Evidence map›Paper›PMID 37883381›Full record

ArticlePloS one2023

Computational analysis of control of hepatitis B virus disease through vaccination and treatment strategies.

Azhar Iqbal Kashif Butt, Muhammad Imran, Javeria Aslam, Saira Batool, Saira Batool

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.1field-weighted citation impact, top 11% of its field
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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 1 institution in 3 countries.

Azhar Iqbal Kashif ButtDepartment of Mathematics and Statistics, College of Science, King Faisal University, Al-Ahsa, Saudi Arabia.ORCID 0000-0002-0846-1640
Muhammad ImranDepartment of Mathematics, GC University, Lahore, Pakistan.ORCID 0000-0002-6924-5220
Javeria AslamDepartment of Mathematics, GC University, Lahore, Pakistan.
Saira BatoolGovernment Associate College (W) Kamar Mashani, Mianwali, Pakistan.
Saira BatoolDepartment of Mathematics, GC University, Lahore, Pakistan.
Government College University, Lahore · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatitis B disease is an infection caused by a virus that severely damages the liver. The disease can be both acute and chronic. In this article, we design a new nonlinear SVEICHR model to study dynamics of Hepatitis B Virus (HBV) disease. The aim is to carry out a comprehensive mathematical and computational analysis by exploiting preventive measures of vaccination and hospitalization for disease control. Mathematical properties of proposed model such as boundedness, positivity, and existence and uniqueness of the solutions are proved. We also determine the disease free and endemic equilibrium points. To analyze dynamics of HBV disease, we compute a biologically important quantity known as the reproduction number R0 by using next generation method. We also investigate the stability at both of the equilibrium points. To control the spread of disease due to HBV, two feasible optimal control strategies with three different cases are presented. For this, optimal control problem is constructed and Pontryagin maximum principle is applied with a goal to put down the disease in the population. At the end, we present and discuss effective solutions obtained through a MATLAB code.

Indexed as

Hepatitis BHepatitis B virusHumansNonlinear DynamicsReproductionVaccination

Identifiers

PMID37883381
PMCPMC10602336
OpenAlexW4387954360

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.