A Bayesian evidence synthesis approach to estimate disease prevalence in hard-to-reach populations: hepatitis C in New York City

A Bayesian evidence synthesis approach to estimate disease prevalence in hard-to-reach populations: hepatitis C in New York City

Existing methods to estimate the prevalence of chronic hepatitis C (HCV) in New York City (NYC) are limited in scope and fail to assess hard-to-reach subpopulations with highest risk such as injecting drug users (IDUs). To address these limitations, we employ a Bayesian multi-parameter evidence synt...

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Bibliographic Details
Main Authors: Sarah Tan, Susanna Makela, Daliah Heller, Kevin Konty, Sharon Balter, Tian Zheng, James H. Stark
Format: Article
Language:English
Published: Elsevier 2018-06-01
Series:Epidemics
Online Access:http://www.sciencedirect.com/science/article/pii/S1755436516300755

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http://www.sciencedirect.com/science/article/pii/S1755436516300755

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