A Comprehensive Approach to Assuring Quality of Laboratory Testing in HIV Surveys: Lessons Learned From the Population-Based HIV Impact Assessment Project.
Journal
Journal of acquired immune deficiency syndromes (1999)
ISSN: 1944-7884
Titre abrégé: J Acquir Immune Defic Syndr
Pays: United States
ID NLM: 100892005
Informations de publication
Date de publication:
01 08 2021
01 08 2021
Historique:
entrez:
24
6
2021
pubmed:
25
6
2021
medline:
6
11
2021
Statut:
ppublish
Résumé
Conducting HIV surveys in resource-limited settings is challenging because of logistics, limited availability of trained personnel, and complexity of testing. We described the procedures and systems deemed critical to ensure high-quality laboratory data in the population-based HIV impact assessments and large-scale household surveys. Laboratory professionals were engaged in every stage of the surveys, including protocol development, site assessments, procurement, training, quality assurance, monitoring, analysis, and reporting writing. A tiered network of household, satellite laboratories, and central laboratories, accompanied with trainings, optimized process for blood specimen collection, storage, transport, and real-time monitoring of specimen quality, and test results at each level proved critical in maintaining specimen integrity and high-quality testing. A plausibility review of aggregate merged data was conducted to confirm associations between key variables as a final quality check for quality of laboratory results. Overall, we conducted a hands-on training for 3355 survey staff across 13 surveys, with 160-387 personnel trained per survey on biomarker processes. Extensive training and monitoring demonstrated that overall, 99% of specimens had adequate volume and 99.8% had no hemolysis, indicating high quality. We implemented quality control and proficiency testing for testing, resolved discrepancies, verified >300 Pima CD4 instruments, and monitored user errors. Aggregate data review for plausibility further confirmed the high quality of testing. Ongoing engagement of laboratory personnel to oversee processes at all levels of the surveys is critical for successful national surveys. High-quality population-based HIV impact assessments laboratory data ensured reliable results and demonstrated the impact of HIV programs in 13 countries.
Sections du résumé
BACKGROUND
Conducting HIV surveys in resource-limited settings is challenging because of logistics, limited availability of trained personnel, and complexity of testing. We described the procedures and systems deemed critical to ensure high-quality laboratory data in the population-based HIV impact assessments and large-scale household surveys.
METHODS
Laboratory professionals were engaged in every stage of the surveys, including protocol development, site assessments, procurement, training, quality assurance, monitoring, analysis, and reporting writing. A tiered network of household, satellite laboratories, and central laboratories, accompanied with trainings, optimized process for blood specimen collection, storage, transport, and real-time monitoring of specimen quality, and test results at each level proved critical in maintaining specimen integrity and high-quality testing. A plausibility review of aggregate merged data was conducted to confirm associations between key variables as a final quality check for quality of laboratory results.
RESULTS
Overall, we conducted a hands-on training for 3355 survey staff across 13 surveys, with 160-387 personnel trained per survey on biomarker processes. Extensive training and monitoring demonstrated that overall, 99% of specimens had adequate volume and 99.8% had no hemolysis, indicating high quality. We implemented quality control and proficiency testing for testing, resolved discrepancies, verified >300 Pima CD4 instruments, and monitored user errors. Aggregate data review for plausibility further confirmed the high quality of testing.
CONCLUSIONS
Ongoing engagement of laboratory personnel to oversee processes at all levels of the surveys is critical for successful national surveys. High-quality population-based HIV impact assessments laboratory data ensured reliable results and demonstrated the impact of HIV programs in 13 countries.
Identifiants
pubmed: 34166309
doi: 10.1097/QAI.0000000000002702
pii: 00126334-202108011-00013
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
S17-S27Subventions
Organisme : PEPFAR
Pays : United States
Organisme : CGH CDC HHS
ID : U2G GH001271
Pays : United States
Organisme : CGH CDC HHS
ID : U2G GH001226
Pays : United States
Informations de copyright
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors have no conflicts of interest to disclose.
Références
De Gruttola V, Fineberg HV. Estimating prevalence of HIV infection: considerations in the design and analysis of a national seroprevalence survey . J Acquir Immune Defic Syndr. 1989;2:472–480.
Pepito VC, Newton S. Determinants of HIV testing among Filipino women: results from the 2013 Philippine National Demographic and Health Survey . PLoS One. 2020;15:e0232620.
Bulstra CA, Hontelez JA, Giardina F, et al. Mapping and characterising areas with high levels of HIV transmission in sub-Saharan Africa: a geospatial analysis of national survey data . PLos Med. 2020;17:e1003042.
Bekele YA, Fekadu GA. Factors associated with HIV testing among young females; further analysis of the 2016 Ethiopian Demographic and Health Survey data . PLoS One. 2020;15:e0228783.
Takarinda KC, Madyira LK, Mhangara M, et al. Factors associated with ever being HIV-tested in Zimbabwe: an extended analysis of the Zimbabwe Demographic and Health Survey (2010–2011) . PLoS One. 2016;11:e0147828.
Lakew Y, Benedict S, Haile D. Social determinants of HIV infection, hotspot areas and subpopulation groups in Ethiopia: evidence from the National Demographic and Health Survey in 2011 . BMJ Open. 2015;5:e008669.
Woodring J, Kruszon-Moran D, McQuillan G. HIV infection in U.S. household population aged 18–59: data from the National Health and Nutrition Examination survey, 2007–2012 . Natl Health Stat Rep. 2015;40:1–13.
Chandra A, Billioux VG, Copen CE, et al. HIV testing in the U.S. household population aged 15–44: data from the National Survey of Family Growth, 2006–2010 . Natl Health Stat Rep. 2012;48:1–26.
Anderson JE, Mosher WD, Chandra A. Measuring HIV risk in the U.S. population aged 15–44: results from cycle 6 of the National Survey of family growth . Adv Data. 2006;377:1–27.
Levy V, Page-Shafer K, Evans J, et al. HIV-related risk behavior among hispanic immigrant men in a population-based household survey in low-income neighborhoods of Northern California . Sex Transm Dis. 2005;32:487–490.
Anderson JE, Wilson R, Doll L, et al. Condom use and HIV risk behaviors among U.S. adults: data from a National Survey . Fam Plann Perspect. 1999;31:24–28.
Kwesigabo G, Killewo JZ, Sandstrom A. Sentinel surveillance and cross sectional survey on HIV infection prevalence: a comparative study . East Afr Med J. 1996;73:298–302.
Schopper D, Doussantousse S, Orav J. Sexual behaviors relevant to HIV transmission in a rural African population. How much can a KAP survey tell us? Soc Sci Med. 1993;37:401–412.
Quenum B, Guiguet M, Wells J, et al. HIV antibody testing in France: results of a National Survey . J Acquir Immune Defic Syndr. 1992;5:560–564.
Schechter MT, Ballem PJ, Buskard NA, et al. An anonymous seroprevalence survey of HIV infection among pregnant women in British Columbia and the Yukon Territory . CMAJ. 1990;143:1187–1192.
Cherutich P, Kim AA, Kellogg TA, et al. Detectable HIV viral load in Kenya: data from a population-based survey . PLoS One. 2016;11:e0154318.
Ng'eno B, Mwangi A, Ng'ang'a L, et al. Burden of HIV infection among children aged 18 months to 14 years in Kenya: results from a Nationally Representative Population-Based Cross-Sectional Survey . J Acquir Immune Defic Syndr. 2014;66(suppl 1):S82–S88.
UNAIDS. Ending AIDS Progress Towards the 90-90-90 Targets. Global AIDS Update, 20-July-2017. Available at: https://www.unaids.org/en/resources/documents/2017/20170720_Global_AIDS_update_2017 .
Harding R, Simms V, Penfold S, et al. Availability of essential drugs for managing HIV-related pain and symptoms within 120 PEPFAR-funded health facilities in East Africa: a cross-sectional survey with onsite verification . Palliat Med. 2014;28:293–301.
Marum E, Taegtmeyer M, Parekh B, et al. ‟What took you so long?” the impact of PEPFAR on the expansion of HIV testing and counseling services in Africa . J Acquir Immune Defic Syndr. 2012;60(suppl 3):S63–S69.
Richter LM, Lönnroth K, Desmond C, et al. Economic support to patients in HIV and TB grants in rounds 7 and 10 from the global fund to fight AIDS, tuberculosis and malaria . PLoS One. 2014;9:e86225.
Komatsu R, Korenromp EL, Low-Beer D, et al. Lives saved by global fund-supported HIV/AIDS, tuberculosis and malaria programs: estimation approach and results between 2003 and end-2007 . BMC Infect Dis. 2010;10:109.
Leeper SC, Reddi A. United States global health policy: HIV/AIDS, maternal and child health, and the President's Emergency Plan for AIDS Relief (PEPFAR) . AIDS. 2010;24:2145–2149.
PEPFAR and the fight against HIV/AIDS . Lancet. 2007;369:1141.
Kamwi R, Kenyon T, Newton G. PEPFAR and HIV prevention in Africa . Lancet. 2006;367:1978–1979.
Iwuji C, Newell ML. HIV testing: the ‟front door” to the UNAIDS 90-90-90 target . Public Health Action. 2017;7:79.
Jonnalagadda S, Yuengling K, Abrams E, et al. Survival and HIV-free survival among children aged ≤3 years—eight sub-saharan african countries, 2015–2017 . MMWR Morb Mortal Wkly Rep. 2020;69:582–586.
Gonese E, Musuka G, Ruangtragool L, et al. Comparison of HIV incidence in the Zimbabwe population-based HIV impact assessment survey (2015–2016), with modeled estimates: progress toward epidemic control . AIDS Res Hum Retroviruses. 2020;38:652–662.
Thin K, Frederix K, McCracken S, et al. Progress toward HIV epidemic control in Lesotho: results from a population-based survey . AIDS. 2019;33:2393–2401.
Low A, Thin K, Davia S, et al. Correlates of HIV infection in adolescent girls and young women in Lesotho: results from a population-based survey . Lancet HIV. 2019;6:e613–e622.
Brown K, Williams DB, Kinchen S, et al. Status of HIV epidemic control among adolescent girls and young women aged 15–24 years—seven African countries, 2015–2017 . MMWR Morb Mortal Wkly Rep. 2018;67:29–32.
Saito S, Duong YT, Metz M, et al. Returning HIV-1 viral load results to participant-selected health facilities in National Population-based HIV Impact Assessment (PHIA) household surveys in three sub-Saharan African Countries, 2015 to 2016 . J Int AIDS Soc. 2017;20(suppl 7):19–25.
Augusto ÂD, Iriemenam NC, Kohatsu L, et al. High level of HIV false positives using EIA-based algorithm in survey: importance of confirmatory testing . PLoS One. 2020;15:e0239782.
Staveteig S, Croft TN, Kampa KT, et al. Reaching the ‟first 90”: gaps in coverage of HIV testing among people living with HIV in 16 African countries . PLoS One. 2017;12:e0186316.
Githuka G, Hladik W, Mwalili S, et al. Populations at increased risk for HIV infection in Kenya: results from a National Population-Based Household Survey, 2012 . J Acquir Immune Defic Syndr. 2014;66(suppl 1):S46–S56.
Hakim PH, Duong Y, Katoro J, et al. Evaluation of an EIA-Based Testing Algorithm Using Dried Blood Spots From South Sudan in Conference on Retroviruses and Opportunistic Infections. Conference held on February 22–25, 2016; Boston, Massachusetts; 2016.
Kimanga DO, Ogola S, Umuro M, et al. Prevalence and incidence of HIV infection, trends, and risk factors among persons aged 15-64 years in Kenya: results from a Nationally Representative Study . J Acquir Immune Defic Syndr. 2014;66(suppl 1):S13–S26.
Duong YT, Dobbs T, Mavengere Y, et al. Field validation of limiting-antigen avidity enzyme immunoassay to estimate HIV-1 incidence in cross-sectional survey in Swaziland . AIDS Res Hum Retroviruses. 2019;35:896–905.
Kim AA, Parekh BS, Umuro M, et al. Identifying risk factors for recent HIV infection in Kenya using a recent infection testing algorithm: results from a Nationally Representative Population-Based Survey . PLoS One. 2016;11:e0155498.
Duong YT, Kassanjee R, Welte A, et al. Recalibration of the limiting antigen avidity EIA to determine mean duration of recent infection in divergent HIV-1 subtypes . PLoS One. 2015;10:e0114947.
Duong YT, Qiu M, De AK, et al. Detection of recent HIV-1 infection using a new limiting-antigen avidity assay: potential for HIV-1 incidence estimates and avidity maturation studies . PLoS One. 2012;7:e33328.
Meesters RJ, van Kampen JJ, Reedijk ML, et al. Ultrafast and high-throughput mass spectrometric assay for therapeutic drug monitoring of antiretroviral drugs in pediatric HIV-1 infection applying dried blood spots . Anal Bioanal Chem. 2010;398:319–328.
Parekh BS, Anyanwu J, Patel H, et al. Dried tube specimens: a simple and cost-effective method for preparation of HIV proficiency testing panels and quality control materials for use in resource-limited settings . J Virol Methods. 2010;163:295–300.
Smurzynski M, Wu K, Benson CA, et al. Relationship between CD4+ T-cell counts/HIV-1 RNA plasma viral load and AIDS-defining events among persons followed in the ACTG longitudinal linked randomized trials study . J Acquir Immune Defic Syndr. 2010;55:117–127.
Betts MR, Ambrozak DR, Douek DC, et al. Analysis of total human immunodeficiency virus (HIV)-specific CD4(+) and CD8(+) T-cell responses: relationship to viral load in untreated HIV infection . J Virol. 2001;75:11983–11991.
Martinson NA, Gupte N, Msandiwa R, et al. CD4 and viral load dynamics in antiretroviral-naïve HIV-infected adults from Soweto, South Africa: a prospective cohort . PLoS One. 2014;9:e96369.
Kranzer K, Lawn SD, Johnson LF, et al. Community viral load and CD4 count distribution among people living with HIV in a South African Township: implications for treatment as prevention . J Acquir Immune Defic Syndr. 2013;63:498–505.
Rompalo AM, Astemborski J, Schoenbaum E, et al. Comparison of clinical manifestations of HIV infection among women by risk group, CD4+ cell count, and HIV-1 plasma viral load. HER study group. HIV epidemiology research . J Acquir Immune Defic Syndr Hum Retrovirol. 1999;20:448–454.
Addo MM, Altfeld M. Sex-based differences in HIV type 1 pathogenesis . J Infect Dis. 2014;209(suppl 3):S86–S92.
Voetsch AC, Duong YT, Stupp P, et al. HIV-1 recent infection testing algorithm with antiretroviral drug detection to improve accuracy of incidence estimates . J Acquir Immune Defic Syndr. 2021;87(suppl 1):S72–79.
de Boer MA, Celentano DD, Tovanabutra S, et al. Reliability of self-reported sexual behavior in human immunodeficiency virus (HIV) concordant and discordant heterosexual couples in northern Thailand . Am J Epidemiol. 1998;147:1153–1161.
Johnston LG, Sabin ML, Prybylski D, et al. The importance of assessing self-reported HIV status in bio-behavioural surveys . Bull World Health Organ. 2016;94:605–612.
Harbertson J, Hale BR, Tran BR, et al. Self-reported HIV-positive status but subsequent HIV-negative test result using rapid diagnostic testing algorithms among seven sub-Saharan African military populations . PLoS One. 2017;12:e0180796.
Baker Z, Javanbakht M, Mierzwa S, et al. Predictors of over-reporting HIV pre-exposure prophylaxis (PrEP) adherence among young men who have sex with men (YMSM) in self-reported versus biomarker data . AIDS Behav. 2018;22:1174–1183.
Surveillance. Monitoring the Impact of the HIV Epidemic Using Population-Based Surveys. Geneva, Switzerland: UNAIDS/WHO; 2015.