Evidence map›Paper›PMID 32842988›Full record

ArticleBMC infectious diseases2020

Hepatitis a virus infection in Central-West Tunisia: an age structured model of transmission and vaccination impact.

Kaouther Ayouni, Bechir Naffeti, Walid Ben Aribi, Jihène Bettaieb, Walid Hammami, Afif Ben Salah, Hamadi Ammar, Slimane Ben Miled, Henda Triki

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Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

9 authors.

Kaouther AyouniLaboratory of Clinical Virology - Pasteur Institute of Tunis, University of Tunis El Manar, 13, Place Pasteur, BP: 74-1002, Tunis, Tunisia. Kaouther.ayouni@live.fr.ORCID http://orcid.org/0000-0002-0872-5706
Bechir NaffetiLaboratory of Intelligent Networks and Nanotechnology, LARINA, University of Carthage, Tunis, Tunisia.
Walid Ben AribiLaboratory of Intelligent Networks and Nanotechnology, LARINA, University of Carthage, Tunis, Tunisia.
Jihène BettaiebClinical Investigation Center - Pasteur Institute of Tunis, University of Tunis El Manar, Street 15 Medenine Bardo, Tunis, Tunisia.
Walid HammamiLaboratory of Clinical Virology - Pasteur Institute of Tunis, University of Tunis El Manar, 13, Place Pasteur, BP: 74-1002, Tunis, Tunisia.
Afif Ben SalahClinical Investigation Center - Pasteur Institute of Tunis, University of Tunis El Manar, Street 15 Medenine Bardo, Tunis, Tunisia.
Hamadi AmmarLaboratory of Intelligent Networks and Nanotechnology, LARINA, University of Carthage, Tunis, Tunisia.
Slimane Ben MiledLaboratory of Bioinformatics, Biomathématics and Biostatistics, Pasteur Institute of Tunis, University of Tunis El Manar, 13, Place Pasteur, BP: 74-1002, Tunis, Tunisia.
Henda TrikiLaboratory of Clinical Virology - Pasteur Institute of Tunis, University of Tunis El Manar, 13, Place Pasteur, BP: 74-1002, Tunis, Tunisia.

Funding

Ministry of Health and the Ministry of High Education and Scientific Research PRF-4; CIC2016IPT02
6 · The paper itself

Abstract

backgroundThe epidemiological pattern of hepatitis A infection has shown dynamic changes in many parts of the world due to improved socio-economic conditions and the accumulation of seronegative subjects, which leads to possible outbreaks and increased morbidity rate. In Tunisia, the epidemiological status of hepatits A virus is currently unknown. However, over the past years higher numbers of symptomatic hepatitis A virus infection in school attendants and several outbreaks were reported to the Ministry of Health, especially from regions with the lowest socio-economic levels in the country. The aim of this study was to investigate the current seroprevalence of hepatitis A virus antibodies in central-west Tunisia and assess the impact of hepatitis A virus vaccination on hepatitis A epidemiology.

methodsSerum samples from 1379 individuals, aged 5-75 years, were screened for hepatitis A virus antibodies. Adjusted seroprevalence, incidence and force of infection parameters were estimated by a linear age structured SEIR (Susceptible-Exposed-Infectious-Recovered) compartmental model. A vaccine model was then constructed to assess the impact on hepatitis A virus epidemiology of 3 scenarios of vaccination strategies: one dose at 12-months of age, one dose at 6-years and one dose at 12-months and another at 6-years of age during 6 years.

resultsA rapid increase in anti-hepatitis A virus seroprevalence was noted during infancy and adolescence: 47% of subjects under 10-years-old are infected; the prevalence increases to 77% at 15-years and reaches 97% in subjects aged 30-years. The force of infection is highest between 10 and 30-years of age and the incidence declines with increasing age. The vaccine model showed that the 3-scenarios lead to a significant reduction of the fraction of susceptibles. The two doses scenario gives the best results. Single-dose vaccination at 6-years of age provides more rapid decrease of disease burden in school-aged children, as compared to single-dose vaccination at 12-months, but keeps with a non-negligible fraction of susceptibles among children < 6-years.

conclusionsOur study confirms the epidemiological switch from high to intermediate endemicity of hepatitis A virus in Tunisia and provides models that may help undertake best decisions in terms of vaccinations strategies.

Indexed as

Models, TheoreticalAdolescentAdultAgedAge FactorsChildChild, PreschoolFemaleHepatitis AHepatitis A AntibodiesHepatitis A virusHumansIncidenceMaleMiddle AgedPrevalenceHepatitis A AntibodiesHepatitis A virusMathematical modelPublic healthSeroprevalenceVaccination

Identifiers

PMID32842988
PMCPMC7477833

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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.