Literature DB >> 12410003

The theoretical population-level impact of a prophylactic human papilloma virus vaccine.

James P Hughes1, Geoff P Garnett, Laura Koutsky.   

Abstract

BACKGROUND: The ongoing development of a vaccine against human papillomavirus (HPV) raises important questions about the impact of various vaccination strategies.
METHODS: Two mathematical models are developed to explore the population-level impact of an HPV vaccine. The first model focuses on the infection process and the second on the disease process (specifically, cervical carcinoma and cancer).
RESULTS: Both population characteristics (, sexual mixing and rates of sex partner change) and vaccine characteristics affect the steady state prevalence of HPV that would be expected if a vaccine program is implemented. Under a particular set of assumptions, we find that vaccinating both men and women against a specific HPV type would result in a 44% decrease in prevalence of that type whereas vaccinating only women would result in a 30% reduction. We also find that if a vaccine gives protection against some, but not all, high risk types of HPV, the reduction in disease may be less than the reduction in HPV because the remaining high risk HPV types may replace the disease caused by the eliminated types.
CONCLUSIONS: A multivalent vaccine containing the majority of disease-causing HPV types would greatly reduce the need for colposcopy, biopsy and treatment. However, it is unlikely that Pap-screening programs would become redundant unless the vaccine is highly effective and coverage is widespread. In contrast to less common infections that are primarily restricted to core groups, targeting the vaccine towards the most sexually active individuals is less effective for a common sexually transmitted infection such as HPV.

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Year:  2002        PMID: 12410003     DOI: 10.1097/00001648-200211000-00006

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


  42 in total

1.  Cervical cancer pathogenesis is associated with one-carbon metabolism.

Authors:  Sujata Pathak; Neerja Bhatla; Neeta Singh
Journal:  Mol Cell Biochem       Date:  2012-06-23       Impact factor: 3.396

Review 2.  HPV-vaccination against cervical carcinoma: will it really work?

Authors:  Gerd Gross
Journal:  Med Microbiol Immunol       Date:  2007-02-21       Impact factor: 3.402

3.  Modelling heterogeneity and the impact of chemotherapy and vaccination against human hookworm.

Authors:  L Sabatelli; A C Ghani; L C Rodrigues; P J Hotez; S Brooker
Journal:  J R Soc Interface       Date:  2008-11-06       Impact factor: 4.118

4.  Controlling cervical cancer.

Authors:  Maurizio Bonati; Silvio Garattini
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

5.  Revisiting assumptions about age-based mixing representations in mathematical models of sexually transmitted infections.

Authors:  C W Easterly; F Alarid-Escudero; E A Enns; S Kulasingam
Journal:  Vaccine       Date:  2018-08-06       Impact factor: 3.641

6.  Difficulties in estimating the male-to-female sexual transmissibility of human papillomavirus infection.

Authors:  Ali Rowhani-Rahbar; James P Hughes; Laura A Koutsky
Journal:  Sex Transm Dis       Date:  2009-04       Impact factor: 2.830

7.  When do sexual partnerships need to be accounted for in transmission models of human papillomavirus?

Authors:  Heidi Muller; Chris Bauch
Journal:  Int J Environ Res Public Health       Date:  2010-02-22       Impact factor: 3.390

Review 8.  [Impact of prophylactic HPV vaccines on dermatology and venereology].

Authors:  G Gross
Journal:  Hautarzt       Date:  2007-06       Impact factor: 0.751

9.  Induction of immune responses against human papillomaviruses by hypervariable epitope constructs.

Authors:  K Jyotsna Reddy; Babak Banapour; David E Anderson; Sang H Lee; Juan P Marquez; Maria P Carlos; Jose V Torres
Journal:  Immunology       Date:  2004-06       Impact factor: 7.397

10.  An updated natural history model of cervical cancer: derivation of model parameters.

Authors:  Nicole G Campos; Emily A Burger; Stephen Sy; Monisha Sharma; Mark Schiffman; Ana Cecilia Rodriguez; Allan Hildesheim; Rolando Herrero; Jane J Kim
Journal:  Am J Epidemiol       Date:  2014-07-31       Impact factor: 4.897

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