Evidence map›Paper›PMID 28589490›Full record

ArticleJournal of mathematical biology2018

Bifurcation thresholds and optimal control in transmission dynamics of arboviral diseases.

Hamadjam Abboubakar, Jean Claude Kamgang, Leontine Nkague Nkamba, Daniel Tieudjo

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In one paragraph

Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.2field-weighted citation impact, top 37% 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

9 citing papers in PubMed, 4 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Hamadjam AbboubakarLaboratory of Analysis, Simulations and Tests (LASE), Department of Computer Engineering, UIT-University of Ngaoundere, P. O. Box 455, Ngaoundere, Cameroon. abboubakarhamadjam@yahoo.fr.
Jean Claude KamgangLaboratory of Experimental Mathematics (LME), Department of Mathematics and Computer Science, ENSAI-University of Ngaoundere, P. O. Box 455, Ngaoundere, Cameroon.
Leontine Nkague NkambaDepartment of Mathematics, Higher Teacher Training College, University of Yaounde I, P. O. Box 47, Yaoundé, Cameroon.
Daniel TieudjoLaboratory of Experimental Mathematics (LME), Department of Mathematics and Computer Science, ENSAI-University of Ngaoundere, P. O. Box 455, Ngaoundere, Cameroon.
University of Ngaoundéré · CMLaboratoire de Mathématiques d'Orsay · FRUniversité de Yaoundé I · CM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we derive and analyse a model for the control of arboviral diseases which takes into account an imperfect vaccine combined with some other control measures already studied in the literature. We begin by analysing the basic model without control. We prove the existence of two disease-free equilibrium points and the possible existence of up to two endemic equilibrium points (where the disease persists in the population). We show the existence of a transcritical bifurcation and a possible saddle-node bifurcation and explicitly derive threshold conditions for both, including defining the basic reproduction number, [Formula: see text], which provides whether the disease can persist in the population or not. The epidemiological consequence of saddle-node bifurcation is that the classical requirement of having the reproduction number less than unity, while necessary, is no longer sufficient for disease elimination from the population. It is further shown that in the absence of disease-induced death, the model does not exhibit this phenomenon. The model is extended by reformulating the model as an optimal control problem, with the use of five time dependent controls, to assess the impact of vaccination combined with treatment, individual protection and two vector control strategies (killing adult vectors and reduction of eggs and larvae). By using optimal control theory, we establish conditions under which the spread of disease can be stopped, and we examine the impact of combined control tools on the transmission dynamic of disease. The Pontryagin's maximum principle is used to characterize the optimal control. Numerical simulations and efficiency analysis show that, vaccination combined with other control mechanisms, would reduce the spread of the disease appreciably.

Indexed as

Models, BiologicalAnimalsArbovirus InfectionsBasic Reproduction NumberComputational BiologyComputer SimulationHumansInsect ControlMathematical ConceptsMosquito VectorsViral VaccinesViral VaccinesArboviral diseasesBifurcationEfficiency analysisOptimal controlPontryagin’s maximum principle (PMP)

Identifiers

PMID28589490
OpenAlexW2235317711

What OpenQuestion holds

Textmetadata
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.