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Using data from respondent-driven sampling studies to estimate the number of people who inject drugs: Application to the Kohtla-Järve region of Estonia
Estimating the size of key risk populations is essential for determining the resources needed to implement effective public health intervention programs. Several standard methods for population size estimation exist, but the statistical and practical assumptions required for their use may not be met...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5667832/ https://www.ncbi.nlm.nih.gov/pubmed/29095866 http://dx.doi.org/10.1371/journal.pone.0185711 |
Sumario: | Estimating the size of key risk populations is essential for determining the resources needed to implement effective public health intervention programs. Several standard methods for population size estimation exist, but the statistical and practical assumptions required for their use may not be met when applied to HIV risk groups. We apply three approaches to estimate the number of people who inject drugs (PWID) in the Kohtla-Järve region of Estonia using data from a respondent-driven sampling (RDS) study: the standard “multiplier” estimate gives 654 people (95% CI 509–804), the “successive sampling” method gives estimates between 600 and 2500 people, and a network-based estimate that uses the RDS recruitment chain gives between 700 and 2800 people. We critically assess the strengths and weaknesses of these statistical approaches for estimating the size of hidden or hard-to-reach HIV risk groups. |
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