Evidence map›Paper›PMID 37649792›Full record

ArticleInfectious Disease Modelling2023

Mathematical modeling of malaria transmission dynamics in humans with mobility and control states.

Gbenga Adegbite, Sunday Edeki, Itunuoluwa Isewon, Jerry Emmanuel, Titilope Dokunmu, Solomon Rotimi, Jelili Oyelade, Ezekiel Adebiyi

Open access · goldAbstract read
In one paragraph

Article in Infectious Disease Modelling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
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  5. Review
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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

8 authors at 2 institutions in 2 countries.

Gbenga AdegbiteCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Sunday EdekiCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Itunuoluwa IsewonCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Jerry EmmanuelDepartment of Computer and Information Sciences, Covenant University, Ota, Nigeria.
Titilope DokunmuCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Solomon RotimiCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Jelili OyeladeCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Ezekiel AdebiyiCovenant University Bioinformatics Research, Covenant University, Ota, Nigeria.
Covenant University · NGGerman Cancer Research Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malaria importation is one of the hypothetical drivers of malaria transmission dynamics across the globe. Several studies on malaria importation focused on the effect of the use of conventional malaria control strategies as approved by the World Health Organization (WHO) on malaria transmission dynamics but did not capture the effect of the use of traditional malaria control strategies by vigilant humans. In order to handle the aforementioned situation, a novel system of Ordinary Differential Equations (ODEs) was developed comprising the human and the malaria vector compartments. Analysis of the system was carried out to assess its quantitative properties. The novel computational algorithm used to solve the developed system of ODEs was implemented and benchmarked with the existing Runge-Kutta numerical solution method. Furthermore, simulations of different vigilant conditions useful to control malaria were carried out. The novel system of malaria models was well-posed and epidemiologically meaningful based on its quantitative properties. The novel algorithm performed relatively better in terms of model simulation accuracy than Runge-Kutta. At the best model-fit condition of 98% vigilance to the use of conventional and traditional malaria control strategies, this study revealed that malaria importation has a persistent impact on malaria transmission dynamics. In lieu of this, this study opined that total vigilance to the use of the WHO-approved and traditional malaria management tools would be the most effective control strategy against malaria importation.

Indexed as

Malaria importationNovel algorithmOrdinary differential equationQuantitative propertiesRunge-KuttaTraditional malaria control

Identifiers

PMID37649792
PMCPMC10463202
OpenAlexW4386034851

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.