Last data update: Jun 17, 2024. (Total: 47034 publications since 2009)
Records 1-6 (of 6 Records) |
Query Trace: Fellows IE [original query] |
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Triangulating truth and reaching consensus on population size, prevalence, and more: Modeling study
Fellows IE , Corcoran C , McIntyre AF . JMIR Public Health Surveill 2024 10 e48738 ![]() BACKGROUND: Population size, prevalence, and incidence are essential metrics that influence public health programming and policy. However, stakeholders are frequently tasked with setting performance targets, reporting global indicators, and designing policies based on multiple (often incongruous) estimates of these variables, and they often do so in the absence of a formal, transparent framework for reaching a consensus estimate. OBJECTIVE: This study aims to describe a model to synthesize multiple study estimates while incorporating stakeholder knowledge, introduce an R Shiny app to implement the model, and demonstrate the model and app using real data. METHODS: In this study, we developed a Bayesian hierarchical model to synthesize multiple study estimates that allow the user to incorporate the quality of each estimate as a confidence score. The model was implemented as a user-friendly R Shiny app aimed at practitioners of population size estimation. The underlying Bayesian model was programmed in Stan for efficient sampling and computation. RESULTS: The app was demonstrated using biobehavioral survey-based population size estimates (and accompanying confidence scores) of female sex workers and men who have sex with men from 3 survey locations in a country in sub-Saharan Africa. The consensus results incorporating confidence scores are compared with the case where they are absent, and the results with confidence scores are shown to perform better according to an app-supplied metric for unaccounted-for variation. CONCLUSIONS: The utility of the triangulator model, including the incorporation of confidence scores, as a user-friendly app is demonstrated using a use case example. Our results offer empirical evidence of the model's effectiveness in producing an accurate consensus estimate and emphasize the significant impact that the accessible model and app offer for public health. It offers a solution to the long-standing problem of synthesizing multiple estimates, potentially leading to more informed and evidence-based decision-making processes. The Triangulator has broad utility and flexibility to be adapted and used in various other contexts and regions to address similar challenges. |
The HIV care continuum for sexually active transgender women in three metropolitan municipalities in South Africa: findings from a biobehavioural survey 2018-19
Cloete A , Mabaso M , Savva H , van der Merwe LL , Naidoo D , Petersen Z , Kose Z , Mthembu J , Moyo S , Skinner D , Jooste S , Fellows IE , Shiraishi RW , Mwandingi SL , Simbayi LC . Lancet HIV 2023 10 (6) e375-e384 BACKGROUND: Despite high HIV prevalence in transgender women in sub-Saharan Africa, to our knowledge no study presents data across the HIV care continuum for this population in the region. The aim of this study was to estimate HIV prevalence and present data to develop the HIV care continuum indicators for transgender women in three South African metropolitan municipalities. METHODS: Biobehavioural survey data were collected among sexually active transgender women in the metropolitan municipalities of Johannesburg, Buffalo City, and Cape Town, South Africa. Transgender women (aged ≥18 years, self-reporting consensual sex with a man in the 6 months before the survey) were recruited using respondent-driven sampling (RDS). An interviewer-administered questionnaire was used to determine awareness of HIV status; blood specimens were collected on dried blood spots to test for HIV antibodies, antiretroviral treatment (ART) exposure, and viral load suppression. Population-based estimates of HIV 95-95-95 cascade indicators were derived by use of individualised RDS weights with RDS Analyst software. Multivariate stepwise backward logistic regression modelling was used to determine factors associated with each cascade indicator. All eligible participants were included in the final analysis. FINDINGS: Between July 26, 2018, and March 15, 2019, we enrolled 887 sexually active transgender women: 323 in Johannesburg, 305 in Buffalo City, and 259 in Cape Town. HIV prevalence was highest in Johannesburg where 229 (74·1%) of 309 tests were positive (weighted prevalence estimate 63·3%, 95% CI 55·5-70·5), followed by Buffalo City where 121 (43·7%) of 277 were positive (46·1%, 38·7-53·6), and then Cape Town where 122 (48·4%) of 252 were positive (45·6%, 36·7-54·7). In Johannesburg, an estimated 54·2% (95% CI 45·8-62·4) of transgender women with HIV knew their positive status, in Cape Town this was 24·2% (15·4-35·8), and in Buffalo City this was 39·5% (27·1-53·4). Among those who knew their status, 82·1% (73·3-88·5) in Johannesburg, 78·2% (57·9-90·3) in Cape Town, and 64·7% (45·2-80·2) in Buffalo City were on ART. Of those on ART, 34·4% (27·2-42·4) in Johannesburg, 41·2% (30·7-52·6) in Cape Town, and 55·0% (40·7-68·4) in Buffalo City were virally suppressed. INTERPRETATION: Innovative strategies are needed to inform efforts to diagnose and to treat transgender women living with HIV promptly to achieve viral load suppression. Differentiated HIV services tailored to transgender women of race groups other than Black South African, and those with low education attainment and low outreach exposure, innovative testing, and adherence strategies should be developed to improve the HIV cascade for South African transgender women. FUNDING: The US President's Emergency Plan For AIDS Relief and US Centers for Disease Control and Prevention. |
Improving biomarker-based HIV incidence estimation in the treatment era
Fellows IE , Hladik W , Eaton JW , Voetsch AC , Parekh BS , Shiraishi RW . Epidemiology 2023 34 (3) 353-364 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. |
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
Gurley SA , Stupp PW , Fellows IE , Parekh BS , Young PW , Shiraishi RW , Sullivan PS , Voetsch AC . J Acquir Immune Defic Syndr 2023 92 (3) 189-196 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. |
Population Size Estimation From Capture-Recapture Studies Using shinyrecap: Design and Implementation of a Web-Based Graphical User Interface.
McIntyre AF , Fellows IE , Gutreuter S , Hladik W . JMIR Public Health Surveill 2022 8 (4) e32645 ![]() ![]() BACKGROUND: Population size estimates (PSE) provide critical information in determining resource allocation for HIV services geared toward those at high risk of HIV, including female sex workers, men who have sex with men, and people who inject drugs. Capture-recapture (CRC) is often used to estimate the size of these often-hidden populations. Compared with the commonly used 2-source CRC, CRC relying on 3 (or more) samples (3S-CRC) can provide more robust PSE but involve far more complex statistical analysis. OBJECTIVE: This study aims to design and describe the Shiny application (shinyrecap), a user-friendly interface that can be used by field epidemiologists to produce PSE. METHODS: shinyrecap is built on the Shiny web application framework for R. This allows it to seamlessly integrate with the sophisticated CRC statistical packages (eg, Rcapture, dga, LCMCR). Additionally, the application may be accessed online or run locally on the user's machine. RESULTS: The application enables users to engage in sample size calculation based on a simulation framework. It assists in the proper formatting of collected data by providing a tool to convert commonly used formats to that used by the analysis software. A wide variety of methodologies are supported by the analysis tool, including log-linear, Bayesian model averaging, and Bayesian latent class models. For each methodology, diagnostics and model checking interfaces are provided. CONCLUSIONS: Through a use case, we demonstrated the broad utility of this powerful tool with 3S-CRC data to produce PSE for female sex workers in a subnational unit of a country in sub-Saharan Africa. |
A new method for estimating HIV incidence from a single cross-sectional survey
Fellows IE , Shiraishi RW , Cherutich P , Achia T , Young PW , Kim AA . PLoS One 2020 15 (8) e0237221 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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