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No differences in clinical outcomes with the addition of viral load testing to CD4 cell count monitoring… Okoboi, Stephen; Ekwaru, Paul J; Campbell, James D; Egessa, Aggrey; King, Racheal; Bakanda, Celestin; Muramuzi, Emmy; Kaharuza, Frank; Malamba, Samuel; Moore, David M Feb 1, 2016

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RESEARCH ARTICLE Open AccessNo differences in clinical outcomes withthe addition of viral load testing to CD4cell count monitoring among HIV infectedparticipants receiving ART in rural Uganda:Long-term results from the Home BasedAIDS Care ProjectStephen Okoboi1*, Paul John Ekwaru2, James D. Campbell3, Aggrey Egessa1, Racheal King4, Celestin Bakanda1,Emmy Muramuzi5, Frank Kaharuza5, Samuel Malamba5 and David M. Moore6,7AbstractBackground: We compared clinical outcomes among HIV-infected participants receiving ART who wererandomized to viral load (VL) and CD4 cell count monitoring in comparison to CD4 cell count monitoring alone inTororo, Uganda.Methods: Beginning in May 2003, participants with CD4 cell counts <250 cells/μL or WHO stage 3 or 4 diseasewere randomized to clinical monitoring alone, clinical monitoring plus quarterly CD4 cell counts (CD4-only); orclinical monitoring, quarterly CD4 cell counts and quarterly VL testing (CD4-VL). In 2007, individuals in clinicalmonitoring arm were re-randomized to the other two arms and all participants were followed until March 31, 2009.We used Cox Proportional Hazard models to determine if study arm was independently associated with thedevelopment of opportunistic infections (OIs) or death.Results: We randomized 1211 participants to the three original study arms and 331 surviving participants in theclinical monitoring arm were re-randomized to the CD4-VL and CD4 only arms. At enrolment the median age was38 years and the median CD4 cell count was 134 cells/μL. Over a median of 5.2 years of follow-up, 37 deaths and35 new OIs occurred in the VL-CD4 arm patients, 39 deaths and 42 new OIs occurred in CD4-only patients. We didnot observe an association between monitoring arm and new OIs or death (AHR =1.19 for CD4-only vs. CD4-VL;95 % CI 0.82–1.73).Conclusion: We found no differences in clinical outcomes associated with the addition of quarterly VL monitoringto quarterly CD4 cell count monitoring.Keywords: Antiretroviral therapy, Virologic failure, Morbidity, Mortality, Sub-Saharan Africa, Uganda* Correspondence: stephenokoboi@yahoo.co.uk1The AIDS Support Organization-TASO, Headquarters, Mulago HospitalComplex, P.O BOX 10443, Kampala, UgandaFull list of author information is available at the end of the article© 2016 Okoboi et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Okoboi et al. BMC Public Health  (2016) 16:101 DOI 10.1186/s12889-016-2781-yBackgroundOne of the greatest global public health achievementshas been the rapid scaling up of antiretroviral therapy(ART) in resource limited settings over the past decade.This has largely been achieved through the “publichealth approach” promoted by the World HealthOrganization (WHO) [1–3]. This approach has involvedtraining a range of different health-care personnel tosupport delivery and monitoring of ART treatment andcare services with the aim of shifting from a centralized,doctor-led model of HIV treatment and care to decen-tralized models, thus enabling a larger number of peopleto be initiated and retained in care [3, 4].The WHO 2003 guidelines for the use of ART initiallydid not recommend viral load (VL) testing as a necessarycomponent of treatment programs. However, the WHO2013 guidelines now recommend VL testing as the pre-ferred monitoring approach to diagnose and confirmART treatment failure in both adults and children. Thusmany countries such as Uganda [5] have revised theirnational guidelines for the provision of ART to recom-mend VL monitoring as the preferred standard. How-ever, VL testing remains relatively costly and moretechnologically challenging in comparison to clinical orCD4 cell count monitoring in resource limited settings.Moreover, the WHO scale-up strategy is based ondecentralized, integrated delivery of HIV care. However,in rural areas where most patients live, local health fa-cilities generally do not have access to sophisticated la-boratories and referral networks for transportingsamples to, and receiving results from, centralized la-boratories [1, 6]. While there are advantages to provid-ing access to VL testing such as earlier detection oftreatment failure and thus a reduced likelihood ofdeveloping ART drug resistance, this approach is stilldebated in resource limited settings [7–11].The Home-Based AIDS Care (HBAC) project was a 3arm clinical trial which found that clinical monitoringalone resulted in increased risk of new OIs or death, incomparison to the two other arms where routine labora-tory monitoring was available [8]. However, the studyfound no difference in clinical outcomes between partic-ipants who were randomized to VL and CD4 cell countmonitoring in comparison to CD4 cell count monitor-ing, alone after 3 years of follow-up. The only other ran-domized trial which has directly compared clinicaloutcomes between patients monitored with VL and CD4cell counts with those monitored with CD4 cell countsalone, conducted in Thailand found similar results. [12]In, 2007, following the end of the first phase of theHBAC trial, participants who were originally randomizedto the clinical monitoring arm were re-randomized to ei-ther the VL or the CD4 cell count monitoring arm andall participants were observed for an additional 2 yearsof follow-up. We now report on the long term clinicaloutcomes from this study with this additional follow-uptime. The objective of this continuation of the HBACtrial was to see if any additional differences emergedwith additional follow-up between individuals receivingCD4 cell count monitoring and VL testing in compari-son to those individuals who received CD4 cell counttesting alone.MethodsStudy designBeginning in May, 2003, we assessed for eligibility forstudy enrolment of HIV positive adult patients ≥18 yearswho had registered with The AIDS Support Organization(TASO) - Tororo branch. Enrolment was offered to pa-tients with a CD4 cell count <250 cells/μL or severe HIVdisease (defined as WHO stage 3 or 4 or a history of re-current herpes zoster). Additional enrollment criteria aredescribed elsewhere. [8] We obtained written informedconsent from all the study participants that were enrolledin the study. Participants initiated ART with combinationsof lamuvidine with either niverapine or efavirenz; and zi-dovudine or stavudine, In April, 2007, following analysisof the first phase of the study which demonstrated thatclinical follow-up only participants were at increased riskfor death and/or new opportunistic infections (OIs) [8],these participants were re-randomized to either clinicalmonitoring and quarterly CD4 cell counts and VL (CD4-VL) or clinical monitoring and quarterly CD4 cell countsonly (CD4-only) and all participants were followed untilMarch 31, 2009. Trained lay field workers continued toprovide ART to participants at home including collectingdata to monitor potential toxicity, morbidity and mortal-ity. However, the frequency of home visits was changed inthe second phase of the study over a 4 month period fromonce per week to once every 2 months. Pre-packageddrugs were replaced by using a storage container, and pillcounts were conducted at the study clinic by a pharmacist.Participants were weighed during home visits and theseweights and body mass index (BMI) scores were providedto clinicians. After enrolment, no routine clinic visits werescheduled but participants were encouraged to come tothe clinic or hospital if they were ill and were transportedto the clinic for assessment if they had specifically definedsymptoms or severe illness during a home visit.Monitoring and diagnostic procedures for the occur-rence of illness did not differ between study arms. Physi-cians responsible for patients in the two study armsreceived laboratory results on a quarterly basis. Partici-pants received daily cotrimoxazole prophylaxis regardlessof CD4 cell count except during a five-month cotrimoxa-zole discontinuation sub-study [13] Participants who hadART treatment failure as per the arm-appropriate defini-tions below were switched to didanosine, tenofovir, andOkoboi et al. BMC Public Health  (2016) 16:101 Page 2 of 8lopinavir/ritonavir. In the CD4-VL arm, treatment failurewas defined as two consecutive viral load measurements≥500copies/mL occurring more than 6 months after thestart of ART. For the CD4-only arm, persistently decliningCD4 cell counts on two consecutive measurements wasconsidered to indicate treatment failure. The first responseto a worsening trend in CD4 or VL was counselling aboutadherence to treatment. Study physicians, nurses, counsel-lors, and other staff met weekly in a case conference todiscuss all deaths, opportunistic illnesses, and abnormallaboratory results and approved all regimen changes. Adata safety monitoring board reviewed data every 3months and was asked to reject the null hypothesis ofmonitoring arm equivalence if the rate of severe morbidityand mortality in any arm exceeded another by threestandard errors of the difference (“Haybittle-Peto” rule)[14, 15]. The study received ethics approval from theUniversity of British Columbia, the UgandaVirus ResearchInstitute, and the Institutional Review Board of the UnitedStates Center for Disease Control and Prevention and theUganda National Council for Science and Technology.The trial was registered at ClinicalTrials.gov, Registrationnumber NCT00119093.Laboratory proceduresHIV VL was measured with Cobas Amplicor HIV-1Monitor version 1.5 ultrasensitive assay (Roche,Branchburg, NJ) for baseline measurements, which hada lower limit of detection of 400 copies/mL. Follow-upVL measurements were conducted with the CobasTaqman (manual extraction) assay, with a lower limit ofdetection of 50 copies/mL. CD4 cell counts were donewith Tri TEST reagents following an in house dual plat-form protocol and MultiSET and Attractors softwarewith a FAC Scan or FACS Calibur flowcytometer(Becton-Dickinson, Franklin Lakes, NJ). Completeblood counts were provided with CD4 cell counts [6].Data analysisWe followed the study participants randomized or re-randomized in the remaining two arms for an additional2 years up to 21st March 2009. We conducted bivariateanalyses of clinical and demographic characteristics ofstudy participants in the remaining two arms. Data wereanalyzed with SAS 9.0 (SAS Institute, Cary,NC). We usedKaplan-Meier survival curves to graphically compare timeto first opportunistic illness (OI) or death after 90 days fol-lowing ART initiation (or after re-randomization for thosewho were re-randomized to the CD4-VLor CD4-onlyarms). Adherence to therapy was calculated using themedication possession ratio. [16] Cox proportional haz-ards regression models were used to adjust for possibleconfounding, by age, sex, baseline CD4 cell count, VLand body mass index (BMI). Poisson regression analysiswith log link function was used to compare the rates ofnew opportunistic infections and/or deaths occurringafter 90 days following ART initiation (or after re-randomization for those who were re-randomized). Lo-gistic regression models were used to compare theproportions that were switched to second line regimensand proportion that had elevated (≥500 copies/mL)viral loads after 6 months on ART or after re-randomization for those who were re-randomized.Person time for people lost to follow-up or transferredto a different provider was censored at the time of thelast home visit at which they received ART.ResultsA total of 1211 participants were randomized beginningin May 2004 and started on ART in the initial threestudy arms (413 in VL arm 411 in CD4 cell count armand 387 in the clinical arm [8]. Overall, 71.8 % of theparticipants were female, the median age was 38 years(IQR: 32–44) and the median baseline CD4 cell countwas 134 cells/mL (IQR: 70–199). In April, 2007, 331 sur-viving participants in the clinical arm were re-randomized to the VL (165) and CD4 cell count (166)arms (Fig. 1). Demographic and clinical parameters weresimilar across the two study arms, (Table 1).As of April 30, 2009, the median follow-up time forall participants was 5.2 years from the originalrandomization date and 4.8 years after 90 days on ART(or re-randomization). During follow-up after 90 dayson ART (or re-randomization) 37 deaths and 35 newOIs occurred in patients randomized or re-randomizedto the CD4-VL arm and 39 deaths. The last medianCD4 for VL arm was 560, IQR (324–602) while CD4arm was 554, 1QR (331–595). We did not find any sig-nificant differences between the two arms p = 0.986.Forty two (42) new OIs occurred in patients in the CD4cell count arm. The most common OIs diagnosedamong participants were tuberculosis (49 % of OIs),followed by Cryptococcosis (13 %), and Kaposi’ssarcoma (10 %).In a Kaplan-Meier analysis, we found no difference inthe time to first event of new OI or mortality betweenthe two monitoring arms (Fig. 2.) rate of 3.0 per 100person-years in the CD4-VL arm compared to 3.2 per100 person-years in the CD4 arm; p = 0.605 for log-ranktest. Adherence was similar across the two study armswith the mean adherence over each visit interval of 99 %in each study arm (p = 0.123). In a Cox proportional haz-ards model with adjustment for baseline age, sex, CD4cell count, viral load, and BMI, there was no statisticallysignificant difference in the risk of first serious morbidityor death between the CD4 arm and the CD4-VL arm;adjusted hazard ratio [AHR] 1.19, 95 % confidence inter-val 0.82–1.73) for the CD4 cell count arm in comparisonOkoboi et al. BMC Public Health  (2016) 16:101 Page 3 of 8to the CD4-VL arm. We did not find any statistically sig-nificant difference between the two arms in terms ofmortality (HR =1.12, 95 % CI: 0.70–1.77) (Table 2) orthe number of severe morbidity events including death(RR = 1.23, 95 % CI: 0.88–1.71) after adjusting forbaseline age, sex, CD4 cell count, viral load, and BMI(data not shown), when analyzed separately.During the follow-up, 182 participants had at least oneelevated VL measurement (≥500 copies/mL after 6 monthsor re-randomization for those who were re-randomized;80 (14.6 %) in the CD4-VL arm, 102 (18.9 %) in the CD4arm (Table 3). These differences were not statistically sig-nificant (Odds ratio = 1.31 for CD4 cell count arm relativeto CD4-VL arm, 95 % CI: 0.95–1.83). A total of 54 partici-pants were changed to a second-line regimen (Table 4), 30(5.3 %) in the CD4-VL arm, and 24 (4.3 %) in the CD4arm (Table 4). Again these differences were not statisti-cally significant) (OR = 0.76) for the CD4 arm comparedto the CD4-VL arm, 95 % CI: 0.44–1.33). Of the 24 indi-viduals in the CD4 arm who were switched to second-linetherapy, 11(46 %) were found to have had VLs > 500 cop-ies/mL after 6 months of ART. We noted that a smallerproportion of patients in the CD4-VL arm who ever hadtwo VL results ≥500 copies/mL compared to those in theCD4 monitoring arm (4.6 % vs. 7.5 %). However this dif-ference was not statistically significant (p = 0.56). At theclose of the study, 92 % of the participants on the CD4only arm had undetectable viral loads.DiscussionIn this extension of the HBAC study as a two-arm trial,we found no statistically significant differences in clinicaloutcomes associated with the addition of quarterly VLmonitoring to quarterly CD4 cell count monitoring afterover 5 years of follow-up. Furthermore, we did not findany differences in terms of the proportion of participantsTable 1 Baseline characteristics of HBAC study participantsTororo and Busia Districts, Uganda, 2003-9, according to type ofmonitoring: viral load armALL Viral load arm CD4 armVariable N % n % n % p-valueSexF 810 72.7 409 73.0 401 72.4 0.807M 304 27.3 151 27.0 153 27.6Baseline CD4<50 197 17.7 97 17.4 100 18.1 0.82450–200 645 58.1 322 57.7 323 58.5>200 268 24.1 139 24.9 129 23.4Baseline viral load<1000 35 3.2 17 3.1 18 3.3 0.4341000–9999 47 4.3 28 5.1 19 3.510,000–99,999 311 28.3 148 26.8 163 29.9> = 100,000 705 64.2 360 65.1 345 63.3Baseline BMI<18.5 302 27.8 149 27.4 153 28.1 0.34718.5–24.9 713 65.5 351 64.5 362 66.525–29.9 53 4.9 32 5.9 21 3.9> = 30 20 1.8 12 2.2 8 1.5Fig. 1 Study profileOkoboi et al. BMC Public Health  (2016) 16:101 Page 4 of 8ABCFig. 2 Kaplan-Meier curves of time to first opportunistic illness or death. a-c Porportion of participants without opportunistic infection/illness/mortalityOkoboi et al. BMC Public Health  (2016) 16:101 Page 5 of 8with unsuppressed VL or rate of switching to second-linetherapy between these two strategies. Our analysis againsuggests that the addition of VL monitoring to CD4 cellcount monitoring may not result in improved clinical out-comes for HIV positive patients receiving ART in resourcelimited settings. This conclusion is the same as that of theoriginal HBAC study and the only other direct compari-son of VL and CD4 cell count monitoring, another RCTconducted in Thailand [12, 17]. The latter study reportedthat a CD4 switching strategy was non-inferior in terms ofclinical outcomes among HIV-positive adults, 3 years afterbeginning ART when compared to a VL -based switchingstrategy [12]. The authors found that there was also nodifference between the strategies in terms of virologic sup-pression and immune restoration. Importantly, however,even though patients in the CD4 arm spent longer with ahigh viral load than patients in the VL arm, the emer-gence of HIV mutants resistant to antiretroviral drugswas similar in the two arms [12]. Unfortunately, wedo not have any resistance data in order to makecomparisons in this regard.These findings differ somewhat from the results of ananalysis of mortality of patients on ART in SouthernAfrica from the International epidemiological Databasesto Evaluate AIDS in Southern Africa (IeDEA-SA) [8].Participants from programs which did not have access toVL testing, namely those in Zambia and Malawi re-ported higher rates of death and loss to follow up, incomparison to participants from South Africa where VLmeasurement was accessible and readily available. How-ever, it is unlikely that the only differences between theseprograms related to the provision of VL testing and dif-ferences in health care systems and living environmentsof these patients likely also influenced the differences inoutcomes observed. Studies which compared the effectof routine VL testing to the standard of care where VLwas used sparingly to adjudicate discrepancies betweenCD4 and clinical assessments, found that VL monitoringdid not reduce death over the first 36 months of ARTbut did result in earlier ART regimen change [8, 9, 18].A similar exploratory study by AIDS Clinical TrialsGroup A5115 that followed up participants for threeTable 2 Cox proportional hazards regression analysis for time to first morbidity (OI) or mortality eventArm # people # Events Person years Rate per 100 person years Hazard Ratio (95 % CI) a p_valueOriginal Viral load and CD4 armsViral load arm 395 49 1617.3 3.03 ref.CD4 arm 388 53 1607.7 3.30 1.22( 0.82 to 1.84) 0.327Re-randomized from Clinical armViral load arm 165 8 313.3 2.55 ref.CD4 arm 166 9 314.1 2.87 1.14( 0.42 to 3.10) 0.801All combinedViral load arm 560 57 1930.6 2.95 ref.CD4 arm 554 62 1921.9 3.23 1.19( 0.82 to 1.73) 0.368aAdjusted for Age, sex, baseline CD4, Viral load and BMITable 3 Proportion switched to second line regimen (after re-randomization for those who were re-randomized)Arm # people Number Percent Odds Ratio (95 % CI) a p-valueOriginal Viral load and CD4 armsViral load arm 395 15 3.8 ref.CD4 arm 388 13 3.4 0.87( 0.40 to 1.90) 0.727Re-randomized from Clinical armViral load arm 165 15 9.1 ref.CD4 arm 166 11 6.6 0.70( 0.31 to 1.60) 0.399All combinedViral load arm 562 30 5.3 ref.CD4 arm 557 24 4.3 0.76( 0.44 to 1.33) 0.343aAdjusted for Age, sex, baseline CD4, Viral load and BMIOkoboi et al. BMC Public Health  (2016) 16:101 Page 6 of 8years and compared a treatment switching strategybased on CD4-only monitoring versus VL thresholds in21 public hospitals throughout Thailand reported no sig-nificant differences in activated or total CD4 cells atstudy end [19, 20]. Despite the lack of evidence of clin-ical benefit to support the use of routine VL testing,there may be other reasons to promote increase use ofVL testing. Routine monitoring of participants with VLmay result in reduction in the time a patient takes a failingregimen and potentially reducing the frequency of devel-oping drug resistant mutations [21]. However, to date,there is very little evidence that the drug resistance muta-tions which develop while patients are failing their first-line regimens have much effect on the success second-linetherapy. A study from Malawi found that virologic re-sponses to a second line regimen among 109 participantswith immunologically-defined treatment failure and ameasured VL ≥1000 copies/mL was quite good (85 % VL< 400 copies/mL among those with VL measurements at12 months after switching), although mortality was quitehigh at 9 %. All patients in this study had viruses with atleast one resistance mutation, and 56 % of patients had vi-ruses with thymidine analogue mutations, but the authorsdid not find an association with these mutations and viro-logic suppression at one-year after treatment switching[22]. Furthermore, the Thai RCT described above, did notfind differences in the accumulation of virologics resist-ance mutations. More evidence from larger studies areneeded to determine whether virologic monitoring canimprove outcomes for individuals diagnosed with treat-ment failure in resource-limited settings. In the interim,designing HIV programmes that maximize retention ofpatients in the continuum of care and support adherencecounselling to treatment should remain the focus of HIVtreatment programmes. [23–25] Many programmes inSub-Saharan Africa have reported a loss to follow upamong patients on ART of 20 % or more suggesting po-tential for improvement [26, 27].This study has a number of limitations; firstly, thegeneralizability of our study findings to routine care set-tings may be limited as participants in this trial wereseen and counseled more frequently than is routine inmost settings. In the first phase of the HBAC study, par-ticipants received weekly home delivery of ART and clin-ical monitoring by field officers. However, in this phaseof the study we extended the interval between homevisits to once every 2 months over a 4 month period, inorder to reflect standard care models. The intensity ofthe follow-up likely contributed to the low overall ratesof virologic failure and loss to follow-up in comparisonto those reported in most other settings. It is also im-portant to note that laboratory evaluations were per-formed every 3 months, rather than every 6 months thatis recommended by WHO. Furthermore, the rates ofvirological failure in our study were generally lower thanmost reported programmes from the region, as surveyedin a recent systematic review [27–30].ConclusionsIn conclusion, we found that clinical outcomes in thefirst 5 years after ART initiation were not different be-tween participants with access to CD4 testing alone incomparison to those with routine VL and CD4 cellcount testing. These data support the continued expan-sion of access to ART in resource-limited settings, irre-spective of the availability of VL testing.AbbreviationsTASO: The AIDS Support Organization; HBAC: Home Based AIDS Care;BMI: Body Mass Index; ART: Anti-retroviral therapy; RCT: Randomized ClinicalTrial.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsDMM, JPE, RK JCD, FK and SM, designed the study. CB, DMM, and JPEsupervised data collection of the study. AE, CB, and JPE collected the data.AE, CB, SO, and DMM, conducted or contributed to the data analysis. AE, JPE,Table 4 Proportion switched to second line regimen (after re-randomization for those who were re-randomized)Arm # people Number Percent Odds Ratio (95 % CI) a p-valueOriginal Viral load and CD4 armsViral load arm 395 15 3.8 ref.CD4 arm 388 13 3.4 0.87( 0.40 to 1.90) 0.727Re-randomized from Clinical armViral load arm 165 15 9.1 ref.CD4 arm 166 11 6.6 0.70( 0.31 to 1.60) 0.399All combinedViral load arm 562 30 5.3 ref.CD4 arm 557 24 4.3 0.76( 0.44 to 1.33) 0.343aAdjusted for Age, sex, baseline CD4, Viral load and BMIOkoboi et al. BMC Public Health  (2016) 16:101 Page 7 of 8CB, SO and DMM interpreted the data. SO prepared the original manuscript,all authors contributed to subsequent revisions, read and approved the finalmanuscript.Acknowledgements and financial disclosureThe authors would like to thank the study staff and participants of the HBACproject. HBAC was funded by the President’s Emergency Plan for AIDS Reliefthrough the US Centers for Disease Control and Prevention. This researchwas funded by the Canadian Institutes for Health Research (Grant numberHHP-115598). DMM is supported by a Scholar Award from the Michael SmithFoundation for Health Research.Author details1The AIDS Support Organization-TASO, Headquarters, Mulago HospitalComplex, P.O BOX 10443, Kampala, Uganda. 2University of Alberta,Edmonton, Canada. 3University of Maryland School of Medicine, Baltimore,MD, USA. 4University of California, San Francisco, USA. 5Makerere UniversitySchool of Public Health, Kampala, Uganda. 6BC Centre for Excellence in HIV/AIDS, Vancouver, Canada. 7University of British Columbia, Vancouver, Canada.Received: 16 October 2015 Accepted: 25 January 2016References1. Gilks CF, Crowley S, Ekpini R, Gove S, Perriens J, Souteyrand Y, Sutherland D,et al. The WHO public-health approach to antiretroviral treatment againstHIV in resource-limited settings. Lancet. 2006;368:505–10.2. World Health Organization guidelines. 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AIDS Care. 2007;19:658–65.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Okoboi et al. BMC Public Health  (2016) 16:101 Page 8 of 8


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