Download Early Warning Indicators for HIV Drug Resistance

MAJOR ARTICLE
HIV/AIDS
Early Warning Indicators for HIV Drug
Resistance in Adults in South Africa at 2 Pilot
Sites, 2008–2010
Nomathemba M. Dube,1,2,3 Khin S. Tint,3 and Robert S. Summers1,4
1
Medunsa National Pharmacovigilance Centre, Medunsa Campus, University of Limpopo, Pretoria, 2Centre for HIV/STIs, National Institute for
Communicable Diseases of the National Health Laboratory Services, 3South African Field Epidemiology and Laboratory Training Programme, National
Institute for Communicable Diseases of the National Health Laboratory Services, Johannesburg, and 4Department of Pharmacy, Faculty of Health Sciences,
Medunsa Campus, University of Limpopo, Pretoria, South Africa
(See the Editorial Commentary by Rossouw on pages 1615–7.)
Background. Approximately 5.2 million people in South Africa were infected with human immunodeficiency
virus (HIV) by the year 2010, with just over 30% initiated on highly active antiretroviral therapy by 2011. With such
numbers involved, the potential for the emergence of HIV drug resistance (HIVDR) is high. This study piloted early
warning indicators (EWIs) for HIVDR at 2 clinics in South Africa.
Methods. HIV-infected individuals aged ≥15 years and receiving antiretroviral drugs were enrolled into this
cohort study between March 2008 and February 2010. All analyses were performed using the 2012 World Health
Organization EWI score card.
Results. A total of 1144 subjects were enrolled. Clinic A reached the target for 2 of the 5 EWIs but missed the
desired target for on-time pill pickup, pharmacy stockouts, and virological suppression. Clinic B reached the target
for 1 of 4 EWIs, namely, dispensing practices. Targets were missed for on-time pill pickup, retention in care, and
virological suppression. Pharmacy stockouts could not be calculated at this site.
Conclusions. Actual performance against the levels that the pilot sites should reach to minimize HIVDR was
low. Improvements in follow-up procedures, internal adherence support, monitoring for drug stockouts, and adherence are all aspects that need support to ensure that all records are complete. This pilot study may help to inform the
South African government as EWI monitoring is implemented.
Keywords.
HIV; early warning indicators; drug resistance; antiretroviral medicines; pharmacovigilance.
By 2010, 5.2 million people in South Africa were infected
with human immunodeficiency virus (HIV), representing approximately 80% of all HIV-infected persons in
low and middle-income countries [1, 2]. Scale-up of antiretroviral therapy (ART) in South Africa has been impressive, with >920 000 individuals receiving ART by
2009 and an additional 300 000 initiated on treatment
Received 29 August 2013; accepted 22 January 2014; electronically published 27
February 2014.
Correspondence: Nomathemba Michell Dube, MSc (Med), MPH, Medunsa
National Pharmacovigilance Centre, University of Limpopo, PO Box 172, Medunsa,
Pretoria, South Africa ([email protected]).
Clinical Infectious Diseases 2014;58(11):1607–14
© The Author 2014. Published by Oxford University Press on behalf of the Infectious
Diseases Society of America. All rights reserved. For Permissions, please e-mail:
[email protected].
DOI: 10.1093/cid/ciu109
between 2010 and 2011. This number will increase further as South Africa rolls out ART to individuals with
CD4 cell counts of <350 cells/µL and aims to initiate at
least 80% of eligible patients on ART, with 70% alive and
on treatment 5 years after initiation as stated in the 2012–
2016 National Strategic Plan [3, 4]. The use of ART in the
public sector since 2004 has been guided by the National
Department of Health’s Operational Plan for Comprehensive HIV and AIDS Care, Management, and Treatment [5], revised in 2010 [6]. This plan states that all new
patients needing treatment must be initiated on first-line
antiretroviral (ARV) regimens. The recommended South
African first-line regimens contain stavudine (excluded
from 2010 guideline revision), zidovudine, or tenofovir
(introduced in 2010 guideline revision) plus lamivudine
and either efavirenz or nevirapine.
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Unfortunately, most of these life-saving medicines have adverse effects that cause some patients to adhere poorly to treatment or to discontinue therapy altogether [7–9]. Treatment
interruptions that include late ARV pickup and drug stockouts
may result in the selection of drug-resistant HIV [10]. Poor patient care, reflected by inappropriate prescribing or dispensing
practices, inappropriate switching of ARVs, and a high HIV
RNA level (>1000 copies/mL) at 12 months, may also contribute to the risk of the emergence of population-level HIV drug
resistance (HIVDR) [10].
In 2006, the World Health Organization (WHO) formulated
clinic-based HIVDR early warning indicators (EWIs) [10].
Since 2004, 2017 clinics in 50 countries have monitored for
EWIs. Of 907 clinics monitored in Africa until 2010, 74%
met the target of 100% of subjects receiving ARVs in compliance with national or WHO guidelines, 61% retained subjects
on appropriate therapy 12 months after initiation, 15% had subjects pick up ARVs on-time, and 96% had the targeted number
of subjects suppressing their viral load (VL) at 12 months [10].
Sigaloff et al [11] have published a study investigating EWIs for
population-based monitoring of HIVDR at 13 sentinel sites located in 6 African countries, including South Africa. However,
country-specific performances of EWIs were not highlighted
[11]. Our study aimed to assess the feasibility of EWI monitoring in South Africa by piloting the analysis from routinely collected data at 2 public sector sites.
METHODS
Five WHO-suggested EWIs were monitored following 2012
guidance from the report of the Early Advisory Indicator
Panel meeting [12]. Data to calculate EWIs were sampled
and abstracted from a pharmacovigilance cohort surveillance
study database established in 2006 with the main aim of monitoring for adverse drug reactions in subjects taking ARV
drugs. All subjects were HIV-infected, aged ≥15 years, and receiving ARVs at 1 of 2 government-owned pilot sites in South
Africa. Clinics A and B, situated in Gauteng and Limpopo
provinces, respectively, were selected for inclusion into the
surveillance study based on the large population size serviced,
which reflected patient demographics in each province. Also,
adequate human resources were dedicated to the pharmacovigilance program at these clinics with a minimum of 2 full-time
medical practitioners assigned to the treatment program.
Subject Enrollment Into the Surveillance Study
On-site coordinators used systematic random sampling to enroll patients into the study using the following formula: [total
number of patients presenting at the clinic each day / number
of patients that coordinator can handle per day = select every
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Sampling of Subjects for EWI Calculations
The 2012 WHO sampling guidance was followed to provide
generalizable results to the clinics from which data were abstracted. The 95% confidence interval (CI) according to this
sampling guidance was ±7% [10]. The sample size was calculated based on the total number of patients initiated on ART at
each site at 12-month intervals between March 2008 and February 2010 inclusive.
Data Management and Analysis
Data capturers at the Pharmacovigilance Centre entered data
into a Structured Query Language database. Data from March
2008 and February 2010 were abstracted using the WHO’s
2012 data abstraction tool and imported into Epi Info 3.5.1
(Centers for Disease Control and Prevention) [13], from
which validation checks were performed. The data were verified
by comparing them with the original record and, where possible, with the SOZO database, which houses patient records at
many public ARV treatment sites in the country.
Results were reported using the EWI scorecard [12]. Details
of the EWIs that were calculated in this study are shown in
Table 1.
Ethical Approval
Study Design and Study Setting
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nth patient (usually every 10th–15th patient)]. Patients who
agreed to participate signed an informed consent form and
were not given any preferential treatment at the clinic from
which they were enrolled.
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The project was approved by the Medunsa Research Ethics
Committee at the University of Limpopo.
RESULTS
Profiles of Pilot Sites
Profiles of the pilot sites were compiled to support interpretation of EWI results (Table 2). Although both pilot sites began
operating in June 2004, clinic A initiated 64.3% (1413/2196)
more subjects on ART during the study period than clinic
B. The staff-to-patient ratio at the 2 clinics was noticeably different (1:515 at clinic A and 1:129 at clinic B). A total of 1144
subjects consented to be enrolled into the pharmacovigilance
study between March 2008 and February 2010. Of the 1144 subjects enrolled, 542 (47.4%) were from clinic A and 602 (52.6%)
from clinic B. More females were enrolled (777/1144 [67.9%])
than males (367/1144 [32.1%]).
Despite the absence of procedures to follow up with patients
who missed scheduled appointments at clinic B, adherence support was available. This support was provided by an external organization, unlike that provided by internal counselors and
nurses at clinic A. Self-confessed or suspected nonadherent
Table 1. Early Warning Indicators Used to Assess HIV Drug Resistance Prevention at 2 Pilot Sites, March 2008–February 2010
2012 WHO Early Warning Indicators
EWI
Indicator (WHO
Targets)
WHO Definition [8]
Numerator
Denominator
1
On-time pill pickup
(Red: <80%; Amber:
80%–90%; Green:
≥90%)
Percentage of patients who
picked up prescribed ARV
drugs on time
All patients enrolled into the study
who picked up all their prescribed
ARV drugs at the first drug pickup
after HAART initiation on the
scheduled date. (A grace period
of 2 days before and after
scheduled drug pickup date was
given for this calculation.)
All patients enrolled into the study
who initiated ART between
March 2008 and February 2010
inclusive. This value excluded
patients known to be deceased
and transferred out between
baseline and first scheduled pill
pickup after initiation.
2
Retention in care
(Red: <75%; Amber:
75%–85%; Green:
≥85%)
Percentage of patients
known to be alive and on
treatment 12 mo after ART
initiation
All patients enrolled into the study
that are alive and on treatment 12
mo after ART initiation.
3
Pharmacy stockouts
(Red: <100%; Green:
100%)
Percentage of months in a
designated year in which
there were no ARV drug
stockouts
Total number of months in a
designated year, ie, March 2008–
February 2009 and March 2009–
February 2010, in which there
were no stockout days of any ARV
drug as recorded on pharmacy
stock cards.
All patients enrolled into the study
who initiated ART between
March 2008 and February 2010.
This value excluded patients
known to be transferred out
before their 12 mo date.
12 mo.
4
Dispensing practices
(Red: >0%; Green:
0%)
Percentage of patients
prescribed or picking up
mono- or dual ARV therapy
All patients enrolled in the study that
were initiated on a regimen
consisting of 1 or 2 ARV drugs.
All patients enrolled into the study
who initiated ART between
March 2008 and February 2010.
5
Virological suppression
(Red: <70%; Amber:
70%–85%; Green:
≥85%)
Percentage of patients
receiving ART at the site
after the first 12 mo of ART
whose viral load is <1000
copies/mL
All patients enrolled into the study
who are still taking ART at 12 mo
and who have a viral load of
<1000 copies/mL done between
11–15 mo after ART initiation.
All patients enrolled into the study
who initiated ART between
March 2008 and February 2010.
This value excluded patients
known to be transferred out
before their 12 mo date or
patients with viral loads done <9
mo or >15 mo after initiation.
The score-card colors indicate performance levels reached at the facility for a particular indicator. “Red” indicates poor performance (below desired level); “Amber”
is for fair performance (not yet at desired level); and “Green” reflects excellent performance (achieving desired level).
Abbreviations: ART, antiretroviral therapy; ARV, antiretroviral; EWI, early warning indicator; HAART, highly active antiretroviral therapy; WHO, World Health
Organization.
patients at clinic B were identified and referred to this external
organization for support. The onus was upon the subject to visit
this organization to access its services. An ARV pharmacy was
located within each clinic. Procedures to monitor report and act
on any drug stockouts that occurred were in place at both
pharmacies.
Although free services were provided at both clinics, subjects
visiting clinic B had to travel longer distances (up to 32 km),
using more inconvenient transportation (buses), and wait for
longer periods (up to 45 minutes) to pick up medication from
the pharmacy compared with subjects who attended clinic
A. Most patient records at clinic A were captured on SOZO,
whereas those at clinic B were paper-based. More than 60% of
VL results at clinic B were missing from subject files.
Overall, 99.7% (1141/1144) of subjects enrolled in the pharmacovigilance study were initiated on first-line ARV regimens
as stipulated by the South African national guidelines of 2010
(Figure 1). More than 80% of subjects at both clinics were initiated on regimen 1a (Figure 1). Twenty-nine of the 1144 subjects (2.5%) were transferred out during the first 12 months of
treatment. Of the remaining subjects, 77.0% (858/1115) were retained on first-line regimens 12 months after initiation. Clinic A
retained a higher percentage of subjects on first-line regimens
(87%) compared with clinic B (68%) (Figure 2).
2012 Early Warning Indicators
EWI 1: On-time Pill Pickup
After accounting for deaths (24/1144) and transfers out (1/1144)
between the baseline and first scheduled pill pickup dates after
initiation, 3.1% (35/1119) of subjects did not return to collect
their ARV medicines after their baseline pickup. Overall, 75.6%
(846/1119) collected their medication on time (ie, within 2 days
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Table 2. Pilot Site Profiles of Clinics A and B
Pilot Site
Characteristic
Clinic A (%)
Clinic B (%)
Clinic statistics
Date when facility began providing
ARVs
June 2004
June 2004
3609
2021
2196
1022
No. of patients initiated on ART at site
Year 1 (March 2008–February 2009)
1588
1174
No. of patients enrolled into study
Year 1 (March 2008–February 2009)
Year 2 (March 2009–February 2010)
542 (15.0)
319 (15.8)
602 (27.4)
324 (31.7)
Year 2 (March 2009–February 2010)
223 (14.0)
278 (23.7)
7
17
No. of ARV prescribing staff
No. of ARV initiation staff
3
3
5
5
No. of ARV dispensing staff
(pharmacists)
Staff-to-patient ratio
2
3
1:515
1:129
Present
Yes. Internal support groups present
Absent
Yes. External support groups present
Staff statistics
No. of HIV care providers (nurses,
doctors, physicians, clinical
officers)
Patient support information
Procedures to follow-up patients
Adherence support provided?
General information
Procedures for ARV drug shortages
Monitoring
Bin cards
Stock-cards
Drug controller
Pharmacy store manager
Use alternative drug dosages, eg, 2 × 125 mg
instead of 1 × 250 mg or borrow from
neighboring clinics
Issue <1 month’s supply and request patient to
return for drug collection again or borrow from
neighboring clinics
2–20 km
2–32 km
Public taxis
Buses
Waiting times for routine ART
appointment at clinic (minimummaximum)
60–120 min
Not stipulated
Waiting times for ART drug pickups
(minimum-maximum)
30–35 min
40–45 min
Person to report to
Managing drug stockouts
Distance traveled by patients to clinic
(minimum-maximum)
Most common means of transport
used
Abbreviations: ART, antiretroviral therapy; ARV, antiretroviral; HIV, human immunodeficiency virus.
of their scheduled pickup date). Those who picked up their pills
late collected their medication after a median of 8.15 months (interquartile range [IQR], 6.15–12.45 months) after treatment initiation at clinic A and 9.56 months (IQR, 6.09–13.51 months) at
clinic B. According to the EWI score cards, both sites were in the
red zone (<80% on-time pill pickups) and exhibited poor performance for this indicator (Figure 3).
Approximately 7% (39/542) of subjects at this clinic were lost
to follow-up and 3.1% (17/542) were dead within the first 12
months of treatment. Due to high rates of loss to follow-up
(125/602 [31.3%]) and deaths (31/602 [5.1%]) during the first
12 months after initiation at clinic B, 73.6% (435/591) of subjects were retained in care there (amber zone, fair performance)
(Figure 3).
EWI 2: Retention in Care
Clinic A retained 89.3% (468/524) of subjects in care 12 months
after initiation (≥85%, excellent performance; Figure 3).
EWI 3: Pharmacy Stockouts
At clinic A, drug stockouts were experienced at the main hospital pharmacy that supplies the ARV clinic pharmacy. The main
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(4 months), nevirapine (3 months), lamivudine (2 months), stavudine (2 months), and tenofovir (1 month). Clinic A was not
directly affected by these stockouts because the main hospital
pharmacy reordered stock before the clinic pharmacy ran out
of the medicines they had.
Clinic B monitored for drug stockouts using stock-cards.
These cards could not be obtained from the pharmacy. This indicator was therefore not calculated for this facility.
Figure 1. Highly active antiretroviral therapy initiation regimens of subjects enrolled into the pharmacovigilance surveillance study, March 2008–
February 2010 (N = 1144). *Drug combination dependent on prescriber.
First-line regimens: 1a (stavudine, lamivudine, efavirenz), 1b (stavudine,
lamivudine, nevirapine), 1c (zidovudine, lamivudine, efavirenz), 1d (zidovudine, lamivudine, nevirapine), A1 (tenofovir, lamivudine, efavirenz). Second-line regimen: 2 (zidovudine, didanosine, lopinavir/ritonavir).
Abbreviations: ART, antiretroviral therapy; NS, nonstandard regimen.
hospital pharmacy for clinic A was in the red zone (<100%, poor
performance) for this indicator and scored an average of 54.2%
due to stockouts experienced in 11 of the 24 months observed in
this study (March 2008 to February 2009: 5 of 12 months;
March 2009 to February 2010: 6 of 12 months). In 9 of these
11 months, drugs out of stock (≥1 drug per month) were
those that are part of first-line regimens, namely, efavirenz
EWI 4: Dispensing Practices
Both pilot sites initiated all study subjects on highly active antiretroviral therapy (HAART) as recommended by the South
African initiation guidelines (Figure 3) as opposed to monoor dual therapy. Both clinic A and B scored in the green zone
(0%, excellent performance) for this indicator.
EWI 5: Virological Suppression
In clinic A, 11- to 15-month VL results were available for 90.0%
(476/529) of subjects. Of the subjects with no VL result, 5.7%
(3/53) of them died within the first 12 months of initiating
HAART and therefore had no VL recorded. Reasons why VLs
were missing for the remaining subjects at clinic A are unknown. In clinic B, more than half of the subjects (62.2%
[367/590]) had missing VLs, of whom 6.8% (25/367) had
died within 12 months of initiation.
Of the subjects with 11- to 15-month VL results available,
clinic A achieved an 81.5% (388/476) VL suppression rate
(amber zone) whereas the rate at clinic B was 65.9% (147/
223). Of all the subjects who achieved VL suppression, 96.4%
(516/535) had been on first-line ARV regimens since ART
Figure 2. Flow chart illustrating subjects retained on first-line therapy at clinics A and B, March 2008–February 2010. Abbreviation: LTFU, lost to
follow-up.
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Figure 3. Yearly performance of human immunodeficiency virus drug resistance early warning indicators at each pilot site, March 2008–February 2010.
Abbreviations: ART, antiretroviral therapy; EWI, early warning indicator; N/A, not available.
initiation. Our findings show that an association exists between
retention on first-line regimens for at least 12 months after initiation and VL suppression at 11–15 months (χ2 = 22.19, P =
.000). Subjects receiving ARV medicines at clinics A and B
who remained exclusively on first-line regimens for the first
12 months after initiation were 1.28 times more likely to achieve
VL suppression rates of <1000 copies/mL between 11 and
15 months after initiation than subjects whose regimens were
non-first-line within the first 12 months of initiation (95% CI,
1.21–2.36).
Compliance With HIVDR EWIs, by Year
The number of subjects picking up treatment on-time improved
at both sites from the year 2008–2009 to 2009–2010 (Figure 3).
Clinic A retained more subjects in care in both years compared
with clinic B. In clinic B, a decrease in subjects retained in care
was observed due to a surge in subjects lost to follow-up between 2008–2009 and 2009–2010, that is, 16.1%–27.0%
(χ2 = 10.51, P = .001). Although stockouts increased at clinic
A in 2009–2010, neither clinic A or B dispensed mono- or
dual therapy. Despite both facilities having missing VLs and
not reaching the desired VL suppression target (≥85%), the
proportion of subjects achieving VL suppression at both sites
increased in 2009–2010 (Figure 3).
DISCUSSION
Monitoring EWIs of HIVDR provides information on the functioning of ART clinics and programs. The present pilot study
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was the first of its kind in the country and aimed to assess the
feasibility of the use of EWIs in this setting.
Despite the fact that both pilot sites initiated the majority of
their subjects on first-line ARV regimens, some subjects were
initiated on other HAART drug combinations. The reason for
initiating these subjects on these drug combinations may have
been the anticipation of certain toxicities such as exacerbated
peripheral neuropathy if, for example, subjects with HIV-related
peripheral neuropathy were initiated on first-line drug combinations containing stavudine.
Clinic EWI performance seemed to be inversely related to
staff-to-patient ratio. Despite a lower staff-to-patient ratio at
clinic A compared with clinic B, clinic A performed better for
all EWIs. This result has led us to believe that interventions for
patient care in place at clinics had a more direct influence on
EWI performance than the staff-to-patient ratio. It is worth
conducting a case series study to investigate if the availability
of follow-up procedures as well as internal adherence support
at clinic A contributed to excellent subject retention there, compared with fair performance at clinic B where follow-up services
are not available and adherence support is external.
Although the national guidelines require patients to attend 3
counseling sessions before HAART initiation, in particular, including education on the importance of adherence, both clinics
still had subjects picking up medication late on the first visit
after the baseline pickup and some not returning at all after
baseline pickup. This situation suggests that more must be
done at the clinics to strengthen adherence support. As a result
of this finding, research to investigate reasons for treatment
interruption is under way. This research will also determine if
distance from the clinic, mode of transport used, and long waiting times at clinics are contributing factors to poor on-time pill
pickup. Two studies in South Africa, by Maskew et al and Wang
et al , investigated factors that contributed to treatment interruptions in their cohorts [14, 15]. Financial difficulties in obtaining treatment (eg, transport costs) and pregnancy at ART
initiation were significant contributors. Studies by Bisson et al
and El-Khatib et al concluded that pharmacy refill adherence
estimates are as accurate as CD4 counts for the identification
of patients’ risk of virological and immunologic failure before
the event occurs [16, 17]. It is therefore crucial to address
poor on-time pill pickup at the clinics to prevent treatment failure. For future EWI monitoring, introducing a CD4 count EWI
may be a more accurate measure for HIVDR emergence than
on-time pill pickup.
Efforts were made to obtain stock-card records from clinic
B. Due to restrictions to the access of stock cards at the facility;
pharmacy stockouts could not be calculated. ARV stockouts are
an ongoing challenge in South Africa. Stockouts experienced in
the hospital A pharmacy were mainly of drugs that constitute
first-line regimens. With the country using approximately
80% of worldwide ARV drug supplies (Professor Steven Miller,
personal communication), failure to strengthen ARV drug forecasting, procurement, and distribution, coupled with the scaleup of ARV rollout, will result in more treatment interruptions
and rapid emergence of HIVDR. The National Department of
Health is urgently trying to install a countrywide computer software system that will link healthcare facilities with drug depots
and suppliers to relieve ongoing essential drugs stockouts [18].
We believe that ability to prevent drug stockout in clinic A contributed directly to EWI performance levels. At clinic A, the use
of bin cards and the availability of a drug controller at the main
hospital pharmacy alerted the pharmacists to timely reorder.
Besides, dispensing practices were excellent for clinic A because
all drug combinations were available to give triple therapy. Although clinic A has lower staff-to-patient ratio, it addressed the
challenges of maintaining ARV supply as shown in the study
done in Malawi [19]. Although pill pickup by subjects was
not timely, virological suppression was fair. This is in consensus
with Harrigan et al, who showed that when compared to subjects with relatively high (80%–90%) and essentially perfect
(≥95%) refill estimates, those at low risk of harboring HIVDR
mutations are those with low drug refill estimates (0%–20%)
[20]. Lack of funds to hire a data entry clerk is the main reason
why the record system at clinic B is paper-based. This system
resulted in the majority of VL results disappearing before they
could be entered into the subjects’ files. In addition to missing
VLs, the number of subjects achieving the desired level of VL
suppression at clinic B was very low. The reason for this result
may have been low levels of patient retention on first-line
regimens for ≥12 months after initiation. This factor may
have been attributed to by external adherence counseling,
which may not have been easily accessible at clinic B. This aspect may need to be investigated further.
A major limitation to this study was the unavailability of
stockout data from clinic B. This situation prevented us from
obtaining a true reflection of drug supply continuity there.
The South African government intends to introduce EWI
monitoring at public-sector ART treatment sites and to integrate EWI data abstraction into routine reporting of all ART
clinics. Results of this pilot study may provide valuable information of weaknesses in the current system that may be improved
before EWI monitoring is implemented in the country as a whole.
Most levels of performance, as measured by EWIs, that the
pilot sites should be reaching to minimize HIVDR were not
achieved. Clinic A was on target for retention of subjects in
care at 12 months as well as dispensing practices, whereas clinic
B met the target for dispensing practices only. These results emphasize 3 things: (1) the importance of implementing patient
follow-up coupled with internal ongoing drug adherence support to ensure patients understand the dangers of treatment
interruptions; (2) the need for continuous training and supervision support of health practitioners to prevent premature
drug switches; and (3) the necessity for operational research
to strengthen health systems such as the ability to prevent stockouts and establishing an electronic database at health facilities.
In conclusion, EWI monitoring is feasible in South Africa;
however, the National Department of Health needs to ensure
that the electronic data capturing systems are available at all facilities and continuously updated before EWI results can accurately reflect site performance. Additionally, information
regarding drug stock must be included in the electronic databases and made available on request, as the availability of drug
stock is one of the key factors in preventing HIVDR.
Notes
Acknowledgments. Naome Mberi assisted with data abstraction. Michael R. Jordan, Lynn Morris, and Gillian Hunt reviewed this manuscript.
The Foundation for Professional Development contributed to the development of the database.
Author contributions. N. M. D., R. S. S., and K. S. T. were involved in
the conceptualization of this study. N. M. D. was involved in the study design, statistical analysis, results interpretation, and preparation of this report.
All authors were involved with revision of this report.
Disclaimer. The contents of this manuscript are solely the responsibility of the authors and not of the funding agencies.
Financial support. This work was supported by the South African Field
Epidemiology and Laboratory Training program funded by the Centers for
Disease Control and Prevention (3U2GPS001328-04) and the South African
National Department of Health.
Potential conflicts of interest. All authors: No reported conflicts.
All authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
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References
1. Statistics South Africa. Mid-year population estimates 2010. Available
at: http://www.statssa.gov.za/publications/P0302/P03022010.pdf.
Accessed 12 April 2012.
2. United Nations Joint Programme on HIV/AIDS. AIDS at 30: nations at
a crossroad. Available at: http://www.unaids.org/unaids_resources/
aidsat30/aids-at-30.pdf. Accessed 17 May 2012.
3. World Health Organization. Rapid advice: antiretroviral therapy for
HIV infection in adults and adolescents. Available at: http://www.
who.int/hiv/pub/arv/advice/en/. Accessed 18 May 2012.
4. National Strategic Plan in HIV, STIs and TB. Available at: http://www.
doh.gov.za/docs/stratdocs/2012/NSPfull.pdf. Accessed 21 October
2013.
5. South African Department of Health. Operational plan for comprehensive HIV and AIDS care, management, and treatment for South Africa.
2003. Available at: http://www.gov.za/documents/download.php?
f=164714. Accessed 21 October 2013.
6. South African National Antiretroviral Treatment Guidelines,
2010. Available at: http://www.uj.ac.za/EN/CorporateServices/ioha/
Documentation/Documents/ART%20Guideline.pdf. Accessed 9 May
2012.
7. Montessori V, Press N, Harris M, Akagi L, Montaner JSG. Adverse effects of antiretroviral therapy for HIV infection. Can Med Assoc J 2004;
170:229–38.
8. Reust CE. Common adverse effects of antiretroviral therapy for HIV
disease. Am Fam Physician 2011; 83:1443–51.
9. Dahab M, Kielmann K, Charalambous S, et al. Contrasting reasons for
discontinuation of antiretroviral therapy in workplace and public-sector
HIV programs in South Africa. AIDS Patient Care STDs 2011; 25:53–9.
10. World Health Organization. HIV drug resistance early warning indicators: World Health Organizations to monitor HIV drug resistance prevention at antiretroviral treatment sites. Available at: http://www.unaids.
1614
•
CID 2014:58 (1 June)
•
HIV/AIDS
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
org.br/biblioteca/links/OPAS-OPS/OPAS%2014.pdf. Accessed 25 July
2011.
Sigaloff KCE, Hamers RL, Menke J, et al. Early warning indicators for
population-based monitoring of HIV drug resistance in 6 African
Countries. Clin Infect Dis 2012; 54(suppl 4):S294–99.
World Health Organization. Assessment of the World Health
Organization HIV Drug resistance early warning indicators: report of
the Early Warning Indicator Advisory Panel Meeting, Geneva, Switzerland, 2011. Available at: http://apps.who.int/iris/bitstream/10665/
75186/1/9789241503945_eng.pdf. Accessed 17 September 2012.
Epi Info [computer program]. Version 3.5.1. Atlanta, GA: Centers for
Disease Control and Prevention, 2008.
Maskew M, MacPhail P, Menezes C, Rubel D. Lost to follow up—
contributing factors and challenges in South African patients on antiretroviral therapy. S Afr Med J 2007; 97:5.
Wang B, Losina E, Stark R, et al. Loss to follow-up in a community clinic
in South Africa—roles of gender, pregnancy and CD4 count. S Afr Med
J 2011; 101:253–257.
Bisson GP, Gross R, Bellamy S, et al. Pharmacy refill adherance compared with CD4 count changes for monitoring HIV-infected adults
on antiretroviral therapy. PLoS Med 2008; 5:e109.
El-Khatib Z, Katzenstein D, Marrone G, et al. Adherence to drug-refill is
a useful early warning indicator of virologic and immunologic failure
among HIV patients on first-line ART in South Africa. PLoS One
2011; 6:e17518.
Bateman C. Drug stock-outs: inept supply-chain management and corruption. S Afr Med J 2013; 103:600–602.
Schouten EJ, Jahn A, Ben-Smith A, et al. Antiretroviral drug supply
challenges in the era of scaling up ART in Malawi. J Int AIDS Soc
2011; 14(suppl 1):S4.
Harrigan PR, Hogg RS, Dong WWY, et al. Predictors of HIV drugresistance mutations in a large antiretroviral-naive cohort initiating triple antiretroviral therapy. J Infect Dis 2005; 191:339–47.