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Identifying newly acquired cases of hepatitis C using surveillance: a literature review

Published online by Cambridge University Press:  01 June 2012

R. SACKS-DAVIS*
Affiliation:
Burnet Institute, Melbourne, Victoria, Australia Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Victoria, Australia
C. VAN GEMERT
Affiliation:
Burnet Institute, Melbourne, Victoria, Australia National Centre for Epidemiology and Population Health, Australian National University, Australian Capital Territory, Australia
I. BERGERI
Affiliation:
Burnet Institute, Melbourne, Victoria, Australia
M. STOOVE
Affiliation:
Burnet Institute, Melbourne, Victoria, Australia Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Victoria, Australia
M. HELLARD
Affiliation:
Burnet Institute, Melbourne, Victoria, Australia Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Victoria, Australia Melbourne School of Population Health, The University of Melbourne, Parkville, Victoria, Australia
*
*Author for correspondence: Ms. R. Sacks-Davis, Centre for Population Health, 85 Commercial Rd, Melbourne, Victoria, 3004, Australia. (Email: rachelsd@burnet.edu.au)
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Summary

Surveillance of newly acquired hepatitis C virus (HCV) infection is crucial for understanding the epidemiology of HCV and informing public health practice. However, monitoring such infections via surveillance systems is challenging because they are commonly asymptomatic. A literature review was conducted to identify methodologies used by HCV surveillance systems to identify newly acquired infections; relevant surveillance systems in 15 countries were identified. Surveillance systems used three main strategies to identify newly acquired infections: (1) asking physicians to classify cases; (2) identifying symptomatic cases or cases with elevated alanine aminotransferases; and (3) identifying cases with documented evidence of anti-HCV antibody seroconversion within a specific time-frame. Case-ascertainment methods varied with greater completeness of data in enhanced compared to passive surveillance systems. Automated systems that extract and link testing data from multiple laboratory and clinic databases may provide an opportunity for collecting testing histories for individuals that is less resource intensive than enhanced surveillance.

Information

Type
Review Article
Copyright
Copyright © Cambridge University Press 2012
Figure 0

Table 1. Key definitions