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Bannick M, Donnell D, Hayes R, Laeyendecker O, Gao F. An enhanced cross-sectional HIV incidence estimator that incorporates prior HIV test results. Stat Med 2024; 43:3125-3139. [PMID: 38803064 DOI: 10.1002/sim.10112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 02/14/2024] [Accepted: 04/29/2024] [Indexed: 05/29/2024]
Abstract
Incidence estimation of HIV infection can be performed using recent infection testing algorithm (RITA) results from a cross-sectional sample. This allows practitioners to understand population trends in the HIV epidemic without having to perform longitudinal follow-up on a cohort of individuals. The utility of the approach is limited by its precision, driven by the (low) sensitivity of the RITA at identifying recent infection. By utilizing results of previous HIV tests that individuals may have taken, we consider an enhanced RITA with increased sensitivity (and specificity). We use it to propose an enhanced estimator for incidence estimation. We prove the theoretical properties of the enhanced estimator and illustrate its numerical performance in simulation studies. We apply the estimator to data from a cluster-randomized trial to study the effect of community-level HIV interventions on HIV incidence. We demonstrate that the enhanced estimator provides a more precise estimate of HIV incidence compared to the standard estimator.
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Affiliation(s)
- Marlena Bannick
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Deborah Donnell
- Biostatistics, Bioinformatics and Epidemiology Program, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Richard Hayes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, England, UK
| | - Oliver Laeyendecker
- School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland, USA
| | - Fei Gao
- Biostatistics, Bioinformatics and Epidemiology Program, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
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2
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He J, Flaxman A, Imai-Eaton JW, Aravkin A, Zheng P, Sorensen R, Mittal S, Kyu HH. Association Between Early Sexual Debut and New HIV Infections Among Adolescents and Young Adults in 11 African Countries. AIDS Behav 2024; 28:2444-2453. [PMID: 38878135 PMCID: PMC11199287 DOI: 10.1007/s10461-024-04343-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 06/26/2024]
Abstract
We investigated the association between early sexual debut and HIV infection among adolescents and young adults. Analyzing data from nationally representative Population-Based HIV Impact Assessment (PHIA) surveys in 11 African countries, the research employed a multivariate logistic regression model to assess the relationship between the early sexual debut and new HIV infections in the age group of 10-24 years. The results revealed a significant and robust association, indicating that young individuals who experienced early sexual debut were approximately 2.65 times more likely to contract HIV than those who did not, even after accounting for other variables. These findings align with prior research suggesting that early initiation of sexual activity may increase vulnerability to HIV infection due to factors such as biological susceptibility and risky behaviors like low condom use and multiple sexual partners. The implications of these findings for HIV prevention strategies are substantial, suggesting that interventions aimed at delaying sexual debut could be an effective component in reducing HIV risk for this population. Targeted sex education programs that address the risks of early sexual debut may play a pivotal role in these prevention efforts. By employing a comprehensive approach, there is a possibility to advance efforts towards ending AIDS by 2030.
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Affiliation(s)
- Jiawei He
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA
| | - Abraham Flaxman
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA
| | - Jeffrey W Imai-Eaton
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Aleksandr Aravkin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA
| | - Peng Zheng
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA
| | - Reed Sorensen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA
| | - Shachi Mittal
- Department of Chemical Engineering, University of Washington, Seattle, USA
| | - Hmwe H Kyu
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA.
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, USA.
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van den Berg K, Murphy EL, Maartens G, Louw VJ, Grebe E. The impact of non-disclosure of HIV status and antiretroviral therapy on HIV recency testing and incidence algorithms. Vox Sang 2024; 119:581-589. [PMID: 38622931 DOI: 10.1111/vox.13627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/16/2024] [Accepted: 03/18/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND AND OBJECTIVES Accurate HIV incidence estimates among blood donors are necessary to assess the effectiveness of programs aimed at limiting transfusion-transmitted HIV. We assessed the impact of undisclosed HIV status and antiretroviral (ARV) use on HIV recency and incidence estimates using increasingly comprehensive recent infection testing algorithms. MATERIALS AND METHODS Using 2017 donation data from first-time and lapsed donors, we populated four HIV recency algorithms: (1) serology and limiting-antigen avidity testing, (2) with individual donation nucleic amplification testing (ID-NAT) added to Algorithm 1, (3) with viral load added to Algorithm 2 and (4) with ARV testing added to Algorithm 3. Algorithm-specific mean durations of recent infection (MDRI) and false recency rates (FRR) were calculated and used to derive and compare incidence estimates. RESULTS Compared with Algorithm 4, progressive algorithms misclassified fewer donors as recent: Algorithm 1: 61 (12.1%); Algorithm 2: 14 (2.8%) and Algorithm 3: 3 (0.6%). Algorithm-specific MDRI and FRR values resulted in marginally lower incidence estimates: Algorithm 1: 0.19% per annum (p.a.) (95% confidence interval [CI]: 0.13%-0.26%); Algorithm 2: 0.18% p.a. (95% CI: 0.13%-0.22%); Algorithm 3: 0.17% p.a. (95% CI: 0.13%-0.22%) and Algorithm 4: 0.17% p.a. (95% CI: 0.13%-0.21%). CONCLUSION We confirmed significant misclassification of recent HIV cases when not including viral load and ARV testing. Context-specific MDRI and FRR resulted in progressively lower incidence estimates but did not fully account for the context-specific variability in incidence modelling. The inclusion of ARV testing, in addition to viral load and ID-NAT testing, did not have a significant impact on incidence estimates.
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Affiliation(s)
- Karin van den Berg
- Medical Division, South African National Blood Service, Roodepoort, South Africa
- Division of Clinical Haematology, Department of Medicine, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa
- Division of Clinical Haematology, University of the Free State, Bloemfontein, South Africa
| | - Edward L Murphy
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
- Department of Epidemiology, University of California, San Francisco, California, USA
- Vitalant Research Institute, San Francisco, California, USA
| | - Gary Maartens
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Vernon J Louw
- Division of Clinical Haematology, Department of Medicine, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa
| | - Eduard Grebe
- Vitalant Research Institute, San Francisco, California, USA
- Eduard Grebe Consulting, Cape Town, South Africa
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Mulenga LB, Hines JZ, Stafford KA, Dzekedzeke K, Sivile S, Lindsay B, Chola M, Ussery F, Patel HK, Abimiku A, Birhanu S, Minchella PA, Stevens T, Hanunka B, Chisenga T, Shibemba A, Fwoloshi S, Siame M, Mutukwa J, Chirwa L, Siwingwa M, Mulundu G, Agbakwuru C, Mapondera P, Detorio M, Agolory SG, Monze M, Bronson M, Charurat ME. Comparison of HIV prevalence, incidence, and viral load suppression in Zambia population-based HIV impact assessments from 2016 and 2021. AIDS 2024; 38:895-905. [PMID: 38227572 DOI: 10.1097/qad.0000000000003834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
BACKGROUND The Zambian government has implemented a public health response to control the HIV epidemic in the country. Zambia conducted a population-based HIV impact assessment (ZAMPHIA) survey in 2021 to assess the status of the HIV epidemic to guide its public health programs. METHODS ZAMPHIA 2021 was a cross-sectional two-stage cluster sample household survey among persons aged ≥15 years conducted in Zambia across all 10 provinces. Consenting participants were administered a standardized questionnaire and whole blood was tested for HIV according to national guidelines. HIV-1 viral load (VL), recent HIV infection, and antiretroviral medications were tested for in HIV-seropositive samples. Viral load suppression (VLS) was defined as <1000 copies/ml. ZAMPHIA 2021 results were compared to ZAMPHIA 2016 for persons aged 15-59 years (i.e., the overlapping age ranges). All estimates were weighted to account for nonresponse and survey design. RESULTS During ZAMPHIA 2021, of 25 483 eligible persons aged ≥15 years, 18 804 (73.8%) were interviewed and tested for HIV. HIV prevalence was 11.0% and VLS prevalence was 86.2% overall, but was <80% among people living with HIV aged 15-24 years and in certain provinces. Among persons aged 15-59 years, from 2016 to 2021, HIV incidence declined from 0.6% to 0.3% ( P -value: 0.07) and VLS prevalence increased from 59.2% to 85.7% ( P -value: <0.01). DISCUSSION Zambia has made substantial progress toward controlling the HIV epidemic from 2016 to 2021. Continued implementation of a test-and-treat strategy, with attention to groups with lower VLS in the ZAMPHIA 2021, could support reductions in HIV incidence and improve overall VLS in Zambia.
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Affiliation(s)
- Lloyd B Mulenga
- Ministry of Health
- University Teaching Hospital
- University of Zambia, School of Medicine
| | - Jonas Z Hines
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Kristen A Stafford
- Center for International Health, Education, and Biosecurity, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kumbutso Dzekedzeke
- Center for International Health, Education, and Biosecurity, Maryland Global Initiatives Corporation-an affiliate of the University of Maryland, Baltimore, Lusaka, Zambia
| | | | - Brianna Lindsay
- Center for International Health, Education, and Biosecurity, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mumbi Chola
- Center for International Health, Education, and Biosecurity, Maryland Global Initiatives Corporation-an affiliate of the University of Maryland, Baltimore, Lusaka, Zambia
| | - Faith Ussery
- U.S. Centers for Disease Control and Prevention, Atlanta, USA
| | - Hetal K Patel
- U.S. Centers for Disease Control and Prevention, Atlanta, USA
| | - Alash'le Abimiku
- Center for International Health, Education, and Biosecurity, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Sehin Birhanu
- U.S. Centers for Disease Control and Prevention, Atlanta, USA
| | | | - Thomas Stevens
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Brave Hanunka
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | | | | | | | | | | | | | - Mpanji Siwingwa
- University Teaching Hospital
- University of Zambia, School of Medicine
| | - Gina Mulundu
- University Teaching Hospital
- University of Zambia, School of Medicine
| | - Chinedu Agbakwuru
- Center for International Health, Education, and Biosecurity, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Prichard Mapondera
- Center for International Health, Education, and Biosecurity, Maryland Global Initiatives Corporation-an affiliate of the University of Maryland, Baltimore, Lusaka, Zambia
| | - Mervi Detorio
- U.S. Centers for Disease Control and Prevention, Atlanta, USA
| | - Simon G Agolory
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Mwaka Monze
- Ministry of Health
- University Teaching Hospital
| | - Megan Bronson
- U.S. Centers for Disease Control and Prevention, Atlanta, USA
| | - Man E Charurat
- Center for International Health, Education, and Biosecurity, Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
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Mhlanga L, Welte A, Grebe E, Ohler L, Van Cutsem G, Huerga H, Conan N. Evidence of HIV incidence reduction in young women, but not in adolescent girls, in KwaZulu-Natal, South Africa. IJID REGIONS 2023; 8:111-117. [PMID: 37577330 PMCID: PMC10415685 DOI: 10.1016/j.ijregi.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023]
Abstract
Objectives We estimated changes in the HIV incidence from 2013-2018 in Eshowe/Mbongolwane, KwaZulu-Natal, South Africa where Médecins Sans Frontières is engaged in providing HIV testing and care since 2011. Methods Using data from two cross-sectional household-based surveys conducted in 2013 and 2018, with consenting participants aged 15-59 years, we applied the incidence estimation frameworks of Mahiane et al and Kassanjee et al. Results In total, 5599 (62.4% women) and 3276 (65.9% women) individuals were included in 2013 and 2018, respectively. We found a mean incidence in women aged 20-29 years of 2.71 cases per 100 person-years (95% confidence interval [CI]: 1.23;4.19) in 2013 and 0.4 cases per 100 person-years (95% CI: 0.0;1.5) in 2018. The incidence in men aged 20-29 years was 1.91 cases per 100 person-years (95% CI: 0.87; 2.93) in 2013 and 0.53 cases per 100 person-years (95% CI: 0.0; 1.4) in 2018. The incidence decline among women aged 15-19 was -0.34 cases per 100 person-years (95% CI: -1.31;0.64). Conclusions The lack of evidence of incidence decline among adolescent girls is noteworthy and disconcerting. Our findings suggest that large-scale surveys should seriously consider focusing their resources on the core group of women aged 15-19 years.
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Affiliation(s)
- Laurette Mhlanga
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- NorthWestern University, Illinois, USA
| | - Alex Welte
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Eduard Grebe
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- Vitalant Research Institute, San Fransico, USA
- University of California, San Francisco, USA
| | | | - Gilles Van Cutsem
- Médecins sans Frontières, Southern Africa Medical Unit, Cape Town, South Africa
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, South Africa
| | - Helena Huerga
- Interventional Epidemiology Department, Epicentre, Paris, France
| | - Nolwenn Conan
- Interventional Epidemiology Department, Epicentre, Paris, France
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Fellows IE, Hladik W, Eaton JW, Voetsch AC, Parekh BS, Shiraishi RW. Improving Biomarker-based HIV Incidence Estimation in the Treatment Era. Epidemiology 2023; 34:353-364. [PMID: 36863062 PMCID: PMC10069749 DOI: 10.1097/ede.0000000000001604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 02/08/2023] [Indexed: 03/04/2023]
Abstract
BACKGROUND Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for false recency rate (FRR) and mean duration of recent infection (MDRI) after applying a recent infection testing algorithm (RITA). METHODS This article shows how testing and diagnosis reduce both FRR and mean duration of recent infection compared to a treatment-naive population. A new method is proposed for calculating appropriate context-specific estimates of FRR and mean duration of recent infection. The result of this is a new formula for incidence that depends only on reference FRR and mean duration of recent infection parameters derived in an undiagnosed, treatment-naive, nonelite controller, non-AIDS-progressed population. RESULTS Applying the methodology to eleven cross-sectional surveys in Africa results in good agreement with previous incidence estimates, except in 2 countries with very high reported testing rates. CONCLUSIONS Incidence estimation equations can be adapted to account for the dynamics of treatment and recent infection testing algorithms. This provides a rigorous mathematical foundation for the application of HIV recency assays in cross-sectional surveys.
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Affiliation(s)
- Ian E. Fellows
- From the Fellows Statistics, San Diego, CA
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA
| | - Wolfgang Hladik
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA
| | - Jeffrey W. Eaton
- MRC Centre for Global Infectious Disease Analysis, School of Public Health Imperial College London, London, United Kingdom
| | - Andrew C. Voetsch
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA
| | - Bharat S. Parekh
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA
| | - Ray W. Shiraishi
- MRC Centre for Global Infectious Disease Analysis, School of Public Health Imperial College London, London, United Kingdom
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Gurley SA, Stupp PW, Fellows IE, Parekh BS, Young PW, Shiraishi RW, Sullivan PS, Voetsch AC. Estimation of HIV-1 Incidence Using a Testing History-Based Method; Analysis From the Population-Based HIV Impact Assessment Survey Data in 12 African Countries. J Acquir Immune Defic Syndr 2023; 92:189-196. [PMID: 36730779 PMCID: PMC9911103 DOI: 10.1097/qai.0000000000003123] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/18/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND Estimating HIV incidence is essential to monitoring progress in sub-Saharan African nations toward global epidemic control. One method for incidence estimation is to test nationally representative samples using laboratory-based incidence assays. An alternative method based on reported HIV testing history and the proportion of undiagnosed infections has recently been described. METHODS We applied an HIV incidence estimation method which uses history of testing to nationally representative cross-sectional survey data from 12 sub-Saharan African nations with varying country-specific HIV prevalence. We compared these estimates with those derived from laboratory-based incidence assays. Participants were tested for HIV using the national rapid test algorithm and asked about prior HIV testing, date and result of their most recent test, and date of antiretroviral therapy initiation. RESULTS The testing history-based method consistently produced results that are comparable and strongly correlated with estimates produced using a laboratory-based HIV incidence assay (ρ = 0.85). The testing history-based method produced incidence estimates that were more precise compared with the biomarker-based method. The testing history-based method identified sex-, age-, and geographic location-specific differences in incidence that were not detected using the biomarker-based method. CONCLUSIONS The testing history-based method estimates are more precise and can produce age-specific and sex-specific incidence estimates that are informative for programmatic decisions. The method also allows for comparisons of the HIV transmission rate and other components of HIV incidence among and within countries. The testing history-based method is a useful tool for estimating and validating HIV incidence from cross-sectional survey data.
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Affiliation(s)
- Stephen A. Gurley
- Rollins School of Public Health, Emory University, Atlanta, GA
- Emory University School of Medicine, Atlanta, GA
| | - Paul W. Stupp
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
| | - Ian E. Fellows
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
- Fellows Statistics Inc., San Diego, CA; and
| | - Bharat S. Parekh
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
| | - Peter W. Young
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, Maputo, Mozambique
| | - Ray W. Shiraishi
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
| | | | - Andrew C. Voetsch
- Rollins School of Public Health, Emory University, Atlanta, GA
- Division of Global HIV&TB, United States Centers for Disease Control and Prevention, Atlanta, GA
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Rosenberg NE, Shook-Sa BE, Liu M, Stranix-Chibanda L, Yotebieng M, Sam-Agudu NA, Hudgens MG, Phiri SJ, Mutale W, Bekker LG, Moyo S, Zuma K, Charurat ME, Justman J, Chi BH. Adult HIV-1 incidence across 15 high-burden countries in sub-Saharan Africa from 2015 to 2019: a pooled analysis of nationally representative data. Lancet HIV 2023; 10:e175-e185. [PMID: 36702151 PMCID: PMC10126805 DOI: 10.1016/s2352-3018(22)00328-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 10/13/2022] [Accepted: 10/27/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND Harmonised population-based surveys with recent HIV-1 infection testing algorithms permit pooled cross-sectional estimation of HIV incidence across multiple countries. We aimed to estimate adult HIV-1 incidence rates and number of new infections by sex, age, and subregion in sub-Saharan Africa. METHODS We analysed data from 13 Population-Based HIV Impact Assessment (PHIA) surveys and two additional population-based surveys done between 2015 and 2019 in 15 sub-Saharan African countries. HIV-seropositive samples from adults aged 15-59 years were tested for recent HIV-1 infection by use of an algorithm consisting of the HIV-1 limiting antigen avidity enzyme immunoassay, HIV-1 viral load, and qualitative detection of antiretroviral agents. Data were pooled across countries; sampling weights were incorporated to represent all adults in the 15 national populations. Analyses accounted for the complex sample designs. HIV incidence rates, incidence rate differences, and number of new annual infections were estimated. FINDINGS Among 445 979 adults sampled, 382 had recent HIV-1 infection. The estimated HIV-1 incidence rate was 3·3 per 1000 person-years (95% CI 2·6-4·0) among women and 2·0 per 1000 person-years (1·2-2·7) among men (incidence rate difference 1·3 per 1000 person-years, 95% CI 0·3-2·3). Among adults aged 15-24 years, the incidence rate was higher for women (3·5 per 1000 person-years) than men (1·2 per 1000 person-years; difference 2·3, 95% CI 0·8-3·8), but infection rates were similar between sexes in all other age groups. The HIV-1 incidence rate was 7·4 per 1000 person-years (95% CI 5·0-9·7) in southern sub-Saharan Africa, 2·3 per 1000 person-years (1·7-2·9) in the eastern subregion, and 0·9 per 1000 person-years (0·6-1·2) in the western and central subregion. 689 000 (95% CI 546 000-833 000) new HIV cases were estimated annually among the 265 million susceptible adults (61·6% in women). INTERPRETATION HIV-1 incidence and number of new infections differed by age, sex, and subregion. Approaches for risk stratification are needed to guide comprehensive HIV-1 prevention. FUNDING National Institutes of Health.
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Affiliation(s)
- Nora E Rosenberg
- Department of Health Behavior, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Bonnie E Shook-Sa
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mincen Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lynda Stranix-Chibanda
- Child and Adolescent Health Unit, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe; University of Zimbabwe Clinical Trials Research Centre, Harare, Zimbabwe
| | - Marcel Yotebieng
- Division of General Internal Medicine, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Nadia A Sam-Agudu
- Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA; International Research Center of Excellence, Institute of Human Virology Nigeria, Abuja, Nigeria
| | - Michael G Hudgens
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sam J Phiri
- Partners in Hope, Lilongwe, Malawi; Department of Public Health and Family Medicine, Kamuzu University of Health Sciences, Lilongwe, Malawi
| | | | | | - Sizulu Moyo
- University of Cape Town, Cape Town, South Africa; Human Sciences Research Council, Pretoria, South Africa
| | | | - Manhattan E Charurat
- Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jessica Justman
- ICAP at Columbia, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Benjamin H Chi
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Sheng B, Li C, Bao L, Li R. Probabilistic HIV recency classification-a logistic regression without labeled individual level training data. Ann Appl Stat 2023; 17:108-129. [PMID: 37846343 PMCID: PMC10577400 DOI: 10.1214/22-aoas1618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2023]
Abstract
Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest risk of new infection, and evaluating existing programs of prevention and treatment. Starting from 2015, the Population-based HIV Impact Assessment (PHIA) individual-level surveys are implemented in the most-affected countries in sub-Saharan Africa. PHIA is a nationally-representative HIV-focused survey that combines household visits with key questions and cutting-edge technologies such as biomarker tests for HIV antibody and HIV viral load which offer the unique opportunity of distinguishing between recent infection and long-term infection, and providing relevant HIV information by age, gender, and location. In this article, we propose a semi-supervised logistic regression model for estimating individual level HIV recency status. It incorporates information from multiple data sources - the PHIA survey where the true HIV recency status is unknown, and the cohort studies provided in the literature where the relationship between HIV recency status and the covariates are presented in the form of a contingency table. It also utilizes the national level HIV incidence estimates from the epidemiology model. Applying the proposed model to Malawi PHIA data, we demonstrate that our approach is more accurate for the individual level estimation and more appropriate for estimating HIV recency rates at aggregated levels than the current practice - the binary classification tree (BCT).
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Affiliation(s)
- Ben Sheng
- Department of Statistics, Penn State University, University Park, PA, USA
| | - Changcheng Li
- School of Mathematical Sciences, Dalian University of Technology Dalian, P.R. China
| | - Le Bao
- Department of Statistics, Penn State University, University Park, PA, USA
| | - Runze Li
- Department of Statistics, Penn State University, University Park, PA, USA
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Young PW, Musingila P, Kingwara L, Voetsch AC, Zielinski-Gutierrez E, Bulterys M, Kim AA, Bronson MA, Parekh BS, Dobbs T, Patel H, Reid G, Achia T, Keter A, Mwalili S, Ogollah FM, Ondondo R, Longwe H, Chege D, Bowen N, Umuro M, Ngugi C, Justman J, Cherutich P, De Cock KM. HIV Incidence, Recent HIV Infection, and Associated Factors, Kenya, 2007-2018. AIDS Res Hum Retroviruses 2023; 39:57-67. [PMID: 36401361 PMCID: PMC9942172 DOI: 10.1089/aid.2022.0054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Nationally representative surveys provide an opportunity to assess trends in recent human immunodeficiency virus (HIV) infection based on assays for recent HIV infection. We assessed HIV incidence in Kenya in 2018 and trends in recent HIV infection among adolescents and adults in Kenya using nationally representative household surveys conducted in 2007, 2012, and 2018. To assess trends, we defined a recent HIV infection testing algorithm (RITA) that classified as recently infected (<12 months) those HIV-positive participants that were recent on the HIV-1 limiting antigen (LAg)-avidity assay without evidence of antiretroviral use. We assessed factors associated with recent and long-term (≥12 months) HIV infection versus no infection using a multinomial logit model while accounting for complex survey design. Of 1,523 HIV-positive participants in 2018, 11 were classified as recent. Annual HIV incidence was 0.14% in 2018 [95% confidence interval (CI) 0.057-0.23], representing 35,900 (95% CI 16,300-55,600) new infections per year in Kenya among persons aged 15-64 years. The percentage of HIV infections that were determined to be recent was similar in 2007 and 2012 but fell significantly from 2012 to 2018 [adjusted odds ratio (aOR) = 0.31, p < .001]. Compared to no HIV infection, being aged 25-34 versus 35-64 years (aOR = 4.2, 95% CI 1.4-13), having more lifetime sex partners (aOR = 5.2, 95% CI 1.6-17 for 2-3 partners and aOR = 8.6, 95% CI 2.8-26 for ≥4 partners vs. 0-1 partners), and never having tested for HIV (aOR = 4.1, 95% CI 1.5-11) were independently associated with recent HIV infection. Although HIV remains a public health priority in Kenya, HIV incidence estimates and trends in recent HIV infection support a significant decrease in new HIV infections from 2012 to 2018, a period of rapid expansion in HIV diagnosis, prevention, and treatment.
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Affiliation(s)
- Peter Wesley Young
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Maputo, Mozambique.,Address correspondence to: Peter Wesley Young, U.S. Embassy Maputo, Avenida Marginal nr 5467, Sommerschield, Distrito Municipal de KaMpfumo, Caixa Postal 783, CEP 0101-11 Maputo, Mozambique
| | - Paul Musingila
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Leonard Kingwara
- National AIDS & STI Control Programme, Ministry of Health, Nairobi, Kenya
| | - Andrew C. Voetsch
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Emily Zielinski-Gutierrez
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya.,Central America Regional Office, U.S. Centers for Disease Control and Prevention, Guatemala City, Guatemala
| | - Marc Bulterys
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Andrea A. Kim
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Megan A. Bronson
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Bharat S. Parekh
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Trudy Dobbs
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Hetal Patel
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Giles Reid
- Survey Unit, ICAP at Columbia University, New York, New York, USA
| | - Thomas Achia
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Alfred Keter
- National AIDS & STI Control Programme, Ministry of Health, Nairobi, Kenya
| | - Samuel Mwalili
- Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Juja, Kenya
| | | | - Raphael Ondondo
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Herbert Longwe
- Survey Unit, ICAP at Columbia University, New York, New York, USA
| | - Duncan Chege
- Survey Unit, ICAP at Columbia University, New York, New York, USA
| | - Nancy Bowen
- National Public Health Laboratory, Ministry of Health, Nairobi, Kenya
| | - Mamo Umuro
- National Public Health Laboratory, Ministry of Health, Nairobi, Kenya
| | | | - Jessica Justman
- Survey Unit, ICAP at Columbia University, New York, New York, USA
| | | | - Kevin M. De Cock
- Division of Global HIV & TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
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11
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Parkin N, Gao F, Grebe E, Cutrell A, Das M, Donnell D, Duerr A, Glidden DV, Hughes JP, Murray J, Robertson MN, Zinserling J, Lau J, Miller V. Facilitating Next-Generation Pre-Exposure Prophylaxis Clinical Trials Using HIV Recent Infection Assays: A Consensus Statement from the Forum HIV Prevention Trial Design Project. Clin Pharmacol Ther 2022. [PMID: 36550769 DOI: 10.1002/cpt.2830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
Standard-of-care HIV pre-exposure prophylaxis (PrEP) is highly efficacious, but uptake of and persistence on a daily oral pill is low in many settings. Evaluation of alternate PrEP products will require innovation to avoid the unpractically large sample sizes in noninferiority trials. We propose estimating HIV incidence in people not on PrEP as an external counterfactual to which on-PrEP incidence in trial subjects can be compared. HIV recent infection testing algorithms (RITAs), such as the limiting antigen avidity assay plus viral load used on specimens from untreated HIV positive people identified during screening, is one possible approach. Its feasibility is partly dependent on the sample size needed to ensure adequate power, which is impacted by RITA performance, the number of recent infections identified, the expected efficacy of the intervention, and other factors. Screening sample sizes to support detection of an 80% reduction in incidence for 3 key populations are more modest, and comparable to the number of participants in recent phase III PrEP trials. Sample sizes would be significantly larger in populations with lower incidence, where the false recency rate is higher or if PrEP efficacy is expected to be lower. Our proposed counterfactual approach appears to be feasible, offers high statistical power, and is nearly contemporaneous with the on-PrEP population. It will be important to monitor the performance of this approach during new product development for HIV prevention. If successful, it could be a model for preventive HIV vaccines and prevention of other infectious diseases.
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Affiliation(s)
- Neil Parkin
- Data First Consulting, Sebastopol, California, USA
| | - Fei Gao
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Eduard Grebe
- Vitalant Research Institute, San Francisco, California, USA.,Edward Grebe Consulting, Cape Town, South Africa
| | - Amy Cutrell
- ViiV Healthcare, Research Triangle Park, North Carolina, USA
| | - Moupali Das
- Gilead Sciences, Foster City, California, USA
| | - Deborah Donnell
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Ann Duerr
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | | | | | | | | | - Joerg Zinserling
- Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM), Bonn, Germany
| | - Joseph Lau
- Forum for Collaborative Research, Washington, DC, USA
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12
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Grant-McAuley W, Laeyendecker O, Monaco D, Chen A, Hudelson SE, Klock E, Brookmeyer R, Morrison D, Piwowar-Manning E, Morrison CS, Hayes R, Ayles H, Bock P, Kosloff B, Shanaube K, Mandla N, van Deventer A, Ruczinski I, Kammers K, Larman HB, Eshleman SH. Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment. BMC Infect Dis 2022; 22:838. [PMID: 36368950 PMCID: PMC9652879 DOI: 10.1186/s12879-022-07850-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 11/07/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Multi-assay algorithms (MAAs) are used to estimate population-level HIV incidence and identify individuals with recent infection. Many MAAs use low viral load (VL) as a biomarker for long-term infection. This could impact incidence estimates in settings with high rates of early HIV treatment initiation. We evaluated the performance of two MAAs that do not include VL. METHODS Samples were collected from 219 seroconverters (infected < 1 year) and 4376 non-seroconverters (infected > 1 year) in the HPTN 071 (PopART) trial; 28.8% of seroconverter samples and 73.2% of non-seroconverter samples had VLs ≤ 400 copies/mL. Samples were tested with the Limiting Antigen Avidity assay (LAg) and JHU BioRad-Avidity assays. Antibody reactivity to two HIV peptides was measured using the MSD U-PLEX assay. Two MAAs were evaluated that do not include VL: a MAA that includes the LAg-Avidity assay and BioRad-Avidity assay (LAg + BR) and a MAA that includes the LAg-Avidity assay and two peptide biomarkers (LAg + PepPair). Performance of these MAAs was compared to a widely used MAA that includes LAg and VL (LAg + VL). RESULTS The incidence estimate for LAg + VL (1.29%, 95% CI: 0.97-1.62) was close to the observed longitudinal incidence (1.34% 95% CI: 1.17-1.53). The incidence estimates for the other two MAAs were higher (LAg + BR: 2.56%, 95% CI 2.01-3.11; LAg + PepPair: 2.84%, 95% CI: 1.36-4.32). LAg + BR and LAg + PepPair also misclassified more individuals infected > 2 years as recently infected than LAg + VL (1.2% [42/3483 and 1.5% [51/3483], respectively, vs. 0.2% [6/3483]). LAg + BR classified more seroconverters as recently infected than LAg + VL or LAg + PepPair (80 vs. 58 and 50, respectively) and identified ~ 25% of virally suppressed seroconverters as recently infected. CONCLUSIONS The LAg + VL MAA produced a cross-sectional incidence estimate that was closer to the longitudinal estimate than two MAAs that did not include VL. The LAg + BR MAA classified the greatest number of individual seroconverters as recently infected but had a higher false recent rate.
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Affiliation(s)
- Wendy Grant-McAuley
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Monaco
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Athena Chen
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sarah E Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ethan Klock
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ron Brookmeyer
- Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Douglas Morrison
- Department of Public Health Sciences, UC Davis School of Medicine, Davis, CA, USA
| | | | - Charles S Morrison
- Behavioral, Epidemiologic, and Clinical Sciences, Durham, NC, FHI 360, USA
| | - Richard Hayes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Helen Ayles
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Peter Bock
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Barry Kosloff
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Kwame Shanaube
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
| | - Nomtha Mandla
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Anneen van Deventer
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Kai Kammers
- Division of Biostatistics and Bioinformatics, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - H Benjamin Larman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan H Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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13
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Kassanjee R, Welte A, Otwombe K, Jaffer M, Milovanovic M, Hlongwane K, Puren AJ, Hill N, Mbowane V, Dunkle K, Gray G, Abdullah F, Jewkes R, Coetzee J. HIV incidence estimation among female sex workers in South Africa: a multiple methods analysis of cross-sectional survey data. Lancet HIV 2022; 9:e781-e790. [PMID: 36075252 PMCID: PMC9626386 DOI: 10.1016/s2352-3018(22)00201-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Although numerous studies have investigated HIV risk factors and shown high HIV prevalence among female sex workers in South Africa, no national HIV incidence estimate exists for this potentially important group for HIV transmission. We aimed to estimate HIV incidence among female sex workers in South Africa who could be accessed through sex worker programmes, and to refine and describe the methods that enabled analysis. METHODS This study was embedded in a cross-sectional national survey of female sex workers who were linked to sex worker programmes. We aimed to enrol 3000 female sex workers aged at least 18 years who had sold or transacted in sex in the preceding 6 months in 12 randomly selected districts of the 22 districts with sex worker programmes, ensuring coverage of all provinces of South Africa. Women who self-reported as current victims of human trafficking were excluded from enrolment. We used a multistep process to sample districts and then hotspots, and a chain referral method to recruit participants. We collected cross-sectional data for self-reported HIV status, demographic characteristics, and exposure to violence. Two rapid tests were used to ascertain diagnostic markers, a viral load assay was used to ascertain clinical markers, and the Maxim Limiting Antigen Avidity EIA was used to ascertain infection-staging HIV markers. Given the challenges of estimating HIV incidence, especially cross-sectionally, multiple methods of estimation were adapted to our setting, leveraging the age structure of HIV prevalence, recency-of -infection biomarker results (ie, where recent infection is classified as ≤1·5 normalised optical density [ODn] on the avidity assay and viral load of ≥1000 copies per mL), and reported testing histories. FINDINGS Of 3005 female sex workers who were enrolled and interviewed between Feb 4 and June 26, 2019, 2999 who had HIV test results were included in this analysis. The median age of participants was 32 years (IQR 27-38). 1714 (57·2%) of 2999 participants self-reported as being HIV positive, and 1447 (48·3%) of 2993 participants reported client sexual violence in the past year. The measured HIV prevalence was 62·1% (95% CI 60·3-65·7) and peaked at approximately age 40 years. Using recency-of-infection biomarker results, we obtained a base case estimate of HIV incidence of 4·60 cases per 100 person-years (95% CI 1·53-8·45) for the population. Estimates were generally consistent by method, and outlying incidence estimates calculated by self-reported testing histories were considered unreliable. Various sensitivity analyses produced estimates up to 11 cases per 100 person-years, and we did not detect differences by age and region. INTERPRETATION We found that female sex workers have extraordinarily high HIV incidence of approximately 5 cases per 100 person-years, emphasising the need to sustain and strengthen efforts to mitigate risk and provide adequate care. The notable role that sex work has in HIV transmission demands substantial investment in ongoing epidemiological monitoring. FUNDING South African Medical Research Council, South African National Treasury, Global Fund, South African Department of Science and Innovation, Wellcome Trust.
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Affiliation(s)
- Reshma Kassanjee
- Centre for Infectious Disease Epidemiology and Research, School of Public Health, University of Cape Town, Cape Town, South Africa; The South African Department of Science and Innovation-National Research Foundation, Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa.
| | - Alex Welte
- The South African Department of Science and Innovation-National Research Foundation, Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
| | - Kennedy Otwombe
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Maya Jaffer
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Minja Milovanovic
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; African Potential Management Consultancy, Kyalami, South Africa
| | - Khuthadzo Hlongwane
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Adrian J Puren
- South African National Institute for Communicable Diseases, Johannesburg, South Africa
| | - Naomi Hill
- Wits Reproductive Health Institute, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Venice Mbowane
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kristin Dunkle
- South African Medical Research Council, Cape Town, South Africa
| | - Glenda Gray
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; South African Medical Research Council, Cape Town, South Africa
| | - Fareed Abdullah
- South African Medical Research Council, Cape Town, South Africa
| | - Rachel Jewkes
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; South African Medical Research Council, Cape Town, South Africa
| | - Jenny Coetzee
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; African Potential Management Consultancy, Kyalami, South Africa; South African Medical Research Council, Cape Town, South Africa
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14
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Building an integrated serosurveillance platform to inform public health interventions: Insights from an experts' meeting on serum biomarkers. PLoS Negl Trop Dis 2022; 16:e0010657. [PMID: 36201428 PMCID: PMC9536637 DOI: 10.1371/journal.pntd.0010657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 16 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group's insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.
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15
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Sempa JB, Grebe E, Welte A. Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis. PLoS One 2022; 17:e0271763. [PMID: 35901053 PMCID: PMC9333292 DOI: 10.1371/journal.pone.0271763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 07/06/2022] [Indexed: 11/18/2022] Open
Abstract
Background
Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data.
Methods
It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data.
Results
We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result.
Conclusion
Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other.
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Affiliation(s)
- Joseph B. Sempa
- Faculty of Health Sciences, Department of Biostatistics, University of the Free State, Bloemfontein, South Africa
- South African Department of Science and Technology—National Research Foundation Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
- * E-mail:
| | - Eduard Grebe
- South African Department of Science and Technology—National Research Foundation Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
- Vitalant Research Institute, San Francisco, California, United States of America
| | - Alex Welte
- South African Department of Science and Technology—National Research Foundation Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
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16
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Facente SN, Grebe E, Maher AD, Fox D, Scheer S, Mahy M, Dalal S, Lowrance D, Marsh K. Use of HIV Recency Assays for HIV Incidence Estimation and Other Surveillance Use Cases: Systematic Review. JMIR Public Health Surveill 2022; 8:e34410. [PMID: 35275085 PMCID: PMC8956992 DOI: 10.2196/34410] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/16/2022] [Accepted: 02/02/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND HIV assays designed to detect recent infection, also known as "recency assays," are often used to estimate HIV incidence in a specific country, region, or subpopulation, alone or as part of recent infection testing algorithms (RITAs). Recently, many countries and organizations have become interested in using recency assays within case surveillance systems and routine HIV testing services to measure other indicators beyond incidence, generally referred to as "non-incidence surveillance use cases." OBJECTIVE This review aims to identify published evidence that can be used to validate methodological approaches to recency-based incidence estimation and non-incidence use cases. The evidence identified through this review will be used in the forthcoming technical guidance by the World Health Organization (WHO) and United Nations Programme on HIV/AIDS (UNAIDS) on the use of HIV recency assays for identification of epidemic trends, whether for HIV incidence estimation or non-incidence indicators of recency. METHODS To identify the best methodological and field implementation practices for the use of recency assays to estimate HIV incidence and trends in recent infections for specific populations or geographic areas, we conducted a systematic review of the literature to (1) understand the use of recency testing for surveillance in programmatic and laboratory settings, (2) review methodologies for implementing recency testing for both incidence estimation and non-incidence use cases, and (3) assess the field performance characteristics of commercially available recency assays. RESULTS Among the 167 documents included in the final review, 91 (54.5%) focused on assay or algorithm performance or methodological descriptions, with high-quality evidence of accurate age- and sex-disaggregated HIV incidence estimation at national or regional levels in general population settings, but not at finer geographic levels for prevention prioritization. The remaining 76 (45.5%) described the field use of incidence assays including field-derived incidence (n=45), non-incidence (n=25), and both incidence and non-incidence use cases (n=6). The field use of incidence assays included integrating RITAs into routine surveillance and assisting with molecular genetic analyses, but evidence was generally weaker or only reported on what was done, without validation data or findings related to effectiveness of using non-incidence indicators calculated through the use of recency assays as a proxy for HIV incidence. CONCLUSIONS HIV recency assays have been widely validated for estimating HIV incidence in age- and sex-specific populations at national and subnational regional levels; however, there is a lack of evidence validating the accuracy and effectiveness of using recency assays to identify epidemic trends in non-incidence surveillance use cases. More research is needed to validate the use of recency assays within HIV testing services, to ensure findings can be accurately interpreted to guide prioritization of public health programming.
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Affiliation(s)
- Shelley N Facente
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, United States.,Facente Consulting, Richmond, CA, United States.,Vitalant Research Institute, San Francisco, CA, United States
| | - Eduard Grebe
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, United States.,Vitalant Research Institute, San Francisco, CA, United States.,South African Centre for Epidemiological Modeling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Andrew D Maher
- South African Centre for Epidemiological Modeling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa.,Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, United States
| | - Douglas Fox
- Facente Consulting, Richmond, CA, United States
| | | | - Mary Mahy
- Strategic Information Department, The Joint United Nations Programme on HIV/AIDS (UNAIDS), Geneva, Switzerland
| | - Shona Dalal
- Global HIV, Hepatitis and Sexually Transmitted Infections Programmes, World Health Organisation, Geneva, Switzerland
| | - David Lowrance
- Global HIV, Hepatitis and Sexually Transmitted Infections Programmes, World Health Organisation, Geneva, Switzerland
| | - Kimberly Marsh
- Strategic Information Department, The Joint United Nations Programme on HIV/AIDS (UNAIDS), Geneva, Switzerland
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17
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Gao F, Bannick M. Statistical considerations for cross-sectional HIV incidence estimation based on recency test. Stat Med 2022; 41:1446-1461. [PMID: 34984710 PMCID: PMC8918003 DOI: 10.1002/sim.9296] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/22/2021] [Accepted: 12/08/2021] [Indexed: 11/08/2022]
Abstract
Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional sample to infer whether they are "recently" infected and to estimate incidence in the population. Two main estimators have been used in practice: one that assumes a recency test is perfectly specific, and another that allows for false-recent results. To date, these commonly used estimators have not been rigorously studied with respect to their assumptions and statistical properties. In this article, we present a theoretical framework with which to understand these estimators and interrogate their assumptions, and perform a simulation study and data analysis to assess the performance of these estimators under realistic HIV epidemiological dynamics. We find that the snapshot estimator and the adjusted estimator perform well when their corresponding assumptions hold. When assumptions on constant incidence and recency test characteristics fail to hold, the adjusted estimator is more robust than the snapshot estimator. We conclude with recommendations for the use of these estimators in practice and a discussion of future methodological developments to improve HIV incidence estimation via recency test.
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Affiliation(s)
- Fei Gao
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Marlena Bannick
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
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Eaton JW, Dwyer‐Lindgren L, Gutreuter S, O'Driscoll M, Stevens O, Bajaj S, Ashton R, Hill A, Russell E, Esra R, Dolan N, Anifowoshe YO, Woodbridge M, Fellows I, Glaubius R, Haeuser E, Okonek T, Stover J, Thomas ML, Wakefield J, Wolock TM, Berry J, Sabala T, Heard N, Delgado S, Jahn A, Kalua T, Chimpandule T, Auld A, Kim E, Payne D, Johnson LF, FitzJohn RG, Wanyeki I, Mahy MI, Shiraishi RW. Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa. J Int AIDS Soc 2021; 24 Suppl 5:e25788. [PMID: 34546657 PMCID: PMC8454682 DOI: 10.1002/jia2.25788] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 07/19/2021] [Indexed: 11/23/2022] Open
Abstract
INTRODUCTION HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups. METHODS Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016-2018. RESULTS Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty-eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city. CONCLUSIONS The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.
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19
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Voetsch AC, Duong YT, Stupp P, Saito S, McCracken S, Dobbs T, Winterhalter FS, Williams DB, Mengistu A, Mugurungi O, Chikwanda P, Musuka G, Ndongmo CB, Dlamini S, Nuwagaba-Biribonwoha H, Pasipamire M, Tegbaru B, Eshetu F, Biraro S, Ward J, Aibo D, Kabala A, Mgomella GS, Malewo O, Mushi J, Payne D, Mengistu Y, Asiimwe F, Shang J, Dokubo EK, Eno LT, Bissek ACZK, Kingwara L, Junghae M, Kiiru JN, Mwesigwa R, Balachandra S, Lobognon R, Kampira E, Detorio M, Yufenyuy EL, Brown K, Patel HK, Parekh BS. HIV-1 Recent Infection Testing Algorithm With Antiretroviral Drug Detection to Improve Accuracy of Incidence Estimates. J Acquir Immune Defic Syndr 2021; 87:S73-S80. [PMID: 34166315 PMCID: PMC8630595 DOI: 10.1097/qai.0000000000002707] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND HIV-1 incidence calculation currently includes recency classification by HIV-1 incidence assay and unsuppressed viral load (VL ≥ 1000 copies/mL) in a recent infection testing algorithm (RITA). However, persons with recent classification not virally suppressed and taking antiretroviral (ARV) medication may be misclassified. SETTING We used data from 13 African household surveys to describe the impact of an ARV-adjusted RITA on HIV-1 incidence estimates. METHODS HIV-seropositive samples were tested for recency using the HIV-1 Limiting Antigen (LAg)-Avidity enzyme immunoassay, HIV-1 viral load, ARVs used in each country, and ARV drug resistance. LAg-recent result was defined as normalized optical density values ≤1.5. We compared HIV-1 incidence estimates using 2 RITA: RITA1: LAg-recent + VL ≥ 1000 copies/mL and RITA2: RITA1 + undetectable ARV. We explored RITA2 with self-reported ARV use and with clinical history. RESULTS Overall, 357 adult HIV-positive participants were classified as having recent infection with RITA1. RITA2 reclassified 55 (15.4%) persons with detectable ARV as having long-term infection. Those with detectable ARV were significantly more likely to be aware of their HIV-positive status (84% vs. 10%) and had higher levels of drug resistance (74% vs. 26%) than those without detectable ARV. RITA2 incidence was lower than RITA1 incidence (range, 0%-30% decrease), resulting in decreased estimated new infections from 390,000 to 341,000 across the 13 countries. Incidence estimates were similar using detectable or self-reported ARV (R2 > 0.995). CONCLUSIONS Including ARV in RITA2 improved the accuracy of HIV-1 incidence estimates by removing participants with likely long-term HIV infection.
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Affiliation(s)
- Andrew C. Voetsch
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Paul Stupp
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Suzue Saito
- ICAP at Columbia University, New York, NY, USA
| | - Stephen McCracken
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Trudy Dobbs
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Daniel B. Williams
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Prisca Chikwanda
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Clement B. Ndongmo
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sindisiwe Dlamini
- National Reference Laboratory, Ministry of Health, Mbabane, Eswatini
| | | | - Munyaradzi Pasipamire
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Frehywot Eshetu
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sam Biraro
- ICAP at Columbia University, New York, NY, USA
| | - Jennifer Ward
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - George S. Mgomella
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Optatus Malewo
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Danielle Payne
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Yohannes Mengistu
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Fred Asiimwe
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Judith Shang
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Emily Kainne Dokubo
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Laura T. Eno
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Anne-Cécile Zoung-Kanyi Bissek
- Division of Health Operations Research, Ministry of Public Health, Yaoundé, Cameroon
- Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - Leonard Kingwara
- Division of National AIDS and STI Control Program, Nairobi, Kenya
| | - Muthoni Junghae
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - John N. Kiiru
- National Public Health Laboratory, Ministry of Health, Nairobi, Kenya
| | - Richard Mwesigwa
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Shirish Balachandra
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Roger Lobognon
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Elizabeth Kampira
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Mervi Detorio
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ernest L. Yufenyuy
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Kristin Brown
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hetal K. Patel
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Bharat S. Parekh
- Division of Global HIV & TB, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Hines JZ, Sachathep K, Pals S, Davis SM, Toledo C, Bronson M, Parekh B, Carrasco M, Xaba S, Mandisarisa J, Kamobyi R, Chituwo O, Kirungi WL, Alamo S, Kabuye G, Awor AC, Mmbando S, Simbeye D, Aupokolo MA, Zemburuka B, Nyirenda R, Msungama W, Tarumbiswa T, Manda R, Nuwagaba-Biribonwoha H, Kiggundu V, Thomas AG, Watts H, Voetsch AC, Williams DB. HIV Incidence by Male Circumcision Status From the Population-Based HIV Impact Assessment Surveys-Eight Sub-Saharan African Countries, 2015-2017. J Acquir Immune Defic Syndr 2021; 87:S89-S96. [PMID: 33765683 PMCID: PMC11187824 DOI: 10.1097/qai.0000000000002658] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 12/21/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND Male circumcision (MC) offers men lifelong partial protection from heterosexually acquired HIV infection. The impact of MC on HIV incidence has not been quantified in nationally representative samples. Data from the population-based HIV impact assessments were used to compare HIV incidence by MC status in countries implementing voluntary medical MC (VMMC) programs. METHODS Data were pooled from population-based HIV impact assessments conducted in Eswatini, Lesotho, Malawi, Namibia, Tanzania, Uganda, Zambia, and Zimbabwe from 2015 to 2017. Incidence was measured using a recent infection testing algorithm and analyzed by self-reported MC status distinguishing between medical and nonmedical MC. Country, marital status, urban setting, sexual risk behaviors, and mean population HIV viral load among women as an indicator of treatment scale-up were included in a random-effects logistic regression model using pooled survey weights. Analyses were age stratified (15-34 and 35-59 years). Annualized incidence rates and 95% confidence intervals (CIs) and incidence differences were calculated between medically circumcised and uncircumcised men. RESULTS Men 15-34 years reporting medical MC had lower HIV incidence than uncircumcised men [0.04% (95% CI: 0.00% to 0.10%) versus 0.34% (95% CI: 0.10% to 0.57%), respectively; P value = 0.01]; whereas among men 35-59 years, there was no significant incidence difference [1.36% (95% CI: 0.32% to 2.39%) versus 0.55% (95% CI: 0.14% to 0.67%), respectively; P value = 0.14]. DISCUSSION Medical MC was associated with lower HIV incidence in men aged 15-34 years in nationally representative surveys in Africa. These findings are consistent with the expected ongoing VMMC program impact and highlight the importance of VMMC for the HIV response in Africa.
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Affiliation(s)
- Jonas Z. Hines
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Karampreet Sachathep
- ICAP at Columbia University, Mailman School of Public Health, Columbia University, New York, New York
| | - Sherri Pals
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Stephanie M. Davis
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Carlos Toledo
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Megan Bronson
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Bharat Parekh
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Maria Carrasco
- Office of HIV and AIDS, U.S. Agency for International Development, Washington, District of Columbia
| | | | - John Mandisarisa
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Harare, Zimbabwe
| | | | - Omega Chituwo
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | | | - Stella Alamo
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Kampala, Uganda
| | - Geoffrey Kabuye
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Kampala, Uganda
| | - Anna Colletar Awor
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Kampala, Uganda
| | - Susan Mmbando
- National AIDS Control Programme, Ministry of Health, Community Development, Gender, Elderly and Children, Dar es Salaam, Tanzania
| | - Daimon Simbeye
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Dar es Salaam, Tanzania
| | - Mekondjo A. Aupokolo
- National HIV/AIDS, STI and Hepatitis Control Program, Ministry of Health and Social Services, Windhoek, Namibia
| | - Brigitte Zemburuka
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Windhoek, Namibia
| | | | - Wezi Msungama
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Lilongwe, Malawi
| | | | - Robert Manda
- U.S. Agency for International Development, Maseru, Lesotho
| | - Harriet Nuwagaba-Biribonwoha
- ICAP at Columbia University, Mbabane, Eswatini
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Valerian Kiggundu
- Office of HIV and AIDS, U.S. Agency for International Development, Washington, District of Columbia
| | - Anne G. Thomas
- Defense Health Agency, U.S. Department of Defense, San Diego, California
| | - Heather Watts
- Office of Global AIDS Coordinator, Washington, District of Columbia
| | - Andrew C. Voetsch
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Dan B. Williams
- Division of Global HIV and Tuberculosis, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
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Patel EU, Solomon SS, Lucas GM, McFall AM, Srikrishnan AK, Kumar MS, Iqbal SH, Saravanan S, Paneerselvam N, Balakrishnan P, Laeyendecker O, Celentano DD, Mehta SH. Temporal change in population-level prevalence of detectable HIV viraemia and its association with HIV incidence in key populations in India: a serial cross-sectional study. Lancet HIV 2021; 8:e544-e553. [PMID: 34331860 DOI: 10.1016/s2352-3018(21)00098-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 04/14/2021] [Accepted: 04/27/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Population-level prevalence of detectable HIV viraemia (PDV) has been proposed as a metric for monitoring the population-level effectiveness of HIV treatment as prevention. We aimed to characterise temporal changes in PDV in people who inject drugs (PWID) and men who have sex with men (MSM) in India and evaluate community-level and individual-level associations with cross-sectional HIV incidence. METHODS We did a serial cross-sectional study in which baseline (from Oct 1, 2012, to Dec 19, 2013) and follow-up (from Aug 1, 2016, to May 28, 2017) respondent-driven sampling (RDS) surveys were done in MSM (ten community sites) and PWID (12 community sites) across 21 cities in India. Eligible participants were those aged 18 years or older who provided informed consent and possessed a valid RDS referral coupon. Annualised HIV incidence was estimated with validated multiple-assay algorithms. PDV was calculated as the percentage of people with detectable HIV RNA (>150 copies per mL) in a community site. Community-level associations were determined by linear regression. Multivariable, multilevel Poisson regression was used to assess associations with recent HIV infection. FINDINGS We recruited 21 990 individuals in the baseline survey and 21 726 individuals in the follow-up survey. The median community-level HIV incidence estimate increased from 0·9% (range 0·0-2·2) at baseline to 1·5% (0·5-3·0) at follow-up in MSM and from 1·6% (0·5-12·4) to 3·6% (0·0-18·4) in PWID. At the community-level, every 1 percentage point increase in baseline PDV and temporal change in PDV between surveys was associated with higher annualised HIV incidence at follow-up: for baseline PDV β=0·41 (95% CI 0·18-0·63) and for change in PDV β=0·52 (0·38-0·66). After accounting for individual-level risk factors, every 10 percentage point increase in baseline PDV and temporal change in PDV was associated with higher individual-level risk of recent HIV infection at follow-up: adjusted risk ratio 1·85 (95% CI 1·44-2·37) for baseline PDV and 1·81 (1·43-2·29) for change in PDV. INTERPRETATION PDV was temporally associated with community-level and individual-level HIV incidence. These data support scale-up of treatment as prevention programmes to reduce HIV incidence and the programmatic use of PDV to monitor community HIV risk potential. FUNDING US National Institutes of Health, Elton John AIDS Foundation.
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Affiliation(s)
- Eshan U Patel
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sunil S Solomon
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Gregory M Lucas
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Allison M McFall
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | - Syed H Iqbal
- YR Gaitonde Centre for AIDS Research and Education, Chennai, India
| | | | | | | | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - David D Celentano
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Shruti H Mehta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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22
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Woldesenbet S, Kufa-Chakezha T, Lombard C, Manda S, Cheyip M, Ayalew K, Chirombo B, Barron P, Diallo K, Parekh B, Puren A. Recent HIV infection among pregnant women in the 2017 antenatal sentinel cross-sectional survey, South Africa: Assay-based incidence measurement. PLoS One 2021; 16:e0249953. [PMID: 33852629 PMCID: PMC8046194 DOI: 10.1371/journal.pone.0249953] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/27/2021] [Indexed: 11/30/2022] Open
Abstract
Introduction New HIV infection during pre-conception and pregnancy is a significant contributor of mother–to–child transmission of HIV in South Africa. This study estimated HIV incidence (defined as new infection within the last one year from the time of the survey which included both new infections occurred during pregnancy or just before pregnancy) among pregnant women and described the characteristics of recently infected pregnant women at national level. Methods Between 1 October and 15 November 2017, we conducted a national cross–sectional survey among pregnant women aged 15–49 years old attending antenatal care at 1,595 public facilities. Blood specimens were collected from pregnant women and tested for HIV in a centralised laboratory. Plasma viral load and Limiting Antigen Avidity Enzyme Immunosorbent Assay (LAg) tests were further performed on HIV positive specimens to differentiate between recent and long–term infections. Recent infection was defined as infection that occurred within one year from the date of collection of blood specimen for the survey. Data on age, age of partner, and marital status were collected through interviews. Women whose specimens were classified as recent by LAg assay and with viral loads >1,000 copies/mL were considered as recently infected. The calculated proportion of HIV positive women with recent infection was adjusted for assay–specific parameters to estimate annual incidence. Survey multinomial logistic regression was used to examine factors associated with being recently infected using HIV negative women as a reference group. Age–disparate relationship was defined as having a partner 5 or more years older. Results Of 10,049 HIV positive participants with LAg and viral load data, 1.4% (136) were identified as recently infected. The annual HIV incidence was 1.5% (95% confidence interval (CI): 1.2–1.7). In multivariable analyses, being single (adjusted odds ratio, aOR: 3.4, 95% CI: 1.8–6.2) or cohabiting (aOR: 3.8, 95% CI: 1.8–7.7), compared to being married as well as being in an age–disparate relationship among young women (aOR: 3.1, 95% CI: 2.0–4.7; reference group: young women (15–24years) whose partners were not 5 years or more older) were associated with higher odds of recent infection. Conclusions Compared to previous studies among pregnant women, the incidence estimated in this study was substantially lower. However, the UNAIDS target to reduce incidence by 75% by 2020 (which is equivalent to reducing incidence to <1%) has not been met. The implementation of HIV prevention and treatment interventions should be intensified, targeting young women engaged in age–disparate relationship and unmarried women to fast track progress towards the UNAIDS target.
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Affiliation(s)
- Selamawit Woldesenbet
- Center for HIV and STI, National Institute for Communicable Diseases, Johannesburg, South Africa
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
- * E-mail:
| | - Tendesayi Kufa-Chakezha
- Center for HIV and STI, National Institute for Communicable Diseases, Johannesburg, South Africa
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Carl Lombard
- Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa
| | - Samuel Manda
- Biostatistics Unit, South African Medical Research Council, Pretoria, South Africa
- Department of Statistics, University of Pretoria, Pretoria, South Africa
| | - Mireille Cheyip
- Strategic Information Unit, Center for Disease Control and Prevention, Pretoria, South Africa
| | - Kassahun Ayalew
- Strategic Information Unit, Center for Disease Control and Prevention, Pretoria, South Africa
| | - Brian Chirombo
- HIV and Hepatitis Program, World Health Organization, Pretoria, South Africa
| | - Peter Barron
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Karidia Diallo
- Laboratory Branch, Centers for Disease Control and Prevention South Africa, Pretoria, South Africa
| | - Bharat Parekh
- Division of Global HIV/AIDS, International Laboratory Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Adrian Puren
- Center for HIV and STI, National Institute for Communicable Diseases, Johannesburg, South Africa
- Division of Virology, School of Pathology University of the Witwatersrand, Johannesburg, South Africa
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Abstract
In South Africa, evidence shows high HIV prevalence in older populations, with sexual behavior consistent with high HIV acquisition and transmission risk. However, there is a dearth of evidence on older people's HIV incidence.
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Gao F, Glidden DV, Hughes JP, Donnell DJ. Sample size calculation for active-arm trial with counterfactual incidence based on recency assay. STATISTICAL COMMUNICATIONS IN INFECTIOUS DISEASES 2021; 13:20200009. [PMID: 35880999 PMCID: PMC8865397 DOI: 10.1515/scid-2020-0009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 09/27/2021] [Accepted: 09/30/2021] [Indexed: 06/15/2023]
Abstract
Objectives The past decade has seen tremendous progress in the development of biomedical agents that are effective as pre-exposure prophylaxis (PrEP) for HIV prevention. To expand the choice of products and delivery methods, new medications and delivery methods are under development. Future trials of non-inferiority, given the high efficacy of ARV-based PrEP products as they become current or future standard of care, would require a large number of participants and long follow-up time that may not be feasible. This motivates the construction of a counterfactual estimate that approximates incidence for a randomized concurrent control group receiving no PrEP. Methods We propose an approach that is to enroll a cohort of prospective PrEP users and aug-ment screening for HIV with laboratory markers of duration of HIV infection to indicate recent infections. We discuss the assumptions under which these data would yield an estimate of the counterfactual HIV incidence and develop sample size and power calculations for comparisons to incidence observed on an investigational PrEP agent. Results We consider two hypothetical trials for men who have sex with men (MSM) and transgender women (TGW) from different regions and young women in sub-Saharan Africa. The calculated sample sizes are reasonable and yield desirable power in simulation studies. Conclusions Future one-arm trials with counterfactual placebo incidence based on a recency assay can be conducted with reasonable total screening sample sizes and adequate power to determine treatment efficacy.
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Affiliation(s)
- Fei Gao
- Fred Hutchinson Cancer Research Center, Seattle, USA
| | - David V. Glidden
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - James P. Hughes
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Deborah J. Donnell
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Grebe E, Busch MP, Notari EP, Bruhn R, Quiner C, Hindes D, Stone M, Bakkour S, Yang H, Williamson P, Kessler D, Reik R, Stramer SL, Glynn SA, Anderson SA, Williams AE, Custer B. HIV incidence in US first-time blood donors and transfusion risk with a 12-month deferral for men who have sex with men. Blood 2020; 136:1359-1367. [PMID: 32693408 PMCID: PMC7483431 DOI: 10.1182/blood.2020007003] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/07/2020] [Indexed: 12/29/2022] Open
Abstract
In 2015, the US Food and Drug Administration published revised guidance that recommended a change in blood donor deferral of men who have sex with men (MSM) from an indefinite to a 12-month deferral since the donor last had sex with a man. We assessed whether HIV incidence in first-time blood donors or associated transfusion risk increased. Donations in 4 major blood collection organizations were monitored for 15 months before and 2 years after implementation of the 12-month MSM deferral policy. HIV-positive donations were classified as recently acquired or long-term using a recent infection testing algorithm and incidence in both periods estimated. Residual transfusion transmission risk was estimated by multiplying incidence by the length of the infectious window period. The latter was estimated using a model based on infectious dose and the sensitivity of nucleic acid testing. Factors associated with incident infection in each period were assessed using Poisson regression. Overall HIV incidence in first-time donors before implementation of the 12-month MSM deferral was estimated at 2.62 cases per 100 000 person-years (105 PY) (95% credible interval [CI], 1.53-3.93 cases/105 PY), and after implementation at 2.85 cases/105 PY (95% CI, 1.96-3.93 cases/105 PY), with no statistically significant change. In male first-time donors, the incidence difference was 0.93 cases/105 PY (95% CI, -1.74-3.58 cases/105 PY). The residual risk of HIV transfusion transmission through components sourced from first-time donors was estimated at 0.32 transmissions per million (106) packed red blood cell transfusions (95% CI, 0.29-0.65 transmissions/106 transfusions) before and 0.35 transmissions/106 transfusions (95% CI, 0.31-0.65 transmissions/106 transfusions) after implementation. The difference was not statistically significant. Factors associated with incident infection were the same in each period. We observed no increase in HIV incidence or HIV transfusion transmission risk after implementation of a 12-month MSM deferral policy.
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Affiliation(s)
- Eduard Grebe
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Michael P Busch
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Edward P Notari
- Scientific Affairs, American Red Cross, Rockville and Gaithersburg, MD
| | - Roberta Bruhn
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Claire Quiner
- Vitalant Research Institute, San Francisco, CA
- RTI International, Research Triangle Park, NC
| | | | - Mars Stone
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Sonia Bakkour
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Hong Yang
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD
| | | | | | | | - Susan L Stramer
- Scientific Affairs, American Red Cross, Rockville and Gaithersburg, MD
| | - Simone A Glynn
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Steven A Anderson
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD
| | - Alan E Williams
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD
| | - Brian Custer
- Vitalant Research Institute, San Francisco, CA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
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26
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Conan N, Coulborn RM, Simons E, Mapfumo A, Apollo T, Garone DB, Casas EC, Puren AJ, Chihana ML, Maman D. Successes and gaps in the HIV cascade of care of a high HIV prevalence setting in Zimbabwe: a population-based survey. J Int AIDS Soc 2020; 23:e25613. [PMID: 32969602 PMCID: PMC7513352 DOI: 10.1002/jia2.25613] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 06/20/2020] [Accepted: 07/31/2020] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Gutu, a rural district in Zimbabwe, has been implementing comprehensive HIV care with the support of Médecins Sans Frontières (MSF) since 2011, decentralizing testing and treatment services to all rural healthcare facilities. We evaluated HIV prevalence, incidence and the cascade of care, in Gutu District five years after MSF began its activities. METHODS A cross-sectional study was implemented between September and December 2016. Using multistage cluster sampling, individuals aged ≥15 years living in the selected households were eligible. Individuals who agreed to participate were interviewed and tested for HIV at home. All participants who tested HIV-positive had their HIV-RNA viral load (VL) measured, regardless of their antiretroviral therapy (ART) status, and those not on ART with HIV-RNA VL ≥ 1000 copies/mL had Limiting-Antigen-Avidity EIA Assay for cross-sectional estimation of population-level HIV incidence. RESULTS Among 5439 eligible adults ≥15 years old, 89.0% of adults were included in the study and accepted an HIV test. The overall prevalence was 13.6% (95%: Confidence Interval (CI): 12.6 to 14.5). Overall HIV-positive status awareness was 87.4% (95% CI: 84.7 to 89.8), linkage to care 85.5% (95% CI: 82.5 to 88.0) and participants in care 83.8% (95% CI: 80.7 to 86.4). ART coverage among HIV-positive participants was 83.0% (95% CI: 80.0 to 85.7). Overall, 71.6% (95% CI 68.0 to 75.0) of HIV-infected participants had a HIV-RNA VL < 1000 copies/mL. Women achieved higher outcomes than men in the five stages of the cascade of care. Viral Load Suppression (VLS) among participants on ART was 83.2% (95% CI: 79.7 to 86.2) and was not statistically different between women and men (p = 0.98). The overall HIV incidence was estimated at 0.35% (95% CI 0.00 to 0.70) equivalent to 35 new cases/10,000 person-years. CONCLUSIONS Our study provides population-level evidence that achievement of HIV cascade of care coverage overall and among women is feasible in a context with broad access to services and implementation of a decentralized model of care. However, the VLS was relatively low even among participants on ART. Quality care remains the most critical gap in the cascade of care to further reduce mortality and HIV transmission.
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Affiliation(s)
| | | | | | | | | | | | | | - Adrian J Puren
- National Institute for Communicable Diseases (NICD)National Health Laboratory ServiceJohannesburgSouth Africa
- Division of Virology, School of PathologyUniversity of the Witwatersrand Medical SchoolJohannesburgSouth Africa
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27
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Quiner C, Bruhn R, Grebe E, Di Germanio C, Kessler D, Reik R, Williamson P, Hampton D, Fayed R, Anderson SA, Williams AE, Glynn SA, Busch MP, Stramer SL, Custer B. Recently acquired infection among HIV-seropositive donors in the US from 2010-2018. Transfusion 2020; 60:2340-2347. [PMID: 32860262 DOI: 10.1111/trf.16032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 08/03/2020] [Accepted: 08/03/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND Monitoring of transfusion-transmissible infections in the blood supply is essential for blood safety, as the donor population is not static, and changes in policy, donor behavior, or other factors could increase the risk of recipient infection. We assessed patterns of recently acquired HIV infection in US blood donors, including before and after the implementation of the 12-month deferral for men who have sex with men (MSM). STUDY DESIGN AND METHODS A large convenience sample of donations from donors testing HIV-1 nucleic acid testing (NAT) and serology-reactive were further tested with the Sedia HIV-1 Limiting Antigen enzyme immunoassay. Samples were analyzed across available demographic and donation data to provide an assessment of recently acquired HIV infection in US blood donors from 2010 to 2018. RESULTS Overall, 317 of 1154 (27.5%; 95% confidence interval, 24.9%-30.1%) donations from HIV NAT and serology-reactive donors had recently acquired HIV infection. There was no evidence of change in the percentages of recent HIV infection by year over the study period, either in all donors or in male donors, including after the MSM policy change. In multivariable logistic regression analysis, donors aged 24 years or younger were over 2.7 times more likely and repeat donors 2.2 times more likely to have recently acquired HIV infection compared to donors aged 55 years or older and first-time donors, respectively. CONCLUSION Patterns of recently acquired HIV infection varied by demographics but not over time. These findings suggest no impact of the MSM policy change on recently acquired HIV infection in US blood donors.
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Affiliation(s)
- Claire Quiner
- Vitalant Research Institute, San Francisco, California, USA
| | - Roberta Bruhn
- Vitalant Research Institute, San Francisco, California, USA.,Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA
| | - Eduard Grebe
- Vitalant Research Institute, San Francisco, California, USA
| | | | | | - Rita Reik
- OneBlood, St. Petersburg, Florida, USA
| | | | - Dylan Hampton
- Vitalant Research Institute, San Francisco, California, USA
| | - Rahima Fayed
- American Red Cross Scientific Affairs, Gaithersburg, Maryland, USA
| | | | - Alan E Williams
- U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Simone A Glynn
- National Heart, Lung and Blood Institute, National Institutes of Health, Rockville, Maryland, USA
| | - Michael P Busch
- Vitalant Research Institute, San Francisco, California, USA.,Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA
| | - Susan L Stramer
- American Red Cross Scientific Affairs, Gaithersburg, Maryland, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, California, USA.,Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA
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28
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Fellows IE, Shiraishi RW, Cherutich P, Achia T, Young PW, Kim AA. A new method for estimating HIV incidence from a single cross-sectional survey. PLoS One 2020; 15:e0237221. [PMID: 32785257 PMCID: PMC7423136 DOI: 10.1371/journal.pone.0237221] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 07/22/2020] [Indexed: 12/03/2022] Open
Abstract
Estimating incidence from cross-sectional data sources is both important to the understanding of the HIV epidemic and challenging from a methodological standpoint. We develop a new incidence estimator that measures the size of the undiagnosed population and the amount of time spent undiagnosed in order to infer incidence and transmission rates. The estimator is calculated using commonly collected information on testing history and HIV status and, thus, can be deployed in many HIV surveys without additional cost. If ART biomarker status and/or viral load information is available, the estimator can be adjusted for biases in self-reported testing history. The performance of the estimator is explored in two large surveys in Kenya, where we find our point estimates to be consistent with assay-derived estimates, with much smaller standard errors.
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Affiliation(s)
- Ian E. Fellows
- Fellows Statistics, San Diego, CA, United States of America
- * E-mail:
| | - Ray W. Shiraishi
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Peter Cherutich
- National AIDS and STD Control Programme, Ministry of Health, Nairobi, Kenya
| | - Thomas Achia
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Peter W. Young
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Andrea A. Kim
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States of America
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29
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Boon D, Bruce V, Patel EU, Quinn J, Srikrishnan AK, Shanmugam S, Iqbal S, Balakrishnan P, Sievers M, Kirk GD, Thomas DL, Quinn TC, Cox AL, Page KA, Solomon SS, Mehta SH, Laeyendecker O. Antibody avidity-based approach to estimate population-level incidence of hepatitis C. J Hepatol 2020; 73:294-302. [PMID: 32240715 PMCID: PMC7458132 DOI: 10.1016/j.jhep.2020.03.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 03/11/2020] [Accepted: 03/15/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND & AIMS Accurate HCV incidence estimates are critical for monitoring progress towards HCV elimination goals, including an 80% reduction in HCV incidence by 2030. Moreover, incidence estimates can help guide prevention and treatment programming, particularly in the context of the US opioid epidemic. METHODS An inexpensive, Genedia-based HCV IgG antibody avidity assay was evaluated as a platform to estimate cross-sectional, population-level primary HCV incidence using 1,840 HCV antibody and RNA-positive samples from 875 individuals enrolled in 5 cohort studies in the US and India. Using samples collected <2 years following HCV seroconversion, the mean duration of recent infection (MDRI) was calculated by fitting a maximum likelihood binomial regression model to the probability of appearing recent. Among samples collected ≥2 years post-HCV seroconversion, an individual-level false recent ratio (FRR) was calculated by estimating the probability of appearing recent using an exact binomial test. Factors associated with falsely appearing recent among samples collected ≥2 years post seroconversion were determined by Poisson regression with generalized estimating equations and robust variance estimators. RESULTS An avidity index cut-off of <40% resulted in an MDRI of 113 days (95% CI 84-146), and FRRs of 0.4% (95% CI 0.0-1.2), 4.6% (95% CI 2.2-8.3), and 9.5% (95% CI 3.6-19.6) among individuals who were HIV-uninfected, HIV-infected, and HIV-infected with a CD4 count <200/μl, respectively. No variation was seen between HCV genotypes 1 and 3. In hypothetical scenarios of high-risk settings, a sample size of <1,000 individuals could reliably estimate primary HCV incidence. CONCLUSIONS This cross-sectional approach can estimate primary HCV incidence for the most common genotypes. This tool can serve as a valuable resource for program and policy planners seeking to monitor and reduce HCV burden. LAY SUMMARY Determining the rate of new hepatitis C virus (HCV) infections in a population is critical to monitoring progress toward HCV elimination and to appropriately guide control efforts. However, since HCV infections are most often initially asymptomatic, it is difficult to estimate the rate of new HCV infections without following HCV-uninfected people over time and repeatedly testing them for HCV infection. Here, we present a novel, resource-efficient method to estimate the rate of new HCV infections in a population using data from a single timepoint.
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Affiliation(s)
- Denali Boon
- Johns Hopkins University, Baltimore, Maryland, USA.
| | | | | | | | | | | | - Syed Iqbal
- YR Gaitonde Centre for AIDS Research and Education, Chennai, India
| | | | | | | | | | - Thomas C Quinn
- Johns Hopkins University, Baltimore, Maryland, USA; National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Andrea L Cox
- Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Sunil S Solomon
- Johns Hopkins University, Baltimore, Maryland, USA; YR Gaitonde Centre for AIDS Research and Education, Chennai, India
| | | | - Oliver Laeyendecker
- Johns Hopkins University, Baltimore, Maryland, USA; National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
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30
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Carlisle LA, Turk T, Kusejko K, Metzner KJ, Leemann C, Schenkel CD, Bachmann N, Posada S, Beerenwinkel N, Böni J, Yerly S, Klimkait T, Perreau M, Braun DL, Rauch A, Calmy A, Cavassini M, Battegay M, Vernazza P, Bernasconi E, Günthard HF, Kouyos RD. Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection. J Infect Dis 2020; 220:254-265. [PMID: 30835266 DOI: 10.1093/infdis/jiz094] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 03/01/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Human immunodeficiency virus type 1 (HIV-1) genetic diversity increases over the course of infection and can be used to infer the time since infection and, consequently, infection recency, which are crucial for HIV-1 surveillance and the understanding of viral pathogenesis. METHODS We considered 313 HIV-infected individuals for whom reliable estimates of infection dates and next-generation sequencing (NGS)-derived nucleotide frequency data were available. Fractions of ambiguous nucleotides, obtained by population sequencing, were available for 207 samples. We assessed whether the average pairwise diversity calculated using NGS sequences provided a more exact prediction of the time since infection and classification of infection recency (<1 year after infection), compared with the fraction of ambiguous nucleotides. RESULTS NGS-derived average pairwise diversity classified an infection as recent with a sensitivity of 88% and a specificity of 85%. When considering only the 207 samples for which fractions of ambiguous nucleotides were available, the NGS-derived average pairwise diversity exhibited a higher sensitivity (90% vs 78%) and specificity (95% vs 67%) than the fraction of ambiguous nucleotides. Additionally, the average pairwise diversity could be used to estimate the time since infection with a mean absolute error of 0.84 years, compared with 1.03 years for the fraction of ambiguous nucleotides. CONCLUSIONS Viral diversity based on NGS data is more precise than that based on population sequencing in its ability to predict infection recency and provides an estimated time since infection that has a mean absolute error of <1 year.
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Affiliation(s)
- Louisa A Carlisle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Teja Turk
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Karin J Metzner
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Christine Leemann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Corinne D Schenkel
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Nadine Bachmann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Susana Posada
- Department of Biosystems Science and Engineering, ETH Zurich.,SIB Swiss Institute of Bioinformatics, University of Basel, Basel
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich.,SIB Swiss Institute of Bioinformatics, University of Basel, Basel
| | - Jürg Böni
- Institute of Medical Virology, University of Zurich, Zurich.,Swiss National Center for Retroviruses, University of Zurich, Zurich
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, Geneva
| | - Thomas Klimkait
- Molecular Virology, Department of Biomedicine-Petersplatz, University of Basel, Basel
| | - Matthieu Perreau
- Division of Immunology and Allergy, Lausanne University Hospital, Lausanne
| | - Dominique L Braun
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern
| | - Alexandra Calmy
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, Geneva
| | | | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel
| | - Pietro Vernazza
- Division of Infectious Diseases, Cantonal Hospital St. Gallen, St. Gallen
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Zurich
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31
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Karatzas-Delgado EF, Ruiz-González V, García-Cisneros S, Olamendi-Portugal ML, Herrera-Ortiz A, López-Gatell H, González-Rodríguez A, Sánchez-Alemán MA. Evaluation of an HIV recent infection testing algorithm with serological assays among men who have sex with men in Mexico. J Infect Public Health 2019; 13:509-513. [PMID: 31813835 DOI: 10.1016/j.jiph.2019.11.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 07/01/2019] [Accepted: 11/10/2019] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Human immunodeficiency virus (HIV) incidence should be calculated in cross-sectional studies using recent infection testing algorithms (RITA) that consider clinical variables and serological test results such as enzyme-linked immunosorbent assay (ELISA) and dried blood spot (DBS) analysis. METHODS The correlation between serum samples and DBS was evaluated using two commercial ELISA kits: SediaTM BED HIV-1 Incidence EIA (BED-Sedia) and Maxim HIV-1 Limiting Antigen Avidity (LAg-Avidity). Eight different RITAs were developed; all of them included serological assays. A combination of the variables viral load, antiretroviral therapy (ART) and CD4 count was used to build the RITAs. The sensitivity, specificity, Youden index, predictive positive value, predictive negative value, false recent rate (FRR) and false long-term rate were evaluated. RESULTS The correlations between serum samples and DBS were 0.990 and 0.867 for BED-Sedia and LAg-avidity, respectively. Using only serological assays, the Youden index was higher for LAg-avidity than BED-Sedia (82.1-83.0% versus 69.2-69.6%). The best RITA was ART-serology, which showed a Youden index of 91.2-93.9% and FRR of 1.8-2.2%. CONCLUSIONS Using DBS samples to determine HIV incidence is a good tool for epidemiological surveillance. The RITA that included ART and serological tests (BED-Sedia or LAg-avidity) showed the highest sensitivity and specificity and a low FRR.
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Affiliation(s)
- Eli F Karatzas-Delgado
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | | | - Santa García-Cisneros
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | - María L Olamendi-Portugal
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | - Antonia Herrera-Ortiz
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | - Hugo López-Gatell
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | | | - Miguel A Sánchez-Alemán
- Centro de Investigación sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico.
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Low A, Thin K, Davia S, Mantell J, Koto M, McCracken S, Ramphalla P, Maile L, Ahmed N, Patel H, Parekh B, Fida N, Schwitters A, Frederix K. Correlates of HIV infection in adolescent girls and young women in Lesotho: results from a population-based survey. Lancet HIV 2019; 6:e613-e622. [PMID: 31422056 PMCID: PMC6829164 DOI: 10.1016/s2352-3018(19)30183-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 05/03/2019] [Accepted: 05/20/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND HIV acquisition remains high among adolescent girls and young women (AGYW, aged 15-24 years) in sub-Saharan Africa. We aimed to estimate prevalence and incidence of HIV in AGYW and to identify correlates of HIV infection by using data from the Lesotho Population-based HIV Impact Assessment (LePHIA). METHODS LePHIA was a nationally representative survey of adults and children based on a multistage cluster sampling method with random selection of enumeration areas and households. All adults aged 15 years and older who had slept in the household the night before were eligible for participation; participants completed an interview and HIV testing. We estimated incidence with the HIV-1 limiting antigen avidity enzyme immunoassay combined with viral load and examined the association between demographic and behavioural variables (including characteristics of cohabitating mothers and sexual partners, when available) and prevalence and incidence among AGYW using logistic regression, incorporating survey weights. FINDINGS We interviewed 8824 households, including 2358 AGYW who were tested for HIV infection. Weighted HIV prevalence was 11·1% (95% CI 9·7-12·5) in the overall population (273 of 2358 AGYW), 5·7% (4·1-7·2) in adolescent girls aged 15-19 years (64 of 1156), and 16·7% (14·4-19·0) in women aged 20-24 years (209 of 1212). Annualised HIV incidence was 1·8% (0·8-2·8). Correlates of prevalent infection include reporting a history of anal sex (adjusted odds ratio [aOR] 3·08, 1·11-8·57), having lived outside Lesotho in the past year (1·86, 1·01-3·42), having a partner suspected or known to be HIV positive (11·7, 6·0-22·5), and having two or more lifetime sexual partners (1·84, 1·21-2·78, for 2-3 lifetime sexual partners; 2·44, 1·45-4·08, for ≥4 lifetime sexual partners). For the 570 AGYW living with their mothers, maternal education was negatively associated with HIV prevalence in their daughters (aOR 0·36, 0·15-0·82, per increase in level attended). For AGYW with a cohabitating partner, the factors associated with AGYW infection were partner age (OR 4·54, 1·30-15·80, for partners aged 35-49 years, although the OR was no longer significant when adjusted for HIV status of partner), HIV status (aOR 11·22, 4·05-31·05), lack of viral load suppression (OR 0·16, 0·04-0·66), and partner employment in the past year (aOR 3·41, 1·12-10·42). INTERPRETATION The findings confirm the importance of improving the treatment cascade in male partners and targeting preventive interventions to AGYW who are at increased risk. A regional approach to prevention could mitigate the effect of migration on transnational spread of HIV. FUNDING President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention.
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Affiliation(s)
- Andrea Low
- ICAP at Columbia University, Mailman School of Public Health, Columbia University, New York, NY, USA.
| | - Kyaw Thin
- Lesotho Ministry of Health, Maseru, Lesotho
| | - Stefania Davia
- Centers for Disease Control and Prevention, Maseru, Lesotho
| | - Joanne Mantell
- HIV Center for Clinical and Behavioral Studies, Division of Gender, Sexuality and Health, New York State Psychiatric Institute and Columbia University, New York, NY, USA
| | | | - Stephen McCracken
- US Centers for Disease Control and Prevention, Center for Global Health, Division of HIV/AIDS, Atlanta, GA, USA
| | | | | | - Nahima Ahmed
- ICAP at Columbia University, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Hetal Patel
- US Centers for Disease Control and Prevention, Center for Global Health, Division of HIV/AIDS, Atlanta, GA, USA
| | - Bharat Parekh
- US Centers for Disease Control and Prevention, Center for Global Health, Division of HIV/AIDS, Atlanta, GA, USA
| | - Neway Fida
- US Agency for International Development Southern Africa Regional HIV/AIDS Program, Pretoria, South Africa
| | | | - Koen Frederix
- ICAP in Lesotho, Mailman School of Public Health, Columbia University, Maseru, Lesotho
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Sempa JB, Welte A, Busch MP, Hall J, Hampton D, Facente SN, Keating SM, Marson K, Parkin N, Pilcher CD, Murphy G, Grebe E. Performance comparison of the Maxim and Sedia Limiting Antigen Avidity assays for HIV incidence surveillance. PLoS One 2019; 14:e0220345. [PMID: 31348809 PMCID: PMC6660077 DOI: 10.1371/journal.pone.0220345] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 07/13/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Two manufacturers, Maxim Biomedical and Sedia Biosciences Corporation, supply CDC-approved versions of the HIV-1 Limiting Antigen Avidity EIA (LAg) for detecting 'recent' HIV infection in cross-sectional incidence estimation. This study assesses and compares the performance of the two assays for incidence surveillance. METHODS We ran both assays on a panel of 2,500 well-characterized HIV-1-infected specimens. We analysed concordance of assay results, assessed reproducibility using repeat testing and estimated mean durations of recent infection (MDRIs) and false-recent rates (FRRs) for a range of normalized optical density (ODn) thresholds, alone and in combination with viral load thresholds. We defined three hypothetical surveillance scenarios, similar to the Kenyan and South African epidemics, and a concentrated epidemic. These scenarios allowed us to evaluate the precision of incidence estimates obtained by means of various recent infection testing algorithms (RITAs) based on each of the two assays. RESULTS The Maxim assay produced lower ODn values than the Sedia assay on average, largely as a result of higher calibrator readings (mean OD of 0.749 vs. 0.643), with correlation of normalized readings lower (R2 = 0.908 vs. R2 = 0.938). Reproducibility on blinded control specimens was slightly better for Maxim. The MDRI of a Maxim-based algorithm at the 'standard' threshold (ODn ≤1.5 & VL >1,000) was 201 days (95% CI: 180,223) and for Sedia 171 (152,191). The difference Differences in MDRI were estimated at 32.7 (22.9,42.8) and 30.9 days (21.7,40.7) for the two algorithms, respectively. Commensurately, the Maxim algorithm had a higher FRR in treatment-naive subjects (1.7% vs. 1.1%). The two assays produced similar precision of incidence estimates in the three surveillance scenarios. CONCLUSIONS Differences between the assays can be primarily attributed to the calibrators supplied by the manufacturers. Performance for surveillance was extremely similar, although different thresholds were optimal (i.e. produced the lowest variance of incidence estimates) and at any given ODn threshold, different estimates of MDRI and FRR were obtained. The two assays cannot be treated as interchangeable: assay and algorithm-specific performance characteristic estimates must be used for survey planning and incidence estimation.
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Affiliation(s)
- Joseph B. Sempa
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Alex Welte
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Michael P. Busch
- Vitalant Research Institute, San Francisco, CA, United States of America
- University of California San Francisco, San Francisco, CA, United States of America
| | - Jake Hall
- Public Health England, London, United Kingdom
| | - Dylan Hampton
- Vitalant Research Institute, San Francisco, CA, United States of America
| | - Shelley N. Facente
- Vitalant Research Institute, San Francisco, CA, United States of America
- University of California San Francisco, San Francisco, CA, United States of America
- Facente Consulting, Richmond, CA, United States of America
| | - Sheila M. Keating
- Vitalant Research Institute, San Francisco, CA, United States of America
- University of California San Francisco, San Francisco, CA, United States of America
| | - Kara Marson
- University of California San Francisco, San Francisco, CA, United States of America
| | - Neil Parkin
- Data First Consulting, Belmont, CA, United States of America
| | | | - Gary Murphy
- Public Health England, London, United Kingdom
| | - Eduard Grebe
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- Vitalant Research Institute, San Francisco, CA, United States of America
- University of California San Francisco, San Francisco, CA, United States of America
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Park SY, Love TMT, Kapoor S, Lee HY. HIITE: HIV-1 incidence and infection time estimator. Bioinformatics 2019; 34:2046-2052. [PMID: 29438560 DOI: 10.1093/bioinformatics/bty073] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 02/08/2018] [Indexed: 01/23/2023] Open
Abstract
Motivation Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting. Results We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs. Availability and implementation Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
| | - Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Shivankur Kapoor
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
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Hansoti B, Stead D, Eisenberg A, Mvandaba N, Mwinnyaa G, Patel EU, Parrish A, Reynolds SJ, Redd AD, Fernandez R, Rothman RE, Laeyendecker O, Quinn TC. A Window Into the HIV Epidemic from a South African Emergency Department. AIDS Res Hum Retroviruses 2019; 35:139-144. [PMID: 30215268 DOI: 10.1089/aid.2018.0127] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The aim of the study was to describe the HIV care continuum in emergency department (ED) patients in the Eastern Cape region of South Africa. This is a cross-sectional, identity-unlinked serosurvey, whereby discarded/excess samples from all patients who had blood drawn during the study period for routine care and sufficient serum remaining were tested for HIV, hepatitis B virus, and hepatitis C virus infection; HIV viral load (VL); and presence of antiretroviral (ARV) drugs. We also estimated cross-sectional incidence using the Limiting-Antigen Avidity assay and HIV VL. The study was conducted between September and November 2016 at the Frere Hospital Emergency Department in East London, South Africa. The overall HIV prevalence in our study population was 26.9% [95% confidence interval (CI): 25.0-28.8; n = 2,100]. The highest prevalence was observed among females in the 30-39 years age group [60.3% (95% CI: 53.2-67.1)]. HIV prevalence was significantly higher among females compared with males in both the 20-29 years age group and 30-39 years age group (p < .05), but nearly identical to older age groups. ARV drugs were detected in 53.5% (95% CI: 48.1-58.9) of HIV-infected subjects. The frequency of HIV viral suppression (< 1,000 copies/mL) was 48.5% (95% CI: 44.3-52.7), and was not statistically different between males and females (age-adjusted prevalence ratio = 1.15, 95% CI: 0.95-1.39). The HIV incidence rate was estimated to be 2.6% (95% CI: 1.2-3.9). The Frere Hospital ED has an extremely high burden of HIV infection. The detection of ARV drugs and prevalence of viral suppression fall short of the World Health Organization 90-90-90 goals in this population. Furthermore, there were a large number of patients with recent infection in the ED. The ED is a critical venue for testing and linkage to care of high-yield population who are likely missed by current testing and linkage-to-care programs.
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Affiliation(s)
- Bhakti Hansoti
- Department of Emergency Medicine, The Johns Hopkins University, Baltimore, Maryland
| | - David Stead
- Department of Medicine, Frere and Cecilia Makiwane Hospitals, East London, South Africa
- Department of Medicine, Faculty of Health Sciences, Walter Sisulu University, East London, South Africa
| | - Anna Eisenberg
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
| | - Nomzamo Mvandaba
- Department of Medicine, Faculty of Health Sciences, Walter Sisulu University, East London, South Africa
| | - George Mwinnyaa
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Eshan U. Patel
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Andy Parrish
- Department of Medicine, Frere and Cecilia Makiwane Hospitals, East London, South Africa
- Department of Medicine, Faculty of Health Sciences, Walter Sisulu University, East London, South Africa
| | - Steven J. Reynolds
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Andrew D. Redd
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Reinaldo Fernandez
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Richard E. Rothman
- Department of Emergency Medicine, The Johns Hopkins University, Baltimore, Maryland
| | - Oliver Laeyendecker
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
| | - Thomas C. Quinn
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
- Department of Infectious Diseases, The Johns Hopkins University, Baltimore, Maryland
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Moyo S, Gaseitsiwe S, Mohammed T, Pretorius Holme M, Wang R, Kotokwe KP, Boleo C, Mupfumi L, Yankinda EK, Chakalisa U, van Widenfelt E, Gaolathe T, Mmalane MO, Dryden-Peterson S, Mine M, Lebelonyane R, Bennett K, Leidner J, Wirth KE, Tchetgen Tchetgen E, Powis K, Moore J, Clarke WA, Lockman S, Makhema JM, Essex M, Novitsky V. Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015. PLoS One 2018; 13:e0204840. [PMID: 30356287 PMCID: PMC6200198 DOI: 10.1371/journal.pone.0204840] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 09/12/2018] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Botswana is close to reaching the UNAIDS "90-90-90" HIV testing, antiretroviral treatment (ART), and viral suppression goals. We sought to determine HIV incidence in this setting with both high HIV prevalence and high ART coverage. METHODS We used a cross-sectional approach to assessing HIV incidence. A random, population-based sample of adults age 16-64 years was enrolled in 30 rural and peri-urban communities as part of the Botswana Combination Prevention Project (BCPP), from October 2013 -November 2015. Data and samples from the baseline household survey were used to estimate cross-sectional HIV incidence, following an algorithm that combined Limiting-Antigen Avidity Assay (LAg-Avidity EIA), ART status (documented or by testing ARV drugs in plasma) and HIV-1 RNA load. The LAg-Avidity EIA cut-off normalized optical density (ODn) was set at 1.5. The HIV-1 RNA cut-off was set at 400 copies/mL. For estimation purposes, the Mean Duration of Recent Infection was 130 days and the False Recent Rate (FRR) was evaluated at values of either 0 or 0.39%. RESULTS Among 12,610 individuals participating in the baseline household survey, HIV status was available for 12,570 participants and 3,596 of them were HIV positive. LAg-Avidity EIA data was generated for 3,581 (99.6%) of HIV-positive participants. Of 326 participants with ODn ≤1.5, 278 individuals were receiving ART verified through documentation and were considered to represent longstanding HIV infections. Among the remaining 48 participants who reported no use of ART, 14 had an HIV-1 RNA load ≤400 copies/mL (including 3 participants with ARVs in plasma) and were excluded, as potential elite/viremic controllers or undisclosed ART. Thus, 34 LAg-Avidity-EIA-recent, ARV-naïve individuals with detectable HIV-1 RNA (>400 copies/mL) were classified as individuals with recent HIV infections. The annualized HIV incidence among 16-64 year old adults was estimated at 1.06% (95% CI 0.68-1.45%) with zero FRR, and at 0.64% (95% CI 0.24-1.04%) using a previously defined FRR of 0.39%. Within a subset of younger individuals 16-49 years old, the annualized HIV incidence was estimated at 1.29% (95% CI 0.82-1.77%) with zero FRR, and at 0.90% (95% CI 0.42-1.38%) with FRR set to 0.39%. CONCLUSIONS Using a cross-sectional estimate of HIV incidence from 2013-2015, we found that at the time of near achievement of the UNAIDS 90-90-90 targets, ~1% of adults (age 16-64 years) in Botswana's rural and peri-urban communities became HIV infected annually.
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Affiliation(s)
- Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Simani Gaseitsiwe
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | | | - Molly Pretorius Holme
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Rui Wang
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - Corretah Boleo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Lucy Mupfumi
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | | | - Unoda Chakalisa
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | | | | | | | - Scott Dryden-Peterson
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Madisa Mine
- Botswana Ministry of Health and Wellness, Gaborone, Botswana
| | | | - Kara Bennett
- Bennett Statistical Consulting, Inc., Ballston Lake, New York, United States of America
| | - Jean Leidner
- Goodtables Data Consulting, Norman, OK, United States of America
| | - Kathleen E. Wirth
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Eric Tchetgen Tchetgen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston Massachusetts, United States of America
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Kathleen Powis
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Departments of Internal Medicine and Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Janet Moore
- U.S. Centers for Disease Control, Atlanta, Georgia, United States of America
| | | | - Shahin Lockman
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Joseph M. Makhema
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Max Essex
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Vlad Novitsky
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Grebe E, Welte A, Johnson LF, van Cutsem G, Puren A, Ellman T, Etard JF, Huerga H. Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa. PLoS One 2018; 13:e0203638. [PMID: 30212513 PMCID: PMC6136757 DOI: 10.1371/journal.pone.0203638] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 08/26/2018] [Indexed: 11/30/2022] Open
Abstract
Introduction There is a notable absence of consensus on how to generate estimates of population-level incidence. Incidence is a considerably more sensitive indicator of epidemiological trends than prevalence, but is harder to estimate. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa. Methods Our novel method uses an ‘optimal weighting’ of estimates based on an implementation of a particular ‘synthetic cohort’ approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of ‘recent infection’ (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013. Results Using the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI: 0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY (2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY (0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY (0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27). Discussion HIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small. Conclusion Application of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.
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Affiliation(s)
- Eduard Grebe
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- * E-mail:
| | - Alex Welte
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Leigh F. Johnson
- Centre for Infectious Diseases Epidemiology and Research (CIDER), University of Cape Town, Cape Town, South Africa
| | - Gilles van Cutsem
- Centre for Infectious Diseases Epidemiology and Research (CIDER), University of Cape Town, Cape Town, South Africa
- Médecins Sans Frontières, Cape Town, South Africa
| | - Adrian Puren
- National Institute for Communicable Diseases (NICD), National Health Laboratory Service, Johannesburg, South Africa
| | - Tom Ellman
- Médecins Sans Frontières, Cape Town, South Africa
| | - Jean-François Etard
- TransVIHMI, Institut de Recherche pour le Développement (IRD), Institut National de la Santé et de la Recherche Médicale (INSERM), Montpellier University, Montpellier, France
- Epicentre, Paris, France
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Morrison D, Laeyendecker O, Konikoff J, Brookmeyer R. Cross-Sectional HIV Incidence Estimation with Missing Biomarkers. ACTA ACUST UNITED AC 2018; 10. [PMID: 30701015 DOI: 10.1515/scid-2017-0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Considerable progress has been made in the development of approaches for HIV incidence estimation based on a cross-sectional survey for biomarkers of recent infection. Multiple biomarkers when used in combination can increase the precision of cross-sectional HIV incidence estimates. Multi-assay algorithms (MAAs) for cross-sectional HIV incidence estimation are hierarchical stepwise algorithms for testing the biological samples with multiple biomarkers. The objective of this paper is to consider some of the statistical challenges for addressing the problem of missing biomarkers in such testing algorithms. We consider several methods for handling missing biomarkers for (1) estimating the mean window period, and (2) estimating HIV incidence from a cross sectional survey once the mean window period has been determined. We develop a conditional estimation approach for addressing the missing data challenges and compare that method with two naïve approaches. Using MAAs developed for HIV subtype B, we evaluate the methods by simulation. We show that the two naïve estimation methods lead to biased results in most of the missing data scenarios considered. The proposed conditional approach protects against bias in all of the scenarios.
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Affiliation(s)
- Doug Morrison
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, NIAID, NIH, Baltimore, MD, USA and The Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jacob Konikoff
- Consultant; work completed as postdoctoral fellow, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ron Brookmeyer
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
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Nascimento EJM, Huleatt JW, Cordeiro MT, Castanha PMS, George JK, Grebe E, Welte A, Brown M, Burke DS, Marques ETA. Development of antibody biomarkers of long term and recent dengue virus infections. J Virol Methods 2018; 257:62-68. [PMID: 29684416 DOI: 10.1016/j.jviromet.2018.04.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 04/05/2018] [Accepted: 04/12/2018] [Indexed: 11/18/2022]
Abstract
Dengue virus (DENV) infections elicit antibody responses to the non-structural protein 1 (NS1) that are associated with protection against disease. However, the antibody isotypes and subclasses involved, and their kinetics have not been extensively studied. We characterized the antibody responses to DENV NS1 by enzyme-linked immunosorbent assay (ELISA) in a longitudinal cohort of 266 confirmed dengue cases in Recife, Northeast Brazil. Samples were collected during the febrile phase and up to over 3 years after onset of symptoms. The antibodies investigated [IgA, IgM, total IgG (all subclasses measured together) and each subclass (IgG2, IgG3 and IgG4) measured separately] had distinct kinetic profiles following primary or secondary DENV infections. Of interest, most of these antibodies were consistently detected greater than 6 months after onset of symptoms, except for IgG3. Anti-dengue NS1-specific IgG was consistently detected from the acute phase to beyond 3 years after symptom onset. In contrast, anti-dengue NS1-specific IgG3 was detected within the first week, peaked at week 2-3, and disappeared within 4-6 months after onset of symptoms. The mean duration of the IgG3 positive signal was 149 days (ranging from 126 to 172 days). In conclusion, anti-dengue NS1-specific IgG and IgG3 are potential biomarkers of long-term and recent (less than 6 months) DENV infections, respectively.
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Affiliation(s)
- Eduardo J M Nascimento
- Graduate School of Public Health and Center for Vaccine Research, University of Pittsburgh, Biomedical Science Tower 3, room 9052, 3501 5th Avenue, Pittsburgh, PA 15261, USA.
| | - James W Huleatt
- Sanofi Pasteur, One Discovery Drive, Swiftwater, PA, 18370, USA
| | - Marli T Cordeiro
- Aggeu Magalhaes Institute, Oswaldo Cruz Foundation (FIOCRUZ), Av. Prof. Moraes Rego, s/n - Cidade Universitária - Campus da UFPE, CEP: 50.740-465, Recife, Pernambuco, Brazil
| | - Priscila M S Castanha
- Aggeu Magalhaes Institute, Oswaldo Cruz Foundation (FIOCRUZ), Av. Prof. Moraes Rego, s/n - Cidade Universitária - Campus da UFPE, CEP: 50.740-465, Recife, Pernambuco, Brazil; School of Medical Science, University of Pernambuco, Recife, Brazil
| | - James K George
- Sanofi Pasteur, One Discovery Drive, Swiftwater, PA, 18370, USA
| | - Eduard Grebe
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, Western Cape, South Africa
| | - Alex Welte
- DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, Western Cape, South Africa
| | - Monique Brown
- Sanofi Pasteur, One Discovery Drive, Swiftwater, PA, 18370, USA
| | - Donald S Burke
- Graduate School of Public Health and Center for Vaccine Research, University of Pittsburgh, Biomedical Science Tower 3, room 9052, 3501 5th Avenue, Pittsburgh, PA 15261, USA
| | - Ernesto T A Marques
- Graduate School of Public Health and Center for Vaccine Research, University of Pittsburgh, Biomedical Science Tower 3, room 9052, 3501 5th Avenue, Pittsburgh, PA 15261, USA; Aggeu Magalhaes Institute, Oswaldo Cruz Foundation (FIOCRUZ), Av. Prof. Moraes Rego, s/n - Cidade Universitária - Campus da UFPE, CEP: 50.740-465, Recife, Pernambuco, Brazil.
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Morrison CS, Homan R, Mack N, Seepolmuang P, Averill M, Taylor J, Osborn J, Dailey P, Parkin N, Ongarello S, Mastro TD. Assays for estimating HIV incidence: updated global market assessment and estimated economic value. J Int AIDS Soc 2018; 20. [PMID: 29165892 PMCID: PMC5810336 DOI: 10.1002/jia2.25018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 10/02/2017] [Indexed: 01/01/2023] Open
Abstract
Introduction Accurate incidence estimates are needed to characterize the HIV epidemic and guide prevention efforts. HIV Incidence assays are cost‐effective laboratory assays that provide incidence estimates from cross‐sectional surveys. We conducted a global market assessment of HIV incidence assays under three market scenarios and estimated the economic value of improved incidence assays. Methods We interviewed 27 stakeholders, and reviewed journal articles, working group proceedings, and manufacturers’ sales figures. We determined HIV incidence assay use in 2014, and estimated use in 2015 to 2017 and in 5 to 10‐years under three market scenarios, as well as the cost of conducting national and key population surveys using an HIV incidence assay with improved performance. Results Global 2014 HIV incidence assay use was 308,900 tests, highest in Asia and mostly for case‐ and population‐based surveillance. Estimated 2015 to 2017 use was 94,475 annually, with declines due to China and the United States discontinuing incidence assay use for domestic surveillance. Annual projected 5 to 10 year use under scenario 1 – no change in technology – was 94,475. For scenario 2 – a moderately improved incidence assay – projected annual use was 286,031. Projected annual use for scenario 3 – game‐changing technologies with an HIV incidence assay part of (a) standard confirmatory testing, and (b) standard rapid testing, were 500,000 and 180 million, respectively. As HIV incidence assay precision increases, decreased sample sizes required for incidence estimation resulted in $5 to 23 million annual reductions in survey costs and easily offset the approximately $3 million required to develop a new assay. Conclusions Improved HIV incidence assays could substantially reduce HIV incidence estimation costs. Continued development of HIV incidence assays with improved performance is required to realize these cost benefits.
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Affiliation(s)
| | - Rick Homan
- Global Health, Population and Nutrition, FHI 360, Durham, NC, USA
| | - Natasha Mack
- Global Health, Population and Nutrition, FHI 360, Durham, NC, USA
| | | | | | - Jamilah Taylor
- Global Health, Population and Nutrition, FHI 360, Durham, NC, USA
| | - Jennifer Osborn
- HIV/HCV Department, The Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Peter Dailey
- HIV/HCV Department, The Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Neil Parkin
- HIV/HCV Department, The Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Stefano Ongarello
- HIV/HCV Department, The Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Timothy D Mastro
- Global Health, Population and Nutrition, FHI 360, Durham, NC, USA
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41
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Infection Staging and Incidence Surveillance Applications of High Dynamic Range Diagnostic Immuno-Assay Platforms. J Acquir Immune Defic Syndr 2017; 76:547-555. [PMID: 28914669 DOI: 10.1097/qai.0000000000001537] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Custom HIV staging assays, including the Sedia HIV-1 Limiting Antigen (LAg) Avidity EIA and avidity modifications of the Ortho VITROS anti-HIV-1+2 and Abbott ARCHITECT HIV Ag/Ab Combo assays, are used to identify "recent" infections in clinical settings and for cross-sectional HIV incidence estimation. However, the high dynamic range of chemiluminescent platforms allows differentiating recent and long-standing infection on signal intensity, and this raises the prospect of using unmodified diagnostic assays for infection timing and surveillance applications. METHODS We tested a panel of 2500 well-characterized specimens with estimable duration of HIV infection with the 3 assays and the unmodified ARCHITECT. Regression models were used to estimate mean durations of recent infection (MDRIs), context-specific false-recent rates (FRRs) and correlation between diagnostic signal intensity and LAg measurements. Hypothetical epidemiological scenarios were constructed to evaluate utility in surveillance applications. RESULTS Over a range of MDRIs (reflecting recency discrimination thresholds), a diluted ARCHITECT-based RITA produced lower FRRs than the VITROS platform (FRR ≈ 0.5% and 1.5%, respectively at MDRI ≈ 200 days), and the unmodified diagnostic ARCHITECT produces incidence estimates with comparable precision to LAg (relative SE ≈ 17.5% and 15%, respectively at MDRI ≈ 200 days). ARCHITECT S/CO measurements were highly correlated with LAg optical density measurements (r = 0.80), and values below 200 are strongly predictive of LAg recency and duration of infection less than 1 year. CONCLUSIONS Low quantitative measurements from the unmodified ARCHITECT obviate the need for additional recency testing, and its use is feasible in clinical staging and incidence surveillance applications.
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Lynch BA, Patel EU, Courtney CR, Nanfack AJ, Bimela J, Wang X, Eid I, Quinn TC, Laeyendecker O, Nyambi PN, Duerr R, Redd AD. Short Communication: False Recent Ratio of the Limiting-Antigen Avidity Assay and Viral Load Testing Algorithm Among Cameroonians with Long-Term HIV Infection. AIDS Res Hum Retroviruses 2017; 33:1114-1116. [PMID: 28670965 DOI: 10.1089/aid.2017.0084] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Current serological assays that are used for cross-sectional HIV incidence estimation have been shown to misclassify individuals with chronic infection. Limited information exists on the performance of cross-sectional incidence assays in Central Africa. HIV-positive individuals from Cameroon who were infected for at least 1 or 2 years were evaluated to determine the false recent ratio (FRR) of a two-assay algorithm, which includes the Limiting Antigen Avidity (LAg-Avidity) assay (normalized optical density units, ODn <1.5) and HIV viral load (>1000 copies/ml). The subject-level FRR was 5.3% (95% confidence interval [CI], 2.1-10.5) for individuals infected for ≥1 year and 3.9% (95% CI, 0.8-11.0) for individuals infected for ≥2 years. These data suggest that the LAg-Avidity plus viral load incidence algorithm may overestimate HIV incidence rates in Central Africa.
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Affiliation(s)
- Briana A. Lynch
- Division of Intramural Research, NIAID, NIH, Baltimore, Maryland
| | - Eshan U. Patel
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | | | | | - Jude Bimela
- Department of Pathology, New York University, New York, New York
| | - Xiaohong Wang
- VA Medical Center, New York Harbor Healthcare Systems, New York, New York
| | - Issa Eid
- VA Medical Center, New York Harbor Healthcare Systems, New York, New York
| | - Thomas C. Quinn
- Division of Intramural Research, NIAID, NIH, Baltimore, Maryland
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Oliver Laeyendecker
- Division of Intramural Research, NIAID, NIH, Baltimore, Maryland
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Phillipe N. Nyambi
- Department of Pathology, New York University, New York, New York
- VA Medical Center, New York Harbor Healthcare Systems, New York, New York
| | - Ralf Duerr
- Department of Pathology, New York University, New York, New York
| | - Andrew D. Redd
- Division of Intramural Research, NIAID, NIH, Baltimore, Maryland
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
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43
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Huerga H, Shiferie F, Grebe E, Giuliani R, Farhat JB, Van-Cutsem G, Cohen K. 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; 17:653. [PMID: 28969607 PMCID: PMC5623964 DOI: 10.1186/s12879-017-2740-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 09/14/2017] [Indexed: 11/10/2022] Open
Abstract
Background Accurately identifying individuals who are on antiretroviral therapy (ART) is important to determine ART coverage and proportion on ART who are virally suppressed. ART is also included in recent infection testing algorithms used to estimate incidence. We compared estimates of ART coverage, viral load suppression rates and HIV incidence using ART self-report and detection of antiretroviral (ARV) drugs and we identified factors associated with discordance between the methods. Methods Cross-sectional population-based survey in KwaZulu-Natal, South Africa. Individuals 15–59 years were eligible. Interviews included questions about ARV use. Rapid HIV testing was performed at the participants’ home. Blood specimens were collected for ARV detection, LAg-Avidity HIV incidence testing and viral load quantification in HIV-positive individuals. Multivariate logistic regression models were used to identify socio-demographic covariates associated with discordance between self-reported ART and ARV detection. Results Of the 5649 individuals surveyed, 1423 were HIV-positive. Median age was 34 years and 76.3% were women. ART coverage was estimated at 51.4% (95%CI:48.5–54.3), 53.1% (95%CI:50.2–55.9) and 56.1% (95%CI:53.5–58.8) using self-reported ART, ARV detection and both methods combined (classified as ART exposed if ARV detected and/or ART reported) respectively. ART coverage estimates using the 3 methods were fairly similar within sex and age categories except in individuals aged 15–19 years: 33.3% (95%CI:23.3–45.2), 33.8% (95%CI:23.9–45.4%) and 44.3% (95%CI:39.3–46.7) using self-reported ART, ARV detection and both methods combined. Viral suppression below 1000cp/mL in individuals on ART was estimated at 89.8% (95%CI:87.3–91.9), 93.1% (95%CI:91.0–94.8) and 88.7% (95%CI:86.2–90.7) using self-reported ART, ARV detection and both methods combined respectively. HIV incidence was estimated at 1.4 (95%CI:0.8–2.0) new cases/100 person-years when employing no measure of ARV use, 1.1/100PY (95%CI:0.6–1.7) using self-reported ART, and 1.2/100PY (95%CI:0.7–1.7) using ARV detection. In multivariate analyses, individuals aged 15–19 years had a higher risk of discordance on measures of ARV exposure (aOR:9.4; 95%CI:3.9–22.8), while migrants had a lower risk (aOR:0.3; 95%CI:0.1–0.6). Conclusions In KwaZulu-Natal, the method of identifying ARV use had little impact on estimates of ART coverage, viral suppression rate and HIV incidence. However, discordant results were more common in younger individuals. This may skew estimates of ART coverage and viral suppression, particularly in adolescent surveys. Electronic supplementary material The online version of this article (10.1186/s12879-017-2740-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | - Eduard Grebe
- South African DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Ruggero Giuliani
- Medical Department, Médecins Sans Frontières, Cape Town, South Africa
| | | | - Gilles Van-Cutsem
- Medical Department, Médecins Sans Frontières, Cape Town, South Africa.,Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - Karen Cohen
- Division of Clinical Pharmacology, University of Cape Town, Cape Town, South Africa
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44
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Shepherd SJ, McDonald SA, Palmateer NE, Gunson RN, Aitken C, Dore GJ, Goldberg DJ, Applegate TL, Lloyd AR, Hajarizadeh B, Grebely J, Hutchinson SJ. HCV avidity as a tool for detection of recent HCV infection: Sensitivity depends on HCV genotype. J Med Virol 2017; 90:120-130. [PMID: 28843002 DOI: 10.1002/jmv.24919] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2017] [Accepted: 08/15/2017] [Indexed: 12/26/2022]
Abstract
Accurate detection of incident hepatitis C virus (HCV) infection is required to target and evaluate public health interventions, but acute infection is largely asymptomatic and difficult to detect using traditional methods. Our aim was to evaluate a previously developed HCV avidity assay to distinguish acute from chronic HCV infection. Plasma samples collected from recent seroconversion subjects in two large Australian cohorts were tested using the avidity assay, and the avidity index (AI) was calculated. Demographic and clinical characteristics of patients with low/high AI were compared via logistic regression. Sensitivity and specificity of the assay for recent infection and the mean duration of recent infection (MDRI) were estimated stratified by HCV genotype. Avidity was assessed in 567 samples (from 215 participants), including 304 with viraemia (defined as ≥250 IU/mL). An inverse relationship between AI and infection duration was found in viraemic samples only. The adjusted odds of a low AI (<30%) decreased with infection duration (odds ratio [OR] per week of 0.93; 95% CI:0.89-0.97), and were lower for G1 compared with G3 samples (OR = 0.14; 95% CI:0.05-0.39). Defining recent infection as <26 weeks, sensitivity (at AI cut-off of 20%) was estimated at 48% (95% CI:39-56%), 36% (95% CI:20-52%), and 65% (95% CI:54-75%) and MDRI was 116, 83, and 152 days for all genotypes, G1, and G3, respectively. Specificity (≥52 weeks infection duration, all genotypes) was 96% (95% CI:90-98%). HCV avidity testing has utility for detecting recent HCV infection in patients, and for assessing progress in reaching incidence targets for eliminating transmission, but variation in assay performance across genotype should be recognized.
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Affiliation(s)
- Samantha J Shepherd
- West of Scotland Specialist Virology Centre, Glasgow Royal Infirmary, Glasgow, Scotland, UK
| | - Scott A McDonald
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, Scotland, UK.,Health Protection Scotland, Glasgow, Scotland, UK
| | | | - Rory N Gunson
- West of Scotland Specialist Virology Centre, Glasgow Royal Infirmary, Glasgow, Scotland, UK
| | - Celia Aitken
- West of Scotland Specialist Virology Centre, Glasgow Royal Infirmary, Glasgow, Scotland, UK
| | - Gregory J Dore
- Kirby Institute, University of New South Wales, Sydney, Australia
| | - David J Goldberg
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, Scotland, UK.,Health Protection Scotland, Glasgow, Scotland, UK
| | | | - Andrew R Lloyd
- Kirby Institute, University of New South Wales, Sydney, Australia
| | | | - Jason Grebely
- Kirby Institute, University of New South Wales, Sydney, Australia
| | - Sharon J Hutchinson
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, Scotland, UK.,Health Protection Scotland, Glasgow, Scotland, UK
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45
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Park SY, Love TMT, Reynell L, Yu C, Kang TM, Anastos K, DeHovitz J, Liu C, Kober KM, Cohen M, Mack WJ, Lee HY. The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards. Sci Rep 2017; 7:7480. [PMID: 28785052 PMCID: PMC5547093 DOI: 10.1038/s41598-017-07490-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 06/29/2017] [Indexed: 11/09/2022] Open
Abstract
HIV incidence is a primary metric for epidemic surveillance and prevention efficacy assessment. HIV incidence assay performance is evaluated via false recency rate (FRR) and mean duration of recent infection (MDRI). We conducted a meta-analysis of 438 incident and 305 chronic specimens' HIV envelope genes from a diverse global cohort. The genome similarity index (GSI) accurately characterized infection stage across diverse host and viral factors. All except one chronic specimen had GSIs below 0.67, yielding a FRR of 0.33 [0-0.98] %. We modeled the incidence assay biomarker dynamics with a logistic link function assuming individual variabilities in a Beta distribution. The GSI probability density function peaked close to 1 in early infection and 0 around two years post infection, yielding MDRI of 420 [361, 467] days. We tested the assay by newly sequencing 744 envelope genes from 59 specimens of 21 subjects who followed from HIV negative status. Both standardized residuals and Anderson-Darling tests showed that the test dataset was statistically consistent with the model biomarker dynamics. This is the first reported incidence assay meeting the optimal FRR and MDRI performance standards. Signatures of HIV gene diversification can allow precise cross-sectional surveillance with a desirable temporal range of incidence detection.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Lucy Reynell
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Carl Yu
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Tina Manzhu Kang
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Kathryn Anastos
- Department of Medicine, and Epidemiology & Population Health, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, United States
| | - Jack DeHovitz
- Department of Medicine, SUNY Downstate Medical Center, Brooklyn, NY, United States
| | - Chenglong Liu
- Department of Medicine, Georgetown University, Washington, DC, United States
| | - Kord M Kober
- Department of Physiological Nursing, University of California San Francisco, San Francisco, CA, United States
| | - Mardge Cohen
- Department of Medicine, Stroger Hospital, Chicago, IL, United States
| | - Wendy J Mack
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
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46
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Schlusser KE, Konikoff J, Kirkpatrick AR, Morrison C, Chipato T, Chen PL, Munjoma M, Eshleman SH, Laeyendecker O. Short Communication: Comparison of Maxim and Sedia Limiting Antigen Assay Performance for Measuring HIV Incidence. AIDS Res Hum Retroviruses 2017; 33:555-557. [PMID: 28318310 DOI: 10.1089/aid.2016.0245] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Accurate methods for cross-sectional incidence estimation are needed for HIV prevention research. The Limiting Antigen Avidity (LAg-Avidity) assay has been marketed by two vendors, Maxim Biomedical and Sedia BioSciences Corporation. Performance differences between the two versions of the assay are unknown. We tested a total 1,410 treatment-naive samples with both versions of the assay. The samples came from 176 seroconverters from the Zimbabwe Hormonal Contraception and HIV Study. The correlation between the two versions of the assay was 0.93 for the optical density (OD) and 0.86 for the normalized OD. As the difference was more pronounced for the normalized OD, the difference in assays can be attributed to the calibrators. The mean duration of recent infection (MDRI), the average time individuals infected <2 years appear recently infected, was determined for both versions using an assay cutoff of 1.5 OD-n alone or in combination with a viral load cutoff of >1,000 copies/ml. The MDRI was 137 days for Sedia and 157 days for Maxim, with a difference of 20 days (95% CI 11-30). The MDRIs decreased to 102 and 120 days with the inclusion of a viral load cutoff of >1,000 copies/ml. These results imply that use of the Sedia LAg-Avidity will result in estimates of incidence ∼13% lower than those using the Maxim LAg-Avidity.
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Affiliation(s)
| | - Jacob Konikoff
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Allison R. Kirkpatrick
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
| | | | - Tsungai Chipato
- Department of Obstetrics and Gynecology, University of Zimbabwe, Harare, Zimbabwe
| | | | - Marshall Munjoma
- Department of Obstetrics and Gynecology, University of Zimbabwe, Harare, Zimbabwe
| | - Susan H. Eshleman
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, Maryland
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47
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Blaizot S, Kim AA, Zeh C, Riche B, Maman D, De Cock KM, Etard JF, Ecochard R. Estimating HIV Incidence Using a Cross-Sectional Survey: Comparison of Three Approaches in a Hyperendemic Setting, Ndhiwa Subcounty, Kenya, 2012. AIDS Res Hum Retroviruses 2017; 33:472-481. [PMID: 27824254 DOI: 10.1089/aid.2016.0123] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES Estimating HIV incidence is critical for identifying groups at risk for HIV infection, planning and targeting interventions, and evaluating these interventions over time. The use of reliable estimation methods for HIV incidence is thus of high importance. The aim of this study was to compare methods for estimating HIV incidence in a population-based cross-sectional survey. DESIGN/METHODS The incidence estimation methods evaluated included assay-derived methods, a testing history-derived method, and a probability-based method applied to data from the Ndhiwa HIV Impact in Population Survey (NHIPS). Incidence rates by sex and age and cumulative incidence as a function of age were presented. RESULTS HIV incidence ranged from 1.38 [95% confidence interval (CI) 0.67-2.09] to 3.30 [95% CI 2.78-3.82] per 100 person-years overall; 0.59 [95% CI 0.00-1.34] to 2.89 [95% CI 0.86-6.45] in men; and 1.62 [95% CI 0.16-6.04] to 4.03 [95% CI 3.30-4.77] per 100 person-years in women. Women had higher incidence rates than men for all methods. Incidence rates were highest among women aged 15-24 and 25-34 years and highest among men aged 25-34 years. CONCLUSION Comparison of different methods showed variations in incidence estimates, but they were in agreement to identify most-at-risk groups. The use and comparison of several distinct approaches for estimating incidence are important to provide the best-supported estimate of HIV incidence in the population.
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Affiliation(s)
- Stéphanie Blaizot
- Hospices Civils de Lyon, Service de Biostatistique, Lyon, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé, Villeurbanne, France
| | - Andrea A. Kim
- Division of Global HIV/AIDS, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Clement Zeh
- Division of HIV/AIDS Prevention, U.S. Centers for Disease Control and Prevention, Kisumu, Kenya
| | - Benjamin Riche
- Hospices Civils de Lyon, Service de Biostatistique, Lyon, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé, Villeurbanne, France
| | | | - Kevin M. De Cock
- Division of Global HIV/AIDS, U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Jean-François Etard
- Epicentre, Paris, France
- UMI 233 TransVIHMI, Institut de Recherche pour le Développement, INSERM U1175, Université de Montpellier, Montpellier, France
| | - René Ecochard
- Hospices Civils de Lyon, Service de Biostatistique, Lyon, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé, Villeurbanne, France
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48
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Kassanjee R, De Angelis D, Farah M, Hanson D, Labuschagne JPL, Laeyendecker O, Le Vu S, Tom B, Wang R, Welte A. Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'. STATISTICAL COMMUNICATIONS IN INFECTIOUS DISEASES 2017. [PMID: 29527254 DOI: 10.1515/scid-2016-0002.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The application of biomarkers for 'recent' infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) - the average time in the 'recent' state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the 'recent' state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best - while 'random effects' describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing 'recent'/'non-recent' classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects' (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.
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Affiliation(s)
- Reshma Kassanjee
- Department of Statistical Sciences, University of Cape Town, Rondebosch 7701, South Africa.,Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa
| | - Daniela De Angelis
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Marian Farah
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Debra Hanson
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jan Phillipus Lourens Labuschagne
- Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa.,South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA.,Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.,Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Stéphane Le Vu
- Département des Maladies Infectieuses, Institut de Veille Sanitaire, Saint-Maurice, France.,Institut National de la Santé et de la Recherche Médicale - U1018, Centre de Recherche en Épidémiologie et Santé des Populations, Université Paris Sud, Le Kremlin Bicêtre, France
| | - Brian Tom
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Rui Wang
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alex Welte
- Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa
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49
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Kassanjee R, De Angelis D, Farah M, Hanson D, Labuschagne JPL, Laeyendecker O, Le Vu S, Tom B, Wang R, Welte A. Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'. STATISTICAL COMMUNICATIONS IN INFECTIOUS DISEASES 2017; 9:20160002. [PMID: 29527254 PMCID: PMC5842819 DOI: 10.1515/scid-2016-0002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
The application of biomarkers for 'recent' infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) - the average time in the 'recent' state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the 'recent' state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best - while 'random effects' describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing 'recent'/'non-recent' classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects' (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.
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Affiliation(s)
- Reshma Kassanjee
- Department of Statistical Sciences, University of Cape Town, Rondebosch 7701, South Africa,Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa
| | - Daniela De Angelis
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Marian Farah
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Debra Hanson
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jan Phillipus Lourens Labuschagne
- Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa,South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA,Department of Medicine, Johns Hopkins University, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Stéphane Le Vu
- Département des Maladies Infectieuses, Institut de Veille Sanitaire, Saint-Maurice, France,Institut National de la Santé et de la Recherche Médicale – U1018, Centre de Recherche en Épidémiologie et Santé des Populations, Université Paris Sud, Le Kremlin Bicêtre, France
| | - Brian Tom
- Medical Research Council, MRC Biostatistics Unit, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Rui Wang
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA USA,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alex Welte
- Stellenbosch University, The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch, South Africa
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Schlusser KE, Pilcher C, Kallas EG, Santos BR, Deeks SG, Facente S, Keating SM, Busch MP, Murphy G, Welte A, Quinn T, Eshleman SH, Laeyendecker O. Comparison of cross-sectional HIV incidence assay results from dried blood spots and plasma. PLoS One 2017; 12:e0172283. [PMID: 28231277 PMCID: PMC5322916 DOI: 10.1371/journal.pone.0172283] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Accepted: 02/02/2017] [Indexed: 11/18/2022] Open
Abstract
Background Assays have been developed for cross-sectional HIV incidence estimation using plasma samples. Large scale surveillance programs are planned using dried blood spot (DBS) specimens for incidence assessment. However, limited information exists on the performance of HIV cross-sectional incidence assays using DBS. Methods The assays evaluated were: Maxim HIV-1 Limiting Antigen Avidity EIA (LAg-Avidity), Sedia HIV-1 BED-Capture EIA (BED-CEIA), and CDC modified BioRad HIV-1/2 Plus O Avidity-based Assay (CDC-BioRad Avidity) using pre-determined cutoff values. 100 matched HIV-1 positive plasma and DBS samples, with known duration of infection, from the Consortium for the Evaluation and Performance of HIV Incidence Assays repository were tested. All assays were run in duplicate. To examine the degree of variability within and between results for each sample type, both categorical and continuous results were analyzed. Associations were assessed with Bland Altman, R2 values and Cohen’s kappa coefficient (ĸ). Results Intra-assay variability using the same sample type was similar for all assays (R2 0.96 to 1.00). The R2 values comparing DBS and plasma results for LAg-Avidity, BED-CEIA, and CDC-BioRad Avidity were 0.96, 0.94, and 0.84, respectively. The concordance and ĸ values between DBS and plasma for all three assays were >87% and >0.64, respectively. The Bland-Altman analysis showed significant differences between plasma and DBS samples. For all three assays, a higher number of samples were classified as recent infections using DBS samples. Conclusions DBS and plasma sample results were highly correlated. However, when compared to plasma, each assay performed somewhat differently in DBS at the lower and higher ends of the dynamic range. DBS samples were more likely to be classified as recently infected by all three assays, which may lead to overestimation of incidence in surveys using performance criteria derived for plasma samples.
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Affiliation(s)
- Katherine E. Schlusser
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Christopher Pilcher
- Department of Medicine, School of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
| | | | | | - Steven G. Deeks
- Department of Medicine, School of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
| | - Shelley Facente
- Department of Medicine, School of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
| | - Sheila M. Keating
- Department of Medicine, School of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
- Blood Systems Research Institute, San Francisco, California, United States of America
| | - Michael P. Busch
- Department of Medicine, School of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
- Blood Systems Research Institute, San Francisco, California, United States of America
| | - Gary Murphy
- Public Health England, London, United Kingdom
| | - Alex Welte
- The South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Thomas Quinn
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
- Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Baltimore, MD, United States of America
| | - Susan H. Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
- Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Baltimore, MD, United States of America
- * E-mail:
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