Evidence map›Paper›PMID 31456852›Full record

ArticleOpen access Macedonian journal of medical sciences2019

Log-Linear Modelling of Effect of Age and Gender on the Spread of Hepatitis B Virus Infection in Lagos State, Nigeria.

Oluwole A Odetunmibi, Adebowale O Adejumo, Timothy A Anake

Abstract read
In one paragraph

Article in Open access Macedonian journal of medical sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Oluwole A OdetunmibiDepartment of Mathematics, College of Science and Technology, Covenant University, Ota, Nigeria.
Adebowale O AdejumoDepartment of Statistics, Faculty of Physical Sciences, University of Ilorin, Ilorin, Kwara State, Nigeria.
Timothy A AnakeDepartment of Mathematics, College of Science and Technology, Covenant University, Ota, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe effect of age and gender on the transmission of any infectious disease can be of great important because the age at which the host contact the disease may be a determinant on the rate at which the disease will spread.

aimThe purpose of this research is to model the significant effect of age and gender on the spread of hepatitis B virus using data collected from Lagos State, Nigeria. MATERIAL AND

methodsThe data that was used for this research is a ten years data covering the period of 2006 to 2015, which was collected from Nigeria Institute of Medical Research (NIMR). A log-linear modelling approach was employed using R programming language software. Akaike Information Criterion (AIC) method of model selection was used in selecting the best model.

resultsIt was discovered from the analysis that both factors (age and gender) have a significant effect on the spread of hepatitis B infection. This means that the age at which an individual is tested positive to hepatitis B virus will affect the spread of the disease. In choosing the best model among the four models that were developed, model AY: GY (age & year: gender and year) was found to be the best model.

conclusionAge and gender were found to act as a risk influencer that could have a great effect on the transmission of hepatitis B virus infections in Lagos state, Nigeria.

Indexed as

AICHepatitis BLog-linearModelingTransmission

Identifiers

PMID31456852
PMCPMC6698125

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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.