RESUMEN
Genital human papillomavirus (HPV) infections are caused by a broad diversity of genotypes. As available vaccines target a subgroup of these genotypes, monitoring transmission dynamics of nonvaccine genotypes is essential. After reviewing the epidemiological literature on study designs aiming to monitor those dynamics, we evaluated their abilities to detect HPV-prevalence changes following vaccine introduction. We developed an agent-based model to simulate HPV transmission in a heterosexual population under various scenarios of vaccine coverage and genotypic interaction, and reproduced two study designs: post-vs.-prevaccine and vaccinated-vs.-unvaccinated comparisons. We calculated the total sample size required to detect statistically significant prevalence differences at the 5% significance level and 80% power. Although a decrease in vaccine-genotype prevalence was detectable as early as 1 year after vaccine introduction, simulations indicated that the indirect impact on nonvaccine-genotype prevalence (a decrease under synergistic interaction or an increase under competitive interaction) would only be measurable after >10 years whatever the vaccine coverage. Sample sizes required for nonvaccine genotypes were >5 times greater than for vaccine genotypes and tended to be smaller in the post-vs.-prevaccine than in the vaccinated-vs.-unvaccinated design. These results highlight that previously published epidemiological studies were not powerful enough to efficiently detect changes in nonvaccine-genotype prevalence.
Asunto(s)
Infecciones por Papillomavirus , Vacunas contra Papillomavirus , Humanos , Infecciones por Papillomavirus/epidemiología , Vacunación , Estudios Epidemiológicos , Genotipo , Prevalencia , PapillomaviridaeRESUMEN
Human papillomaviruses are common sexually transmitted infections, caused by a large diversity of genotypes. In the context of vaccination against a subgroup of genotypes, better understanding the role of genotype interactions and human sexual behavior on genotype dynamics is essential. Herein, we present an individual-based model that integrates realistic heterosexual partnership behaviors and simulates interactions between vaccine and non-vaccine genotypes. Genotype interactions were considered, assuming a previous vaccine-genotype infection shortened (competition) or extended (synergy) the duration of a secondary non-vaccine-genotype infection. Sexual behavior determined papillomavirus acquisition and transmission: only 19.5% of active individuals at most 1 partner r during the year, but > 80% of those with ≥ 2 partners, were infected before vaccine introduction. The pre-vaccination situation was consistent with all genotype interaction scenarios. These genotype interactions, despite being undetectable during the pre-vaccination era, markedly impacted genotype prevalence after vaccination started, with a significant increase/decrease of non-vaccine genotypes prevalence for respectively competitive/synergistic interactions. These prevalence changes were more pronounced in individuals with ≤ 3 partners per year (up to 30% of prevalence modification assuming 65% vaccine coverage) but barely visible for individuals with > 3 partners per year (at most 0.30%). Results suggest the presence of genotype interaction, which is consistent with the pre-vaccine situation, may impact the dynamics of non-vaccine genotypes, particularly in less active individuals.