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Nature of Complex Network of Dengue Epidemic as a Scale-Free Network
OBJECTIVES: Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a ran...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Medical Informatics
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689515/ https://www.ncbi.nlm.nih.gov/pubmed/31406610 http://dx.doi.org/10.4258/hir.2019.25.3.182 |
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author | Malik, Hafiz Abid Mahmood Abid, Faiza Mahmood, Nadeem Wahiddin, Mohamed Ridza Malik, Asif |
author_facet | Malik, Hafiz Abid Mahmood Abid, Faiza Mahmood, Nadeem Wahiddin, Mohamed Ridza Malik, Asif |
author_sort | Malik, Hafiz Abid Mahmood |
collection | PubMed |
description | OBJECTIVES: Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a random network. METHODS: A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient. RESULTS: It has been observed that dengue epidemic follows a power-law, with the value of its exponent γ = −2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period. CONCLUSIONS: The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner. |
format | Online Article Text |
id | pubmed-6689515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-66895152019-08-12 Nature of Complex Network of Dengue Epidemic as a Scale-Free Network Malik, Hafiz Abid Mahmood Abid, Faiza Mahmood, Nadeem Wahiddin, Mohamed Ridza Malik, Asif Healthc Inform Res Original Article OBJECTIVES: Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a random network. METHODS: A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient. RESULTS: It has been observed that dengue epidemic follows a power-law, with the value of its exponent γ = −2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period. CONCLUSIONS: The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner. Korean Society of Medical Informatics 2019-07 2019-07-31 /pmc/articles/PMC6689515/ /pubmed/31406610 http://dx.doi.org/10.4258/hir.2019.25.3.182 Text en © 2019 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Malik, Hafiz Abid Mahmood Abid, Faiza Mahmood, Nadeem Wahiddin, Mohamed Ridza Malik, Asif Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title | Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title_full | Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title_fullStr | Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title_full_unstemmed | Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title_short | Nature of Complex Network of Dengue Epidemic as a Scale-Free Network |
title_sort | nature of complex network of dengue epidemic as a scale-free network |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689515/ https://www.ncbi.nlm.nih.gov/pubmed/31406610 http://dx.doi.org/10.4258/hir.2019.25.3.182 |
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