Estimating prevalence from dried blood spots without using biological cut-offs: application of a novel approach to hepatitis C virus in drug users in France (ANRS-Coquelicot survey)

• Published in: Epidemiology and infection 2019-01, Vol.147, p.e220-e220, Article e220
• Main Authors: Léon, L, Pillonel, J, Jauffret-Roustide, M, Barin, F, Le Strat, Y
• Format: Article
• Language: English
• Subjects: Adult; Age; Antibodies; Bayes Theorem; Bayesian analysis; Bioassays; Blood; Blood & organ donations; Cross-Sectional Studies; Diagnostic systems; Dried Blood Spot Testing - methods; Drug abuse; Drug Users - statistics & numerical data; Enzyme-Linked Immunosorbent Assay - methods; Epidemiology; Female; France - epidemiology; Hepacivirus - isolation & purification; Hepatitis; Hepatitis C; Hepatitis C - diagnosis; Hepatitis C - epidemiology; Hepatitis C Antibodies - blood; Homeless people; Humanities and Social Sciences; Humans; Immunoglobulins; Infections; Male; Middle Aged; Original Paper; Predictive Value of Tests; Prevalence; Random variables; Reproducibility of Results; Risk Assessment; RNA, Viral - blood; Serology; Specimen Handling; Splines; Testing laboratories; Viruses
• ISSN: 0950-2688; 1469-4409
• DOI: 10.1017/S0950268819001043

Seroprevalence estimation using cross-sectional serosurveys can be challenging due to inadequate or unknown biological cut-off limits of detection. In recent years, diagnostic assay cut-offs, fixed assay cut-offs and more flexible approaches as mixture modelling have been proposed to classify biological quantitative measurements into a positive or negative status. Our objective was to estimate the prevalence of anti-HCV antibodies among drug users (DU) in France in 2011 using a biological test performed on dried blood spots (DBS) collected during a cross-sectional serosurvey. However, in 2011, we did not have a cut-off value for DBS. We could not use the values for serum or plasma, knowing that the DBS value was not necessarily the same. Accordingly, we used a method which consisted of applying a two-component mixture model with age-dependent mixing proportions using penalised splines. The component densities were assumed to be log-normally distributed and were estimated in a Bayesian framework. Anti-HCV prevalence among DU was estimated at 43.3% in France and increased with age. Our method allowed us to provide estimates of age-dependent prevalence using DBS without having a specified biological cut-off value.