Evidence map›Paper›PMID 32776972›Full record

ArticlePloS one2020

Modelling hepatitis B virus infection and impact of timely birth dose vaccine: A comparison of two simulation models.

Margaret J de Villiers, Ivane Gamkrelidze, Timothy B Hallett, Shevanthi Nayagam, Homie Razavi, Devin Razavi-Shearer

Abstract readComparative Study
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
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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

6 authors.

Margaret J de VilliersMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Ivane GamkrelidzeCenter for Disease Analysis Foundation, Lafayette, Colorado, United States of America.ORCID 0000-0003-3843-670X
Timothy B HallettMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-9681-0424
Shevanthi NayagamMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-8030-3380
Homie RazaviCenter for Disease Analysis Foundation, Lafayette, Colorado, United States of America.ORCID 0000-0002-2658-6930
Devin Razavi-ShearerCenter for Disease Analysis Foundation, Lafayette, Colorado, United States of America.

Funding

Department of HealthMedical Research Council MR/R015600/1
6 · The paper itself

Abstract

Hepatitis B is a global epidemic that requires carefully orchestrated vaccination initiatives in geographical regions of medium to high endemicity to reach the World Health Organization's elimination targets by 2030. This study compares two widely-used deterministic hepatitis B models-the Imperial HBV model and the CDA Foundation's PRoGReSs-based on their predicted outcomes in four countries. The impact of scaling up of the timely birth dose of the hepatitis B vaccine is also investigated. The two models predicted largely similar outcomes for the impact of vaccination programmes on the projected numbers of new cases and deaths under high levels of the infant hepatitis B vaccine series. However, scenarios for the scaling up of the infant hepatitis B vaccine series had a larger impact in the PRoGReSs model than in the Imperial model due to the infant vaccine series directly leading to the reduction of perinatal transmission in the PRoGReSs model, but not in the Imperial model. Meanwhile, scaling up of the timely birth dose vaccine had a greater impact on the outcomes of the Imperial hepatitis B model than in the PRoGReSs model due to the greater protection that the birth dose vaccine confers to infants in the Imperial model compared to the PRoGReSs model. These differences underlie the differences in projections made by the models under some circumstances. Both sets of assumptions are consistent with available data and reveal a structural uncertainty that was not apparent in either model in isolation. Those relying on projections from models should consider outputs from both models and this analysis provides further evidence of the benefits of systematic model comparison for enhancing modelling analyses.

Indexed as

Models, StatisticalAdolescentAdultAgedAged, 80 and overChildChild, PreschoolFemaleGlobal HealthHepatitis BHepatitis B VaccinesHepatitis B virusHumansImmunization ProgramsInfantInfant, NewbornHepatitis B Vaccines

Identifiers

PMID32776972
PMCPMC7416941

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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.