Summary
Among 3,596 HIV-positive participants enrolled in Botswana Combination Prevention Project (BCPP) who self-reported no prior ART use and were tested for viral load (n=951; 27% of all participants), 136 (14%) had HIV-1 RNA <400 copies/mL. ARV drugs were detected in 52 (39%) of 134 participants tested. Adjusting for undisclosed ARV use increased the overall estimate of virally suppressed individuals on ART by 1.4% from 70.2% to 71.6%.
Keywords: Antiretroviral therapy (ART), Antiretroviral drugs (ARVs), undisclosed ART use, Botswana, estimate of virally suppressed
Introduction
Undisclosed antiretroviral (ARV) use among virally suppressed individuals may underestimate programmatic antiretroviral therapy (ART) coverage estimates, affect interpretability of clinical trials results[1–10], and/or inflate estimates of viremic controllers[11–15]. Undisclosed ARV use has been reported in previous studies[16–18] including studies in Africa[8–10, 19]. While self-report is commonly used to measure ART uptake[20–23], its accuracy could be affected by undisclosed ART use.
As of 2016, Botswana was one of seven countries in the world and the only African country that was reported to have achieved targeted levels of viral suppression defined by UNAIDS[24, 25]. The goal of the study was to evaluate the extent of undisclosed ART use in Botswana and assess how lack of disclosure might alter national estimates of UNAIDS 90-90-90 targets[26, 27].
Methods
Study population
Blood specimens were collected in the BCPP study[6] in 2013–2015. The participants in this study represent a 20% random sampling of households in the 30 communities. People living with HIV (PLHIV) participating in the BCPP study verbally reported prior and current ART receipt[6]. Participants aged 18–64 years provided written informed consent (ascent for participants aged 16–17 years).
HIV-1 RNA testing
Following positive double rapid HIV testing, venous blood was collected by phlebotomy in households. The HIV-1 RNA load in plasma was quantified by Abbott m2000sp/Abbott m2000rt (Wiesbaden, Germany).
ARV drug detection
Plasma from 134 of 135 participants who reported no ART use and had undetectable HIV-1 RNA (≤400 copies/mL) was screened for ARV drugs by high-throughput liquid chromatography coupled with Q-Exactive high-resolution mass spectrometry using data-dependent fragmentation and selected reaction monitoring at resolution of 17,500[28]. To obtain qualitative results, each specimen was compared to positive and negative controls for each of 20 drugs tested. The limit of identification ranged from 5 to 10 ng/ml and is presented elsewhere[28].
Statistical analysis
Adjusted prevalence ratios (aPR) and 95% confidence intervals (CI) were estimated for factors associated with undisclosed ART use accounting for clustering, age, and gender. P-values <0.05 were considered statistically significant. Statistical analyses were performed in STATA v.14.2 (College Station, TX) and SAS v.9.4 (SAS Institute, Cary, NC).
Results
Of 12,610 adult BCPP baseline household survey participants, 3,596 (29%) were HIV-infected, and 953 (27%; 95%CI: 24–30%) self-reported no prior use of ART. Of those with an available viral load (N=951), 136 (14%) had HIV-1 RNA<400 copies/mL. Multiple ARV drugs were detected in 52 (39%, 95%CI: 30–50%) of the 134 virologically suppressed individuals tested for ARV drugs. Three ARV drugs were detected in 42 participants, two drugs in 9 participants, and one participant had a single drug detected (efavirenz). The most commonly identified ARV combinations detected were (efavirenz/nevirapine)/emtricitabine/tenofovir which were the first-line treatment regimens most commonly prescribed in Botswana’s national ART program at the time of sampling. Among 52 individuals with ARV drugs detected, 36 (69%) stated that they did not know their HIV status.
Among virologially suppressed participants with evidence of current ART use either through self-report or detection of ARV drugs (N=2,569), non-disclosure of ART use was associated with being <35 years old (aPR=4.38; 95%CI: 2.51–7.63) and sex with a younger partner (PR=1.63; 95%CI: 1.01–2.63). No significant differences were found according to sex, employment status, income, education, alcohol use, and history of concurrent sexual partnerships or transactional sex.
Discussion
We found that among HIV-infected individuals who reported not being on ART, 14% had undetectable HIV-1 RNA (≤400 copies/mL), 39% of whom had detectable plasma ARV levels. Udisclsosed ART use was also reported in Partners in Prevention study[8], HPTN 052 study[10], in Kenya[9] and South Africa[19]. After adjusting for undisclosed ARV use in BCPP study communities, the estimated proportion of PLHIV who have undetectable HIV-1 RNA on ART in Botswana increased by 1.4%, from 70.2%[6] to 71.6%. Adjusting for undisclosed ARV use provided more accurate estimates of the country progress toward the UNAIDS 90-90-90 targets[26, 27].
Testing for ARV drugs in blood is the only biomedical verification method able to either confirm or reject self-report of no ART use. While feasible in research settings, it is not practical to conduct ARV level testing in programmatic settings. However, testing may represent a viable surveillance measure in a proportion of virally suppressed persons who self-report being ART-naïve in population surveys. ART use could also be ascertained from national ARV data systems where such systems exist and ethical considerations are taken into account.
The underlying reasons of unreported ARV use could include stigma, non-adherence or desire for confirmation of HIV infection, or may represent use of non-prescribed ARVs including sharing of drugs. We found that undisclosed ARV use was associated with younger age (similar to reports from KwaZulu-Natal, South Africa[19] and Kenya[9]) and sex with a younger partner. No significant difference was found in undisclosed ARV use by gender (similar to a report by Kahle et al.[8]), employment status, income level, educational level, alcohol use, and history of concurrent sexual partnerships or transactional sex.
We tested for presence or absence of ARV drugs (at low thresholds), but did not measure ARV drug concentrations, nor could we ascertain the timing of most recent ARV dosing. ARV drug levels are affected by individual drug metabolism and timing of sample collection in relation to drug ingestion. Plasma half-life for NNRTIs is much longer than for NRTIs. We therefore cannot exclude that some ARV drugs could not be detected due to unknown time between ARV intake and sampling. Another limitation of this study is that we did not screen for ARV drugs among individuals with detectable viral load, or individuals who said that they were receiving ART.
Conclusion
Among household survey participants in Botswana who reported no prior use of ART and had no detectable virus, undisclosed ARV use was found in 39%. Accounting for undisclosed ART increased the estimated proportion of virologically suppressed individuals among HIV-infected people in Botswana by 1.4% to 71.6%. Testing for ARV drugs in virologically suppressed individuals could supplement self-report of ART use and inform estimates of ART coverage, as well as providing valuable information to clinicians and clinical trials investigators.
Acknowledgments
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. The content is solely the responsibility of the authors and does 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 and SG were partially supported by Sub-Saharan African Network for TB/HIV Research Excellence (SANTHE), a DELTAS Africa Initiative [grant # DEL-15-006]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [grant #107752/Z/15/Z] and the U.K. government. The views expressed in this publication are those of the authors and not necessarily those of AAS, NEPAD Agency, Wellcome Trust, or the U.K. government. The funders had no role in the study design, data collection and decision to publish, or in the preparation of the manuscript.
We thank the study participants and entire BCPP staff including all the field study teams for making this study a success. We thank the BCPP team members for their contribution to this study. We thank Lendsey Melton for excellent editorial assistance. We thank the Ministry of Health and CDC Botswana for their excellent support and contributions to the study. We thank Michelle Roland for helpful critique and discussion.
Footnotes
Author Disclosure Statement
All authors have declared that no competing interest exists.
References
- 1.Granich R, Gupta S, Hall I, Aberle-Grasse J, Hader S, Mermin J. Status and methodology of publicly available national HIV care continua and 90-90-90 targets: A systematic review. PLoS Med. 2017;14(4):e1002253. doi: 10.1371/journal.pmed.1002253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Granich R, Williams B, Montaner J, Zuniga JM. 90-90-90 and ending AIDS: necessary and feasible. Lancet. 2017;390(10092):341–343. doi: 10.1016/S0140-6736(17)31872-X. [DOI] [PubMed] [Google Scholar]
- 3.Hayes R, Floyd S, Schaap A, Shanaube K, Bock P, Sabapathy K, et al. A universal testing and treatment intervention to improve HIV control: One-year results from intervention communities in Zambia in the HPTN 071 (PopART) cluster-randomised trial. PLoS Med. 2017;14(5):e1002292. doi: 10.1371/journal.pmed.1002292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Jain V, Petersen ML, Liegler T, Byonanebye DM, Kwarisiima D, Chamie G, et al. Population levels and geographical distribution of HIV RNA in rural Ugandan and Kenyan communities, including serodiscordant couples: a cross-sectional analysis. The lancet HIV. 2017;4(3):e122–e133. doi: 10.1016/S2352-3018(16)30220-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Petersen M, Balzer L, Kwarsiima D, Sang N, Chamie G, Ayieko J, et al. Association of Implementation of a Universal Testing and Treatment Intervention With HIV Diagnosis, Receipt of Antiretroviral Therapy, and Viral Suppression in East Africa. JAMA. 2017;317(21):2196–2206. doi: 10.1001/jama.2017.5705. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Gaolathe T, Wirth KE, Holme MP, Makhema J, Moyo S, Chakalisa U, et al. Botswana’s progress toward achieving the 2020 UNAIDS 90-90-90 antiretroviral therapy and virological suppression goals: a population-based survey. The lancet HIV. 2016;3(5):e221–230. doi: 10.1016/S2352-3018(16)00037-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.UNAIDS. UNAIDS Data. 2017 http://www.unaids.org/sites/default/files/media_asset/20170720_Data_book_2017_en.pdf.
- 8.Kahle EM, Kashuba A, Baeten JM, Fife KH, Celum C, Mujugira A, et al. Unreported antiretroviral use by HIV-1-infected participants enrolling in a prospective research study. J Acquir Immune Defic Syndr. 2014;65(2):e90–94. doi: 10.1097/QAI.0b013e3182a2db02. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kim AA, Mukui I, Young PW, Mirjahangir J, Mwanyumba S, Wamicwe J, et al. Undisclosed HIV infection and antiretroviral therapy use in the Kenya AIDS indicator survey 2012: relevance to national targets for HIV diagnosis and treatment. AIDS. 2016;30(17):2685–2695. doi: 10.1097/QAD.0000000000001227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Fogel JM, Wang L, Parsons TL, Ou SS, Piwowar-Manning E, Chen Y, et al. Undisclosed antiretroviral drug use in a multinational clinical trial (HIV Prevention Trials Network 052) J Infect Dis. 2013;208(10):1624–1628. doi: 10.1093/infdis/jit390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Crowell TA, Hatano H. Clinical outcomes and antiretroviral therapy in ‘elite’ controllers: a review of the literature. Journal of virus eradication. 2015;1(2):72–77. doi: 10.1016/S2055-6640(20)30488-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Walker BD. Elite control of HIV Infection: implications for vaccines and treatment. Top HIV Med. 2007;15(4):134–136. [PubMed] [Google Scholar]
- 13.Eyzaguirre LM, Charurat M, Redfield RR, Blattner WA, Carr JK, Sajadi MM. Elevated hypermutation levels in HIV-1 natural viral suppressors. Virology. 2013;443(2):306–312. doi: 10.1016/j.virol.2013.05.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Miura T, Brockman MA, Brumme CJ, Brumme ZL, Carlson JM, Pereyra F, et al. Genetic characterization of human immunodeficiency virus type 1 in elite controllers: lack of gross genetic defects or common amino acid changes. J Virol. 2008;82(17):8422–8430. doi: 10.1128/JVI.00535-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Miura T, Brumme ZL, Brockman MA, Rosato P, Sela J, Brumme CJ, et al. Impaired replication capacity of acute/early viruses in persons who become HIV controllers. J Virol. 2010;84(15):7581–7591. doi: 10.1128/JVI.00286-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sullivan AK, Savage EJ, Lowndes CM, Paul G, Murphy G, Carne S, et al. Non-disclosure of HIV status in UK sexual health clinics--a pilot study to identify non-disclosure within a national unlinked anonymous seroprevalence survey. Sex Transm Infect. 2013;89(2):120–121. doi: 10.1136/sextrans-2012-050801. [DOI] [PubMed] [Google Scholar]
- 17.Das M, Raymond HF, Chu P, Nieves-Rivera I, Pandori M, Louie B, et al. Measuring the unknown: calculating community viral load among HIV-infected MSM unaware of their HIV status in San Francisco from National HIV Behavioral Surveillance, 2004-2011. J Acquir Immune Defic Syndr. 2013;63(2):e84–86. doi: 10.1097/QAI.0b013e31828ed2e4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Marzinke MA, Clarke W, Wang L, Cummings V, Liu TY, Piwowar-Manning E, et al. Nondisclosure of HIV status in a clinical trial setting: antiretroviral drug screening can help distinguish between newly diagnosed and previously diagnosed HIV infection. Clin Infect Dis. 2014;58(1):117–120. doi: 10.1093/cid/cit672. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Huerga H, Shiferie F, Grebe E, Giuliani R, Farhat JB, Van-Cutsem G, et al. A comparison of self-report and antiretroviral detection to inform estimates of antiretroviral therapy coverage, viral load suppression and HIV incidence in Kwazulu-Natal, South Africa. BMC Infect Dis. 2017;17(1):653. doi: 10.1186/s12879-017-2740-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Cherutich P, Kim AA, Kellogg TA, Sherr K, Waruru A, De Cock KM, et al. Detectable HIV Viral Load in Kenya: Data from a Population-Based Survey. PLoS One. 2016;11(5):e0154318. doi: 10.1371/journal.pone.0154318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Bicego GT, Nkambule R, Peterson I, Reed J, Donnell D, Ginindza H, et al. Recent patterns in population-based HIV prevalence in Swaziland. PLoS One. 2013;8(10):e77101. doi: 10.1371/journal.pone.0077101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kassa G, Selenic D, Lahuerta M, Gaolathe T, Liu Y, Letang G, et al. Occupational exposure to bloodborne pathogens among health care workers in Botswana: Reporting and utilization of postexposure prophylaxis. American journal of infection control. 2016 doi: 10.1016/j.ajic.2016.01.027. [DOI] [PubMed] [Google Scholar]
- 23.Odhiambo JO, Kellogg TA, Kim AA, Ng’ang’a L, Mukui I, Umuro M, et al. Antiretroviral treatment scale-up among persons living with HIV in Kenya: results from a nationally representative survey. J Acquir Immune Defic Syndr. 2014;66(Suppl 1):S116–122. doi: 10.1097/QAI.0000000000000122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.UNAIDS. Ending AIDS. Progress towards the 90–90–90 targets. 2017 http://www.unaids.org/sites/default/files/media_asset/Global_AIDS_update_2017_en.pdf.
- 25.UNAIDS. Country factsheets. BOTSWANA; 2016. http://www.unaids.org/en/regionscountries/countries/botswana2017. [Google Scholar]
- 26.UNAIDS. 90-90-90: an ambitious treatment target to help end the AIDS epidemic. Geneva, Switzerland: UNAIDS; 2014. [Access date: 11/14/2017]. http://www.unaids.org/sites/default/files/media_asset/90-90-90_en.pdf. [Google Scholar]
- 27.UNAIDS. [Access date: 01/10/2018];90-90-90 On the right track towards the global target. 2016 :62. URL https://reliefweb.int/sites/reliefweb.int/files/resources/90_90_90_Progress_ReportFINAL.pdf.
- 28.Marzinke MA, Breaud A, Parsons TL, Cohen MS, Piwowar-Manning E, Eshleman SH, et al. The development and validation of a method using high-resolution mass spectrometry (HRMS) for the qualitative detection of antiretroviral agents in human blood. Clin Chim Acta. 2014;433:157–168. doi: 10.1016/j.cca.2014.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]