Estimating seroprevalence of human papillomavirus type 16 using a mixture model with smoothed age-dependent mixing proportions.
BACKGROUND
The presence in serum of antibodies to viral antigens is generally considered a well-defined marker of past infection or vaccination. However, analyses of serological data that use a cut-off value to classify individuals as seropositive are prone to misclassification bias, in particular when studying infections with a weak serological response, such as the sexually transmitted human papillomavirus (HPV).


METHODS
We analyzed the serological concentrations of HPV type 16 (HPV16) antibodies in the general Dutch population in 2006-2007, before the introduction of mass vaccination against HPV. We used a 2-component mixture model to represent persons who were seronegative or seropositive for HPV16. Component densities were assumed to be log-normally distributed, with parameters possibly dependent on sex. The age-dependent mixing proportions were smoothed using penalized splines to obtain a flexible seroprevalence profile.


RESULTS
Our results suggest that HPV16 seropositivity is associated with higher antibody concentrations in women as compared with men. Seroprevalence shows an increase starting from adolescence in men and women alike, coinciding with the age of sexual debut. Seroprevalence stabilizes in men around age 40, whereas it has a decreasing trend from age 50 onwards in women. Analyses that rely on a cut-off value to classify persons as seropositive yield substantially different seroprevalence profiles, leading to a qualitatively different interpretation of HPV16 infection dynamics.


CONCLUSIONS
Our results provide a benchmark for examining the effect of HPV16 vaccination in future serological surveys. Our method may prove useful for estimating seroprevalence of other infections with a weak serological response.
aCentre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; bDepartment of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands; cDepartment of Statistics, Mathematical Modelling and Data Logistics, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; and dHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA.
Margaretha A
MA
Vink
Jan
J
van de Kassteele
Jacco
J
Wallinga
Peter F M
PF
Teunis
Johannes A
JA
Bogaards
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000914:Antibodies, Viral / Q000276:immunology*; D002648:Child; D002675:Child, Preschool; D005260:Female; D052162:Human papillomavirus 16 / Q000276:immunology*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D030361:Papillomavirus Infections / Q000453:epidemiology* / Q000276:immunology; D016036:Seroepidemiologic Studies; D012737:Sex Factors; D055815:Young Adult
D000914:Antibodies, Viral