Literature DB >> 25380503

Estimating seroprevalence of human papillomavirus type 16 using a mixture model with smoothed age-dependent mixing proportions.

Margaretha A Vink1, Jan van de Kassteele, Jacco Wallinga, Peter F M Teunis, Johannes A Bogaards.   

Abstract

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.

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Year:  2015        PMID: 25380503     DOI: 10.1097/EDE.0000000000000196

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  7 in total

1.  Integrating measures of viral prevalence and seroprevalence: a mechanistic modelling approach to explaining cohort patterns of human papillomavirus in women in the USA.

Authors:  Andrew F Brouwer; Rafael Meza; Marisa C Eisenberg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-05-27       Impact factor: 6.237

2.  Applying mixture model methods to SARS-CoV-2 serosurvey data from Geneva.

Authors:  Judith A Bouman; Sarah Kadelka; Silvia Stringhini; Francesco Pennacchio; Benjamin Meyer; Sabine Yerly; Laurent Kaiser; Idris Guessous; Andrew S Azman; Sebastian Bonhoeffer; Roland R Regoes
Journal:  Epidemics       Date:  2022-05-07       Impact factor: 5.324

3.  A Bivariate Mixture Model for Natural Antibody Levels to Human Papillomavirus Types 16 and 18: Baseline Estimates for Monitoring the Herd Effects of Immunization.

Authors:  Margaretha A Vink; Johannes Berkhof; Jan van de Kassteele; Michiel van Boven; Johannes A Bogaards
Journal:  PLoS One       Date:  2016-08-18       Impact factor: 3.240

4.  Estimating the incidence of rotavirus infection in children from India and Malawi from serial anti-rotavirus IgA titres.

Authors:  Aisleen Bennett; Nico Nagelkerke; Ellen Heinsbroek; Prasanna S Premkumar; Małgorzata Wnęk; Gagandeep Kang; Neil French; Nigel A Cunliffe; Naor Bar-Zeev; Ben Lopman; Miren Iturriza-Gomara
Journal:  PLoS One       Date:  2017-12-29       Impact factor: 3.240

5.  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).

Authors:  L Léon; J Pillonel; M Jauffret-Roustide; F Barin; Y Le Strat
Journal:  Epidemiol Infect       Date:  2019-01       Impact factor: 2.451

6.  Inferring infection hazard in wildlife populations by linking data across individual and population scales.

Authors:  Kim M Pepin; Shannon L Kay; Ben D Golas; Susan S Shriner; Amy T Gilbert; Ryan S Miller; Andrea L Graham; Steven Riley; Paul C Cross; Michael D Samuel; Mevin B Hooten; Jennifer A Hoeting; James O Lloyd-Smith; Colleen T Webb; Michael G Buhnerkempe
Journal:  Ecol Lett       Date:  2017-01-16       Impact factor: 9.492

7.  Estimating dengue transmission intensity from serological data: A comparative analysis using mixture and catalytic models.

Authors:  Victoria Cox; Megan O'Driscoll; Natsuko Imai; Ari Prayitno; Sri Rezeki Hadinegoro; Anne-Frieda Taurel; Laurent Coudeville; Ilaria Dorigatti
Journal:  PLoS Negl Trop Dis       Date:  2022-07-11
  7 in total

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