BACKGROUND: Vaccination against human papillomavirus (HPV) types 16/18 is being implemented in many countries. There may be indirect benefit of HPV vaccination to nonvaccinated women, who may experience a reduced risk of infection with vaccine-preventable types (herd immunity). We attempt to disentangle the direct and indirect effects of HPV vaccination, while accounting for 14 oncogenic HPV types in a dynamic modeling framework. METHODS: On the basis of vaccine uptake among preadolescent girls in the Netherlands, we calculated how heterosexual transmission of HPV-16/18 is expected to change as a result of vaccination, and used these predictions in an individual-based simulation model of cervical carcinogenesis that considers 14 high-risk HPV types. Models were parameterized to match prevaccine data on type-specific HPV infection and cervical disease. RESULTS: At 50% vaccine coverage, the estimated lifetime infection risk in nonvaccinated women dropped from 0.46 (95% credible interval = 0.35-0.54) to 0.37 (0.26-0.46) for HPV-16, and from 0.40 (0.32-0.46) to 0.31 (0.22-0.36) [corrected] for HPV-18. For the whole population, we calculated an eventual 47% reduction in cervical cancer incidence, with 1 in 4 cases prevented among nonvaccinated women. The number of indirectly averted cancer cases was highest with vaccine coverage between 50% and 70%, approximating 70 cases per 100,000 women born from 2010 onward. CONCLUSIONS: HPV-16/18 vaccination of preadolescent girls will markedly lower infection rates among nonvaccinated women. Reduced transmission of vaccine-preventable HPV becomes a prominent aspect of cervical cancer control, especially in populations with moderate vaccine coverage.
BACKGROUND: Vaccination against human papillomavirus (HPV) types 16/18 is being implemented in many countries. There may be indirect benefit of HPV vaccination to nonvaccinated women, who may experience a reduced risk of infection with vaccine-preventable types (herd immunity). We attempt to disentangle the direct and indirect effects of HPV vaccination, while accounting for 14 oncogenic HPV types in a dynamic modeling framework. METHODS: On the basis of vaccine uptake among preadolescent girls in the Netherlands, we calculated how heterosexual transmission of HPV-16/18 is expected to change as a result of vaccination, and used these predictions in an individual-based simulation model of cervical carcinogenesis that considers 14 high-risk HPV types. Models were parameterized to match prevaccine data on type-specific HPV infection and cervical disease. RESULTS: At 50% vaccine coverage, the estimated lifetime infection risk in nonvaccinated women dropped from 0.46 (95% credible interval = 0.35-0.54) to 0.37 (0.26-0.46) for HPV-16, and from 0.40 (0.32-0.46) to 0.31 (0.22-0.36) [corrected] for HPV-18. For the whole population, we calculated an eventual 47% reduction in cervical cancer incidence, with 1 in 4 cases prevented among nonvaccinated women. The number of indirectly averted cancer cases was highest with vaccine coverage between 50% and 70%, approximating 70 cases per 100,000 women born from 2010 onward. CONCLUSIONS:HPV-16/18 vaccination of preadolescent girls will markedly lower infection rates among nonvaccinated women. Reduced transmission of vaccine-preventable HPV becomes a prominent aspect of cervical cancer control, especially in populations with moderate vaccine coverage.
Authors: Joseph P Fava; Jacob Colleran; Francesca Bignasci; Raymond Cha; Paul E Kilgore Journal: Hum Vaccin Immunother Date: 2017-06-12 Impact factor: 3.452
Authors: Harrell W Chesson; Elaine W Flagg; Laura Koutsky; Katherine Hsu; Elizabeth R Unger; Judith C Shlay; Peter Kerndt; Khalil G Ghanem; Jonathan M Zenilman; Michael Hagensee; Hillard Weinstock; S Deblina Datta Journal: Vaccine Date: 2013-05-10 Impact factor: 3.641
Authors: Tjalke A Westra; Irina Stirbu-Wagner; Sara Dorsman; Eric D Tutuhatunewa; Edwin L de Vrij; Hans W Nijman; Toos Daemen; Jan C Wilschut; Maarten J Postma Journal: BMC Infect Dis Date: 2013-02-07 Impact factor: 3.090
Authors: Mark Jit; Carol Levin; Marc Brisson; Ann Levin; Stephen Resch; Johannes Berkhof; Jane Kim; Raymond Hutubessy Journal: BMC Med Date: 2013-01-30 Impact factor: 8.775
Authors: Henrike J Vriend; Johannes A Bogaards; Fiona R M van der Klis; Mirte Scherpenisse; Hein J Boot; Audrey J King; Marianne A B van der Sande Journal: PLoS One Date: 2013-04-23 Impact factor: 3.240