Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/71339
標題: Empirical Bayes approach to estimating the number of HIV-infected individuals in hidden and elusive populations
作者: Hsieh, Y.H.
Chen, C.W.S.
Lee, S.M.
關鍵字: injecting drug-use
capture-recapture
size
thailand
prevalence
models
inference
hiv/aids
glasgow
spread
期刊/報告no:: Statistics in Medicine, Volume 19, Issue 22, Page(s) 3095-3108.
摘要: In this paper we estimate the numbers of intravenous drug users (IVDUs) and commercial sex workers (CSWs) in Thailand infected with human immunodeficiency virus (HIV) who have not developed acquired immunodeficiency syndrome (AIDS) directly from the semi-annual HIV serosurveillance data of Thailand from June 1993 to June 1995. We propose a 'generalized removal model for open populations' for estimating HIV-infected population size within a hidden, elusive, and perhaps high-risk population group, for all sampling time when capture probabilities vary with time. We apply empirical Bayes methodology to the generalized removal model for open populations by using the Gibbs sampler, a Markov chain Monte Carlo method. No assumption on the size of the hidden population in question is needed to implement this procedure. The statistical method proposed here requires very little computing and only a minimum of two sets of serosurvey data to obtain an estimate, thereby providing a simple and viable option in epidemiological studies when either powerful computing facilities or abundant sampling data are lacking. Copyright (C) 2000 John Wiley & Sons, Ltd.
URI: http://hdl.handle.net/11455/71339
ISSN: 0277-6715
文章連結: http://dx.doi.org/10.1002/1097-0258(20001130)19:22<3095::aid-sim605>3.0.co
2-w
Appears in Collections:期刊論文

文件中的檔案:

取得全文請前往華藝線上圖書館



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.