Literature DB >> 31494722

Delay in booster schedule as a control parameter in vaccination dynamics.

Zhen Wang1, Gergely Röst2,3, Seyed M Moghadas1.   

Abstract

The use of multiple vaccine doses has proven to be essential in providing high levels of protection against a number of vaccine-preventable diseases at the individual level. However, the effectiveness of vaccination at the population level depends on several key factors, including the dose-dependent protection efficacy of vaccine, coverage of primary and booster doses, and in particular, the timing of a booster dose. For vaccines that provide transient protection, the optimal scheduling of a booster dose remains an important component of immunization programs and could significantly affect the long-term disease dynamics. In this study, we developed a vaccination model as a system of delay differential equations to investigate the effect of booster schedule using a control parameter represented by a fixed time-delay. By exploring the stability analysis of the model based on its reproduction number, we show the disease persistence in scenarios where the booster dose is sub-optimally scheduled. The findings indicate that, depending on the protection efficacy of primary vaccine series and the coverage of booster vaccination, the time-delay in a booster schedule can be a determining factor in disease persistence or elimination. We present model results with simulations for a vaccine-preventable bacterial disease, Heamophilus influenzae serotype b, using parameter estimates from the previous literature. Our study highlights the importance of timelines for multiple-dose vaccination in order to enhance the population-wide benefits of herd immunity.

Entities:  

Keywords:  Booster schedule; Delay equations; Persistence; Reproduction number; Vaccination

Mesh:

Substances:

Year:  2019        PMID: 31494722      PMCID: PMC6858909          DOI: 10.1007/s00285-019-01424-6

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  19 in total

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Review 3.  Haemophilus influenzae type b conjugate vaccines: considerations for vaccination schedules and implications for developing countries.

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Review 4.  Effectiveness of Haemophilus influenzae type b vaccines administered according to various schedules: systematic review and meta-analysis of observational data.

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Journal:  Pediatr Infect Dis J       Date:  2013-11       Impact factor: 2.129

5.  Combating pertussis resurgence: One booster vaccination schedule does not fit all.

Authors:  Maria A Riolo; Pejman Rohani
Journal:  Proc Natl Acad Sci U S A       Date:  2015-01-20       Impact factor: 11.205

6.  Dynamics of natural immunity caused by subclinical infections, case study on Haemophilus influenzae type b (Hib).

Authors:  T Leino; K Auranen; P H Mäkelä; H Käyhty; A K Takala
Journal:  Epidemiol Infect       Date:  2000-12       Impact factor: 2.451

7.  Prevention and control of haemophilus influenzae type b disease: recommendations of the advisory committee on immunization practices (ACIP).

Authors:  Elizabeth C Briere; Lorry Rubin; Pedro L Moro; Amanda Cohn; Thomas Clark; Nancy Messonnier
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8.  Cost-effectiveness of a potential vaccine candidate for Haemophilus influenzae serotype 'a'.

Authors:  Affan Shoukat; Robert Van Exan; Seyed M Moghadas
Journal:  Vaccine       Date:  2018-02-16       Impact factor: 3.641

Review 9.  Comparing Haemophilus influenzae type b conjugate vaccine schedules: a systematic review and meta-analysis of vaccine trials.

Authors:  Nicola Low; Shelagh M Redmond; Anne W S Rutjes; Nahara A Martínez-González; Matthias Egger; Marcello di Nisio; Pippa Scott
Journal:  Pediatr Infect Dis J       Date:  2013-11       Impact factor: 2.129

10.  Modeling insights into Haemophilus influenzae type b disease, transmission, and vaccine programs.

Authors:  Michael L Jackson; Charles E Rose; Amanda Cohn; Fatima Coronado; Thomas A Clark; Jay D Wenger; Lisa Bulkow; Michael G Bruce; Nancy E Messonnier; Thomas W Hennessy
Journal:  Emerg Infect Dis       Date:  2012-01       Impact factor: 6.883

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2.  Short or Long Interval between Priming and Boosting: Does It Impact on the Vaccine Immunogenicity?

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