2018
DOI: 10.7763/ijmo.2018.v8.618
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Age Structural Model of Zika Virus

Abstract: Zika virus is mosquito-borne flavivirus. It can be transmitted between human by bitting of Aedes mosquitoes. It can also transmit chikungunya, yellow fever and dengue disease. Zika virus can spread through mosquito to human, human to mosquito and human to human. In this paper, we account the age structure of zika virus patiens. We divide into two groups: human and mosquito. Age structure of human population is separated two groups: juvenile and adult human. Standard dynamical modeling method is used for analyz… Show more

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Cited by 4 publications
(8 citation statements)
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“…It can be prevented by avoiding contact with the cases. The dynamical model is used for describing the transmission of many disease 13,14,15,16,17,18,19 . The common cold, influenza or allergies are diseases that have already been occurred.…”
Section: Discussionmentioning
confidence: 99%
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“…It can be prevented by avoiding contact with the cases. The dynamical model is used for describing the transmission of many disease 13,14,15,16,17,18,19 . The common cold, influenza or allergies are diseases that have already been occurred.…”
Section: Discussionmentioning
confidence: 99%
“…The local stability of this steady state can be determined from these conditions (Routh-Hurwitz conditions 15,16 ). L  ,where 0 ( ( 1) ) ()…”
Section: Local Stabilitymentioning
confidence: 99%
See 1 more Smart Citation
“…Gregory Piatetsky stated in the Knowledge Discovery (KDD) conference: “Weka is a landmark system in data mining and machine learning history for the research communities, cause it holds the toolkit that has undoubtedly gained such extensive espousal and survived for a prolonged period. [15]” There was substantial attention paid to the determination of how distinctive clustering techniques were utilized in different areas of the environment [16,17,18,19,20] and in the healthcare sector for different disease predictions [21,22,23,24,25,26,27,28,29,30,31,32]. In addition, K-mean and SOM (self-organizing map) were used in this study for grouping the clusters of the real-life diabetes dataset, after careful analysis by the literature.…”
Section: Introductionmentioning
confidence: 99%
“…There is considerable interest in determining how different classification techniques from machine learning can be utilized as disease prediction tools [17][18][19][20][21]. These tools have been used to diagnose diabetes [22], glaucoma [23], meningitis [24], coronary artery disease [25], asthma [26], cancer [27], hypertension [28], heart arrhythmia [29], tuberculosis [30], and other diseases [31,32].…”
Section: Introductionmentioning
confidence: 99%