Assistant Research Scientist
University of Michigan
Incidence of human papillomavirus (HPV) related cancers is increasing, generating substantial interest in understanding how trends in population prevalence of HPV infection are changing. However, there are no direct, population-scale measurements of HPV prevalence prior to 2003. Previous work using models to reconstruct historical trends have focused only on genital infection or seroprevalence (prevalence of antibodies) separately, and the results of these single-measure studies have been hard to reconcile. Here, we develop a mechanistic disease model fit jointly to cervicogential prevalence and seroprevalence in unvaccinated women in the USA using National Health and Nutrition Examination Survey data (2003-2010) and compare it to fits of statistical age-cohort models. We find that including a latent HPV state in our model significantly improves model fit and that antibody waning may be an important contributor to observed patterns of seroprevalence. Moreover, we find that the mechanistic model outperforms the statistical model and that the joint analysis prevents the inconsistencies that arise when estimating historical cohort trends in infection from genital prevalence and seroprevalence separately. Our analysis suggests that while there is substantial uncertainty associated with the estimation of historic HPV trends, there has likely been an increase in the force of infection for more recent birth cohorts. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.
Brouwer AF, Meza R, Eisenberg MC. (2019). Integrating measures of viral prevalence and seroprevalence: a mechanistic modelling approach to explaining cohort patterns of human papillomavirus in women in the USA. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 374(1773)