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Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach

BACKGROUND: Key populations, including female sex workers (FSWs), are at a disproportionately high risk for HIV infection. Estimates of the size of these populations serve as denominator data to inform HIV prevention and treatment programming and are necessary for the equitable allocation of limited...

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Autores principales: Wesson, Paul Douglas, Adhikary, Rajatashuvra, Jonas, Anna, Gerndt, Krysta, Mirzazadeh, Ali, Katuta, Frieda, Maher, Andrew, Banda, Karen, Mutenda, Nicholus, McFarland, Willi, Lowrance, David, Prybylski, Dimitri, Patel, Sadhna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437614/
https://www.ncbi.nlm.nih.gov/pubmed/30869646
http://dx.doi.org/10.2196/11737
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author Wesson, Paul Douglas
Adhikary, Rajatashuvra
Jonas, Anna
Gerndt, Krysta
Mirzazadeh, Ali
Katuta, Frieda
Maher, Andrew
Banda, Karen
Mutenda, Nicholus
McFarland, Willi
Lowrance, David
Prybylski, Dimitri
Patel, Sadhna
author_facet Wesson, Paul Douglas
Adhikary, Rajatashuvra
Jonas, Anna
Gerndt, Krysta
Mirzazadeh, Ali
Katuta, Frieda
Maher, Andrew
Banda, Karen
Mutenda, Nicholus
McFarland, Willi
Lowrance, David
Prybylski, Dimitri
Patel, Sadhna
author_sort Wesson, Paul Douglas
collection PubMed
description BACKGROUND: Key populations, including female sex workers (FSWs), are at a disproportionately high risk for HIV infection. Estimates of the size of these populations serve as denominator data to inform HIV prevention and treatment programming and are necessary for the equitable allocation of limited public health resources. OBJECTIVE: This study aimed to present the respondent-driven sampling (RDS) adjusted reverse tracking method (RTM; RadR), a novel population size estimation approach that combines venue mapping data with RDS data to estimate the population size, adjusted for double counting and nonattendance biases. METHODS: We used data from a 2014 RDS survey of FSWs in Windhoek and Katima Mulilo, Namibia, to demonstrate the RadR method. Information from venue mapping and enumeration from the survey formative assessment phase were combined with survey-based venue-inquiry questions to estimate population size, adjusting for double counting, and FSWs who do not attend venues. RadR estimates were compared with the official population size estimates, published by the Namibian Ministry of Health and Social Services (MoHSS), and with the unadjusted RTM. RESULTS: Using the RadR method, we estimated 1552 (95% simulation interval, SI, 1101-2387) FSWs in Windhoek and 453 (95% SI: 336-656) FSWs in Katima Mulilo. These estimates were slightly more conservative than the MoHSS estimates—Windhoek: 3000 (1800-3400); Katima Mulilo: 800 (380-2000)—though not statistically different. We also found 75 additional venues in Windhoek and 59 additional venues in Katima Mulilo identified by RDS participants’ responses that were not detected during the initial mapping exercise. CONCLUSIONS: The RadR estimates were comparable with official estimates from the MoHSS. The RadR method is easily integrated into RDS studies, producing plausible population size estimates, and can also validate and update key population maps for outreach and venue-based sampling.
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spelling pubmed-64376142019-04-17 Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach Wesson, Paul Douglas Adhikary, Rajatashuvra Jonas, Anna Gerndt, Krysta Mirzazadeh, Ali Katuta, Frieda Maher, Andrew Banda, Karen Mutenda, Nicholus McFarland, Willi Lowrance, David Prybylski, Dimitri Patel, Sadhna JMIR Public Health Surveill Original Paper BACKGROUND: Key populations, including female sex workers (FSWs), are at a disproportionately high risk for HIV infection. Estimates of the size of these populations serve as denominator data to inform HIV prevention and treatment programming and are necessary for the equitable allocation of limited public health resources. OBJECTIVE: This study aimed to present the respondent-driven sampling (RDS) adjusted reverse tracking method (RTM; RadR), a novel population size estimation approach that combines venue mapping data with RDS data to estimate the population size, adjusted for double counting and nonattendance biases. METHODS: We used data from a 2014 RDS survey of FSWs in Windhoek and Katima Mulilo, Namibia, to demonstrate the RadR method. Information from venue mapping and enumeration from the survey formative assessment phase were combined with survey-based venue-inquiry questions to estimate population size, adjusting for double counting, and FSWs who do not attend venues. RadR estimates were compared with the official population size estimates, published by the Namibian Ministry of Health and Social Services (MoHSS), and with the unadjusted RTM. RESULTS: Using the RadR method, we estimated 1552 (95% simulation interval, SI, 1101-2387) FSWs in Windhoek and 453 (95% SI: 336-656) FSWs in Katima Mulilo. These estimates were slightly more conservative than the MoHSS estimates—Windhoek: 3000 (1800-3400); Katima Mulilo: 800 (380-2000)—though not statistically different. We also found 75 additional venues in Windhoek and 59 additional venues in Katima Mulilo identified by RDS participants’ responses that were not detected during the initial mapping exercise. CONCLUSIONS: The RadR estimates were comparable with official estimates from the MoHSS. The RadR method is easily integrated into RDS studies, producing plausible population size estimates, and can also validate and update key population maps for outreach and venue-based sampling. JMIR Publications 2019-03-14 /pmc/articles/PMC6437614/ /pubmed/30869646 http://dx.doi.org/10.2196/11737 Text en ©Paul Douglas Wesson, Rajatashuvra Adhikary, Anna Jonas, Krysta Gerndt, Ali Mirzazadeh, Frieda Katuta, Andrew Maher, Karen Banda, Nicholus Mutenda, Willi McFarland, David Lowrance, Dimitri Prybylski, Sadhna Patel. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.03.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Wesson, Paul Douglas
Adhikary, Rajatashuvra
Jonas, Anna
Gerndt, Krysta
Mirzazadeh, Ali
Katuta, Frieda
Maher, Andrew
Banda, Karen
Mutenda, Nicholus
McFarland, Willi
Lowrance, David
Prybylski, Dimitri
Patel, Sadhna
Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title_full Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title_fullStr Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title_full_unstemmed Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title_short Estimating the Population Size of Female Sex Workers in Namibia Using a Respondent-Driven Sampling Adjustment to the Reverse Tracking Method: A Novel Approach
title_sort estimating the population size of female sex workers in namibia using a respondent-driven sampling adjustment to the reverse tracking method: a novel approach
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437614/
https://www.ncbi.nlm.nih.gov/pubmed/30869646
http://dx.doi.org/10.2196/11737
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