
Suppl 1: i31–i36.
77. Brinkhof MW, Boulle A, Weigel R, Messou E, Mathers C, et al. (2009) Mortality
of HIV-infected patients starting antiretroviral therapy in sub-Saharan Africa:
comparison with HIV-unrelated mortality. PLOS Med 6: e1000066.
78. Lawn SD, Bekker LG, Myer L, Orrell C, Wood R (2005) Cryptococcocal
immune reconstitution disease: a major cause of early mortality in a South
African antiretroviral programme. AIDS 19: 2050–2052.
79. Lawn SD, Myer L, Bekker LG, Wood R (2006) Burden of tuberculosis in an
antiretroviral treatment programme in sub-Saharan Africa: impact on treatment
outcomes and implications for tuberculosis control. AIDS 20: 1605–1612.
80. Padian NS, Shiboski SC, Jewell NP (1991) Female-to-male transmission of
human immunodeficiency virus. JAMA 266: 1664–1667.
81. Nicolosi A, Musicco M, Saracco A, Lazzarin A (1994) Risk factors for woman-
to-man sexual transmission of the human immunodeficiency virus. Italian Study
Modelling HIV Combination Intervention
PLOS ONE | www.plosone.org 12January 2013 | Volume 8 | Issue 1 | e54575
Group on HIV Heterosexual Transmission. J Acquir Immune Defic Syndr 7:
82. Davis KR, Weller SC (1999) The effectiveness of condoms in reducing
heterosexual transmission of HIV. Fam Plann Perspect 31: 272–279.
83. Cremin I, Nyamukapa C, Sherr L, Hallett TB, Chawira G, et al. (2010) Patterns
of self-reported behaviour change associated with receiving voluntary counsel-
ling and testing in a longitudinal study from Manicaland, Zimbabwe. AIDS
Behav 14: 708–715.
84. KwaZulu-Natal Department of Health (2006) Population Data. Available:
http://www.kznhealth.gov.za/census/rates.pdf. Accessed 2011 Dec 10.
Modelling HIV Combination Intervention
PLOS ONE | www.plosone.org13 January 2013 | Volume 8 | Issue 1 | e54575