Evidence map›Paper›PMID 31494722›Full record

ArticleJournal of mathematical biology2019

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

Zhen Wang, Gergely Röst, Seyed M Moghadas

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zhen WangAgent-Based Modelling Laboratory, York University, Toronto, M3J 1P3, Canada.
Gergely RöstMathematical Institute, University of Oxford, Woodstock Road, Oxford, OX2 6GG, UK. rost@math.u-szeged.hu.ORCID 0000-0001-9476-3284
Seyed M MoghadasAgent-Based Modelling Laboratory, York University, Toronto, M3J 1P3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Models, StatisticalDisease EradicationHaemophilus InfectionsHaemophilus influenzaeHaemophilus VaccinesHumansImmunization ScheduleImmunization, SecondaryMass VaccinationTime FactorsVaccination CoverageHaemophilus VaccinesBooster scheduleDelay equationsPersistenceReproduction numberVaccination

Identifiers

PMID31494722
PMCPMC6858909

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.