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Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator

Researchers use a variety of population size estimation methods to determine the sizes of key populations at elevated risk of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), an important step in quantifying epidemic impact, advocating for high-risk groups, and planning...

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Autores principales: Verdery, Ashton M., Weir, Sharon, Reynolds, Zahra, Mulholland, Grace, Edwards, Jessie K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768707/
https://www.ncbi.nlm.nih.gov/pubmed/31299014
http://dx.doi.org/10.1097/EDE.0000000000001059
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author Verdery, Ashton M.
Weir, Sharon
Reynolds, Zahra
Mulholland, Grace
Edwards, Jessie K.
author_facet Verdery, Ashton M.
Weir, Sharon
Reynolds, Zahra
Mulholland, Grace
Edwards, Jessie K.
author_sort Verdery, Ashton M.
collection PubMed
description Researchers use a variety of population size estimation methods to determine the sizes of key populations at elevated risk of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), an important step in quantifying epidemic impact, advocating for high-risk groups, and planning, implementing, and monitoring prevention, care, and treatment programs. Conventional procedures often use information about sample respondents’ social network contacts to estimate the sizes of key populations of interest. A recent study proposes a generalized network scale-up method that combines two samples—a traditional sample of the general population and a link-tracing sample of the hidden population—and produces more accurate results with fewer assumptions than conventional approaches. METHODS: We extended the generalized network scale-up method from link-tracing samples to samples collected with venue-based sampling designs popular in sampling key populations at risk of HIV. Our method obviates the need for a traditional sample of the general population, as long as the size of the venue-attending population is approximately known. We tested the venue-based generalized network scale-up method in a comprehensive simulation evaluation framework. RESULTS: The venue-based generalized network scale-up method provided accurate and efficient estimates of key population sizes, even when few members of the key population were sampled, yielding average biases below ±6% except when false-positive reporting error is high. It relies on limited assumptions and, in our tests, was robust to numerous threats to inference. CONCLUSIONS: Key population size estimation is vital to the successful implementation of efforts to combat HIV/AIDS. Venue-based network scale-up approaches offer another tool that researchers and policymakers can apply to these problems.
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spelling pubmed-67687072019-11-18 Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator Verdery, Ashton M. Weir, Sharon Reynolds, Zahra Mulholland, Grace Edwards, Jessie K. Epidemiology Infectious Diseases Researchers use a variety of population size estimation methods to determine the sizes of key populations at elevated risk of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), an important step in quantifying epidemic impact, advocating for high-risk groups, and planning, implementing, and monitoring prevention, care, and treatment programs. Conventional procedures often use information about sample respondents’ social network contacts to estimate the sizes of key populations of interest. A recent study proposes a generalized network scale-up method that combines two samples—a traditional sample of the general population and a link-tracing sample of the hidden population—and produces more accurate results with fewer assumptions than conventional approaches. METHODS: We extended the generalized network scale-up method from link-tracing samples to samples collected with venue-based sampling designs popular in sampling key populations at risk of HIV. Our method obviates the need for a traditional sample of the general population, as long as the size of the venue-attending population is approximately known. We tested the venue-based generalized network scale-up method in a comprehensive simulation evaluation framework. RESULTS: The venue-based generalized network scale-up method provided accurate and efficient estimates of key population sizes, even when few members of the key population were sampled, yielding average biases below ±6% except when false-positive reporting error is high. It relies on limited assumptions and, in our tests, was robust to numerous threats to inference. CONCLUSIONS: Key population size estimation is vital to the successful implementation of efforts to combat HIV/AIDS. Venue-based network scale-up approaches offer another tool that researchers and policymakers can apply to these problems. Lippincott Williams & Wilkins 2019-11 2019-09-30 /pmc/articles/PMC6768707/ /pubmed/31299014 http://dx.doi.org/10.1097/EDE.0000000000001059 Text en Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Infectious Diseases
Verdery, Ashton M.
Weir, Sharon
Reynolds, Zahra
Mulholland, Grace
Edwards, Jessie K.
Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title_full Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title_fullStr Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title_full_unstemmed Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title_short Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator
title_sort estimating hidden population sizes with venue-based sampling: extensions of the generalized network scale-up estimator
topic Infectious Diseases
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768707/
https://www.ncbi.nlm.nih.gov/pubmed/31299014
http://dx.doi.org/10.1097/EDE.0000000000001059
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