Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015
Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013- 2015
Sikhulile MoyoID 0 1
Simani Gaseitsiwe 0 1
Terence Mohammed 0 1
Molly Pretorius Holme 0 1
Rui Wang 1
Kenanao Peggy Kotokwe 0 1
Corretah Boleo 0 1
Lucy Mupfumi 0 1
Etienne Kadima Yankinda 0 1
Unoda Chakalisa 0 1
Erik van Widenfelt 0 1
Tendani Gaolathe 0 1
Mompati O. Mmalane 0 1
Scott Dryden-Peterson 0 1
Madisa Mine 1
Refeletswe Lebelonyane 1
Kara BennettID 1
Jean Leidner 1
Kathleen E. Wirth 1
Eric Tchetgen Tchetgen 1
Kathleen Powis 0 1
Janet Moore 1
William A. Clarke 1
Shahin Lockman 0 1
Joseph M. Makhema 0 1
Max Essex 0 1
Vlad Novitsky 0 1
0 Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana, 2 Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, 3 Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America, 4 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston Massachusetts, United States of America, 5 Harvard Medical School , Boston , Massachusetts, United States of America, 6 Division of Infectious Diseases, Brigham and Women's Hospital , Boston , Massachusetts, United States of America, 7 Botswana Ministry of Health and Wellness , Gaborone, Botswana, 8 Bennett Statistical Consulting , Inc., Ballston Lake, New York, United States of America , 9 Goodtables Data Consulting, Norman, OK , United States of America, 10 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, 11 Departments of Internal Medicine and Pediatrics, Massachusetts General Hospital , Boston , Massachusetts, United States of America, 12 U.S. Centers for Disease Control, Atlanta, Georgia, United States of America, 13 Johns Hopkins Hospital , Baltimore, MD , United States of America
1 Editor: Alana T. Brennan, Boston University , UNITED STATES
Botswana is close to reaching the UNAIDS ª90-90-90º HIV testing, antiretroviral treatment
(ART), and viral suppression goals. We sought to determine HIV incidence in this setting
with both high HIV prevalence and high ART coverage.
We used a cross-sectional approach to assessing HIV incidence. A random,
populationbased sample of adults age 16±64 years was enrolled in 30 rural and peri-urban
communities as part of the Botswana Combination Prevention Project (BCPP), from October 2013 ±
November 2015. Data and samples from the baseline household survey were used to
estimate cross-sectional HIV incidence, following an algorithm that combined Limiting-Antigen
Avidity Assay (LAg-Avidity EIA), ART status (documented or by testing ARV drugs in
plasma) and HIV-1 RNA load. The LAg-Avidity EIA cut-off normalized optical density (ODn)
was set at 1.5. The HIV-1 RNA cut-off was set at 400 copies/mL. For estimation purposes,
Development Committee (HRDC). IRB contact:
Seeletso Mosweunyane (Head of Health Research
Unit, Ministry of Health and Wellness, Botswana;
phone: +267-3914467; email:
Funding: This study was supported by the US
President's Emergency Plan for AIDS Relief
(PEPFAR) through the Centers for Disease Control
and Prevention (CDC) under the terms of
cooperative agreement U01 GH000447 to SM, SG,
TM, MPH, EKY, UC, EVW, TG, MOM, RL, KEW,
ETT, JM, SL, JMM, ME, and VN. Its contents are
solely the responsibility of the authors and do not
necessarily represent the official views of the
funding agencies. SM was supported by the
Fogarty International Center and National Institute
of Mental Health, of the National Institutes of
Health under Award Number D43 TW010543. SM,
SG and LM were partially funded by Wellcome
Trust DELTAS Initiatives/Sub-Saharan Africa
Network for TB/HIV Research Excellence
(SANTHE) (107752/Z/15/Z). SDP was funded by
the National Institutes of Health under the award
K23AI091434. RW was supported by R37 AI51164
from the National Institutes of Health. The funders
had no role in the study design, data collection and
decision to publish, or in the preparation of the
manuscript. Additionally, Bennett Statistical
Consulting Inc. and Goodtables Data Consulting
provided support in the form of salaries for authors
KB and JL respectively, but did not have any
additional role in the study design, data collection
and analysis, decision to publish, or preparation of
the manuscript. The specific roles of these authors
are articulated in the `author contributions' section.
Competing interests: Kara Bennett is employed by
Bennett Statistical Consulting, Inc and Jean Leidner
was employed by Goodtables Data Consulting. The
entities above provided support in the form of
salaries for authors Kara Bennett and Jean Leidner,
but did not have any additional role in the study
design, data collection and analysis, decision to
publish, or preparation of the manuscript. This
does not alter our adherence to PLOS ONE policies
on sharing data and materials.
the Mean Duration of Recent Infection was 130 days and the False Recent Rate (FRR) was
evaluated at values of either 0 or 0.39%.
Among 12,610 individuals participating in the baseline household survey, HIV status was
available for 12,570 participants and 3,596 of them were HIV positive. LAg-Avidity EIA data
was generated for 3,581 (99.6%) of HIV-positive participants. Of 326 participants with ODn
1.5, 278 individuals were receiving ART verified through documentation and were
considered to represent longstanding HIV infections. Among the remaining 48 participants who
reported no use of ART, 14 had an HIV-1 RNA load 400 copies/mL (including 3
participants with ARVs in plasma) and were excluded, as potential elite/viremic controllers or
undisclosed ART. Thus, 34 LAg-Avidity-EIA-recent, ARV-naïve individuals with detectable
HIV-1 RNA (>400 copies/mL) were classified as individuals with recent HIV infections. The
annualized HIV incidence among 16±64 year old adults was estimated at 1.06% (95% CI
0.68±1.45%) with zero FRR, and at 0.64% (95% CI 0.24±1.04%) using a previously defined
FRR of 0.39%. Within a subset of younger individuals 16±49 years old, the annualized HIV
incidence was estimated at 1.29% (95% CI 0.82±1.77%) with zero FRR, and at 0.90% (95%
CI 0.42±1.38%) with FRR set to 0.39%.
Using a cross-sectional estimate of HIV incidence from 2013±2015, we found that at the
time of near achievement of the UNAIDS 90-90-90 targets, ~1% of adults (age 16±64 years)
in Botswana's rural and peri-urban communities became HIV infected annually.
Botswana has been hard hit by the HIV-epidemic, with the third highest HIV prevalence
worldwide among adults age 15±49, after Lesotho and Swaziland [
]. Botswana appears to be
approaching the UNAIDS ª90-90-90º HIV testing, treatment, and viral suppression targets
]. These high levels of coverage have led to significant reductions in HIV-related mortality
[1, 3±5]. In June 2016 Botswana adopted the World Health Organization (WHO)
recommendation to provide Universal Test and Treat (UTT) . The success of UTT could be measured
by reduction in HIV incidence [7±25]. Monitoring of HIV incidence is a critical tool for
assessment and evaluation the impact of HIV prevention and treatment programs.
Prospective longitudinal cohorts remain the gold standard for assessing HIV incidence.
However, this approach is time consuming, costly and prone to selection and observational
]. Biomarkers of recent HIV infection that can be detected in cross-sectional
samples represent a viable alternative to longitudinal cohort studies. Serological and molecular
biomarkers could be combined in multi-assay algorithm (MAA). An optimized MAA with high
sensitivity and specificity can discriminate between recent and established HIV infections in
cross-sectional sample [27±29][8, 9, 25, 30±36]. Recent advances in design and development of
MAA have facilitated estimating of HIV incidence in cross-sectional surveys with improved
7, 16, 22, 37
In this study, we estimated HIV incidence using a baseline cross-sectional sample from the
Botswana Combination Prevention Project (BCPP; the Ya Tsie study) [
2, 38, 39
]. BCPP is an
2 / 12
ongoing pair-matched, cluster-randomized clinical trial in 30 rural and peri-urban
communities across Botswana. The primary question of the study is reduction in the cumulative HIV
incidence as a result of combination prevention interventions that included enhanced HIV
testing and counseling (HTC) campaigns, linkage to care, antiretroviral treatment (ART),
strengthened male circumcision (MC) and enhanced prevention of mother-to-child transmission of
HIV. Between October 2013 and November 2015, we selected a random sample from 30
communities in three main geographic areas in Botswana: (1) south east, (2) north east, and (3)
central eastern region. The communities were purposively selected and proposed based on (1)
desired size, and (2) feasibility. Pairs of communities were matched by size, health services,
population age structure, and geographic location. In each community, a complete list of all
household-like structures (located within the prespecified community boundaries as defined by the
2011 Botswana Census) was obtained and geocoded using satellite imagery (Google Earth,
Mountain View, CA, USA). Based on these lists, a simple random sample of approximately 20%
of all households was drawn. At each selected household all household members were
enumerated, assessed for eligibility, and approached for participation [
]. The vast majority of
HIV-positive participants of the baseline household survey, 83%, knew their HIV status [
], 87% of them
were receiving ART [
], and 96% of those on ART were virologically suppressed [
Materials and methods
Blood specimens were collected during the BCPP baseline household survey. The HIV-positive
status of participants was based on either written documentation provided (e.g., HIV test
results, ART prescription) or HIV testing that was performed in the households according to
the Botswana national guidelines by using double positive rapid HIV testing. Participants who
self-reported not being on ART and classified as recently infected by the MAA were tested for
presence of ARV drugs in their plasma. In addition to HTC, the survey staff provided
pointof-care CD4 testing, collected blood from people living with HIV for viral load testing and
viral genotyping (venous blood was collected by phlebotomy in households), evaluated uptake
of HTC, and assessed ART and MC coverage.
Among 12,610 individuals participating in the baseline household survey, HIV status was
available for 12,570 participants and 3,596 of them were HIV positive. The study was
conducted in accordance with the Declaration of Helsinki. The study received institutional review
board approval from the Botswana Health Research Development Committee and the U.S.
Centers for Disease Control and Prevention. All participants provided written informed
consent. Participants aged 16±18 years provided written assent (with parents or guardians
providing written permission). The study is registered at ClinicalTrials.gov (NCT01965470).
Limiting Antigen Avidity assay and HIV recent infection algorithm
All plasma specimens from HIV-positive individuals who participated in the survey were
tested using the Sedia HIV-1 Limiting Antigen (LAg)-Avidity EIA (Sedia Biosciences
Corporation, Portland, OR, USA) according to manufacturer's instructions [
]. The LAg-Avidity EIA
differentiates between `recent' and long-term HIV infection. A normalized optical density
(ODn) of <1.5 was considered to represent recent infection [
]. ART status was verified
through documentation provided by the participants or testing for presence of ARV drugs in
plasma. The MAA [
] included the following steps: (1) plasma specimens from HIV-positive
individuals were tested by LAg-Avidity EIA following manufacturer's recommendations, and
ODn was calculated; (2) cases with ODn 1.5 were checked for ART status and individuals on
ART were excluded from HIV recency candidates; (3) levels of HIV-1 RNA were checked for
3 / 12
Fig 1. Multiassay algorithm applied for the cross-sectional HIV incidence estimation in Botswana Combination Prevention project.
the remaining candidates and individuals with undetectable viral load ( 400 copies/mL) were
excluded from HIV recency candidates; and (4) HIV-positive individuals with ODn 1.5 in
LAg-Avidity EIA, not taking ARV and having HIV-1 RNA >400 copies/mL were considered
recently infected with HIV. Fig 1 shows the MAA applied for the cross-sectional HIV
incidence estimation in BCPP. The MAA used the LAg-Avidity EIA in combination with testing
for ARV and HIV-1 RNA load. The final sample of recently HIV infected individuals was
identified based on HIV-positive status, ODn 1.5 in LAg-Avidity EIA, no use of ARVs and
detectable viral load (HIV-1 RNA >400 copies/mL) at the time of testing.
4 / 12
HIV-1 RNA quantification
The HIV-1 RNA load in plasma was quantified by Abbott m2000sp/Abbott m2000rt
(Wiesbaden, Germany). HIV-1 RNA >400 copies/mL was considered detectable viral load.
ARV drug testing
Plasma samples from participants who were classified as recently infected and had
undetectable viral load ( 400 copies/mL) were screened for ARV drugs by high-throughput liquid
chromatography coupled with Q-Exactive high-resolution mass spectrometry using
datadependent fragmentation and selected reaction monitoring at resolution of 17,500 [
obtain qualitative results, each specimen was compared to positive and negative controls for
each drug (abacavir, amprenavir, atazanavir, darunavir, efavirenz, emtricitabine, indinavir,
lamivudine, lopinavir, maraviroc, nelfinavir, nevirapine, raltegravir, rilpivirine, ritonavir,
saquinavir, stavudine, tenofovir, tipranavir, and zidovudine). The limit of identification ranged
from 5 to 10 ng/ml for most drugs and is presented elsewhere [
Statistical analysis and estimation of HIV incidence
The annualized HIV incidence and 95% confidence intervals (CI) were estimated based on
cross-sectional incidence assay-based methods that entail biomarkers of HIV disease
pro-gression that can distinguish recent from long-term infections [7, 14, 42±44]. Specifically, the
annual incidence was estimated as follows:
Where nR, n+, and ns represents the number of individuals who were classified as recent
infection, who were HIV-positive (including both recent and non-recent infections), and who
were uninfected, in the cross-sectional sample, respectively. O^ T is the mean duration of recent
infection (MDRI), which is the population average time spent in the `recent' state; and b^T is
thefalse-recent rate (FRR), representing the proportion of subjects who had been infected for
longer than time T (set to be 730 days) but were misclassified as recent infections. MDRI was
set to 130 days with a standard error of 5.98 days, corresponding to an ODn threshold of 1.5
]. Using HIV-1 RNA load measurement and excluding 14 virologically suppressed
individuals from recency candidates justified setting the false-recent rate (FRR) at zero [
Missing LAg-Avidity EIA test results were considered missing completely at random.
Confidence intervals were estimated taking into account of clustering of communities by applying a
design effect to both HIV prevalence and proportion of recent infections among HIV positive
individuals, implemented in the R package Inctools v. 1.0.10 . The IncTools implements
the HIV incidence calculations from cross-sectional surveys following the guidelines as
proposed by the WHO Incidence assays technical working group [23±25, 47].
In addition to estimating HIV incidence among 16±64 years old participants, we assessed
HIV incidence in a subset of younger participants in order to compare our results with other
studies in Botswana. Specifically, we estimated HIV incidence in a subset of 16±49 years old
participants (n = 10,164) including 2,798 HIV-positive and 7,366 HIV-negative individuals.
A total of 3,596 (29%) individuals from 30 communities in Botswana were HIV positive
among 12,570 adults 16±64 years old with definitive HIV status during the baseline household
5 / 12
Abbreviations: IQR, interquartile range.
a CD4 cell counts among participants not on ART; n indicates the number of participants per group.
b Percent calculated of the total number in the group.
Undetectable HIV RNA load ( 400 copies/mL), N (%)
Recent HIV-1 cases, n (%b)
survey of the BCPP from 2013 to 2105 [
]. Table 1 presents basic socio-demographic and
clinical characteristics of individuals participating in the baseline household survey. The median
(IQR) age was 40 (33±48) years. The majority of participants were females (73%). Among
HIV-positive participants, 3,581 (99.6%) were tested by the LAg-Avidity EIA.
A subset of 326 participants were classified as LAg-Avidity EIA-recent HIV infections with
ODn 1.5 (Fig 1). The documented ART status was considered as an indicator of long-term
HIV infection, and 278 of 326 participants were excluded from recency candidates due to
being on ART. A subset of 14 individuals who reported no prior use of ART (including 3 cases
with detected ARV drugs in plasma) had undetectable HIV-1 RNA load ( 400 copies/mL),
were excluded from the pool of individuals classified as recent HIV-infection [
]. Three of 14
individuals with undetectable viral load and reporting no prior ART use had ARVs in plasma
that were the first-line treatment regimens most commonly prescribed in Botswana's national
ART program at the time of sampling: two cases of zidovudin/3TC/efavirenz and one case of
zidovudin/3TC/nevirapine. Thus, 34 LAg-Avidity EIA-recent and ARV-naïve participants
with detectable HIV-1 RNA load were classified as recent HIV infections (Fig 1). The estimate
of annualized HIV incidence is 1.06% (95% CI 0.68±1.45%), assuming an FRR of zero. For a
more conservative estimate, we used the adjusted FRR at 0.39% that was determined in our
recent study in Botswana [
], and estimated the annualized HIV incidence at 0.64% (95% CI
0.24±1.04%). A higher proportion of recent infections were among young participants, less
than 30 years of age (Table 1).
All recently infected individuals (n = 34) were younger than 49 years old. The annualized
HIV incidence in the subset of 16±49 years old individuals was estimated at 1.29% (95% CI
0.82±1.77%) with FRR set to zero, and at 0.90% (95% CI 0.42±1.38%) with FRR set to 0.39%.
For comparison, two alternative published estimates of HIV incidence in Botswana including
] are presented in Table 2 along with results of this study.
HIV incidence in a population-based sample of adults 16±64 years old residing in 30
communities across Botswana was estimated at about 1% from cross-sectional sampling that occurred
6 / 12
Abbreviations. UNAIDS: Joint United Nations Program on HIV/AIDS. MAA: Multi-Assay Algorithm including viral load (400 copies/mL cut-off) and documented
HIV status. LAg-Avidity EIA: Limiting Antigen±Avidity EIA. BED±BED Incidence Assay. FRR: False Recent Rate; CI±Confidence Intervals.
in 2013±2015. Estimated HIV incidence was slightly higher (0.90±1.29%, depending on the
FRR) in a subset of younger 16±49-year-old adults. Results of our study corroborate the recent
UNAIDS estimates of HIV incidence in Botswana (0.93%) [
], and suggest a declining trend
from previously estimated HIV incidence among 15±49 year old adults in Botswana (3.5% in
2000, 2.4% in 2007 and 1.7% in 2008 [
]). Our results support the observation that new HIV
infections across sub-Saharan Africa continue to decline, although HIV incidence in Botswana
remains unacceptably high [
The strength of the current estimate of HIV incidence includes population-based random
sampling from 30 rural and peri-urban communities across the country, and application of
MAA that includes LAg-Avidity EIA, ART status, and measurements of HIV-1 RNA in all
HIV-positive participants. Limitations of our study include MAA that is reliant upon the ART
status and the uncertainty arising from estimates of corresponding FRR and MDRI. In our
previous studies, we have also found similar estimates of MDRI using an MAA with ART
status and viral load [
]. Individuals on ART were excluded from recency candidates, because
being on ART was interpreted as an indicator of longstanding HIV infection. This approach
worked well in the era of CD4-driven initiation of ARV therapy, and was in line with the
Botswana HIV treatment guidelines at the time of sampling, 2013 to 2015. In June 2016
Botswana introduced a new national policy ªTreatment for Allº, that is, initiating ART as soon
as possible regardless of CD4+ T-cell counts . The ongoing scaling up of this national policy
means that ART status cannot be used as exclusion criteria for estimation of HIV recency in
future studies. Novel cross-sectional assays and MAA independent of ART status are needed
to address this issue.
Self-reported ART status could be considered one of the study limitations. Although ART
status was verified through documentation among those who self-reported to be on ART,
there is an uncertainty due to possible undisclosed ART use among those who self-reported
not to be on ART. To address this limitation we performed ARV drug testing in plasma
among those who had undetectable levels of HIV-1 RNA and reported no ART use. In fact, we
found triple ARV drugs in 3 out of 14 cases. Using viral load threshold could minimize
uncertainty of self-reported status. In fact, 3 cases with ARV drugs in plasma were excluded based
on low levels of HIV-1 RNA.
While we used a Botswana-specific FRR from our previous study [
], it was estimated in a
cohort sampled approximately a decade before sampling in the current study. We speculate
that FRR in Botswana could be decreasing over time and could be lower than the 0.39% used
for conservative estimates of HIV incidence in this study. The extent to which regional FRRs
are changing over time remains unknown. The scale up of national ART programs could affect
FRR estimates. Since ART guidelines have been changing, a greater proportion of individuals
7 / 12
are initiating treatment sooner, more frequently soon after HIV diagnosis. This means the
increasing ART coverage could reduce FRR. In this manuscript, the MAA algorithm included
ARV drug testing leading to reduction of FRR to zero. However, uncertainly remains as to
whether FRR can be eliminated . The upper range of FRR then is FRR without drug
tracing, as we determined in our previous study in Botswana [
The relatively high estimated HIV incidence that we found (~1%) despite high levels of
HIV testing, treatment, and viral suppression may reflect several factors. First, the impact of
widespread ART on HIV incidence may take several years to be realized. In addition, the
~30% of HIV-infected individuals with detectable viremia [
] could yield such high HIV
incidence in the setting of very high HIV prevalence (and these individuals could have different
HIV risk behavior, compared with those with viral suppression on ART). Our findings
highlight the importance of targeted interventions to reach individuals who have not yet sought
HIV testing or treatment services.
In summary, using cross-sectional sampling and MAA based on LAg-Avidity EIA, ART status
(either documented or by testing ARV drugs in plasma) and HIV-1 RNA measurements, we
estimated the HIV incidence in 30 rural and peri-urban Botswana communities in 2013±2015
at about 1%. A higher proportion of recent infections were among participants less than 30
years of age. A reduction from this relatively high estimated HIV incidence may take several
years to be realized despite the impact of widespread ART and other on-going interventions.
Targeted interventions are required to reach individuals who have not yet sought HIV testing
or treatment services.
We thank the study participants. We are grateful to the entire BCPP staff including the field
study teams for making this study a success. We thank the BCPP team members for their
contribution to this study: Ngozana Seonyatseng, Tumalano Sekoto Pharatlhatlhe, Vinoliah
Simon, Rona Letlhogile, Atang Mbikiwa, Kutlo Manyake, Neo Mogowa, Moemedi
Tshwenyana, Kagiso Watema, Chebukani Nkobodo, Phelimon Pong Sebogodi, Thabani Ncube,
Dineo Mongwato, Coulsen Kgathi, Thuso Mokane, Kutlwano Mukokomani, Mompati
Mmalane, Ria Madison, Chloe Auletta-Young, Botswana Harvard HIV Reference Laboratory Staff,
Data Management Centre Staff, and field laboratory assistants. We thank Lendsey Melton for
excellent editorial assistance. We thank Michelle Roland for helpful critique and discussion.
We would like to thank Reshma Kassanjee, Alex Welte and Eduard Grebe for useful
discussions in the application of cross-sectional methods and use of IncTools.
Conceptualization: Sikhulile Moyo, Molly Pretorius Holme, Eric Tchetgen Tchetgen, Shahin
Lockman, Joseph M. Makhema, Max Essex, Vlad Novitsky.
Formal analysis: Sikhulile Moyo, Simani Gaseitsiwe, Vlad Novitsky.
Funding acquisition: Shahin Lockman, Max Essex.
Investigation: Sikhulile Moyo, Simani Gaseitsiwe, Terence Mohammed, Molly Pretorius
Holme, Rui Wang, Kenanao Peggy Kotokwe, Corretah Boleo, Lucy Mupfumi, Etienne
Kadima Yankinda, Unoda Chakalisa, Erik van Widenfelt, Tendani Gaolathe, Mompati O.
8 / 12
Mmalane, Scott Dryden-Peterson, Madisa Mine, Refeletswe Lebelonyane, Kathleen E.
Wirth, Janet Moore, Shahin Lockman, Joseph M. Makhema, Max Essex, Vlad Novitsky.
Project administration: Simani Gaseitsiwe, Etienne Kadima Yankinda, Unoda Chakalisa,
Tendani Gaolathe, Mompati O. Mmalane, Refeletswe Lebelonyane, Janet Moore, Joseph M.
Supervision: Simani Gaseitsiwe, Terence Mohammed, Molly Pretorius Holme, Lucy
Mupfumi, Etienne Kadima Yankinda, Unoda Chakalisa, Erik van Widenfelt, Tendani Gaolathe,
Mompati O. Mmalane, Kathleen E. Wirth, Eric Tchetgen Tchetgen, Kathleen Powis, Janet
Moore, Shahin Lockman, Joseph M. Makhema, Max Essex, Vlad Novitsky.
Writing ± original draft: Sikhulile Moyo, Vlad Novitsky.
Writing ± review & editing: Sikhulile Moyo, Simani Gaseitsiwe, Terence Mohammed, Molly
Pretorius Holme, Rui Wang, Kenanao Peggy Kotokwe, Corretah Boleo, Lucy Mupfumi,
Etienne Kadima Yankinda, Unoda Chakalisa, Erik van Widenfelt, Tendani Gaolathe,
Mompati O. Mmalane, Scott Dryden-Peterson, Madisa Mine, Refeletswe Lebelonyane, Kara
Bennett, Jean Leidner, Kathleen E. Wirth, Eric Tchetgen Tchetgen, Kathleen Powis, Janet
Moore, Shahin Lockman, Joseph M. Makhema, Max Essex, Vlad Novitsky.
9 / 12
02/28. https://doi.org/10.1097/QAD.0b013e3282f2a960 00002030-200802190-00009 [pii]. PMID:
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