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Robustness of Dengue Complex Network under Targeted versus Random Attack

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  • Hafiz Abid Mahmood Malik
  • Faiza Abid
  • Mohamed Ridza Wahiddin
  • Zeeshan Bhatti

Abstract

Dengue virus infection is one of those epidemic diseases that require much consideration in order to save the humankind from its unsafe impacts. According to the World Health Organization (WHO), 3.6 billion individuals are at risk because of the dengue virus sickness. Researchers are striving to comprehend the dengue threat. This study is a little commitment to those endeavors. To observe the robustness of the dengue network, we uprooted the links between nodes randomly and targeted by utilizing different centrality measures. The outcomes demonstrated that 5% targeted attack is equivalent to the result of 65% random assault, which showed the topology of this complex network validated a scale-free network instead of random network. Four centrality measures (Degree, Closeness, Betweenness, and Eigenvector) have been ascertained to look for focal hubs. It has been observed through the results in this study that robustness of a node and links depends on topology of the network. The dengue epidemic network presented robust behaviour under random attack, and this network turned out to be more vulnerable when the hubs of higher degree have higher probability to fail. Moreover, representation of this network has been projected, and hub removal impact has been shown on the real map of Gombak (Malaysia).

Suggested Citation

  • Hafiz Abid Mahmood Malik & Faiza Abid & Mohamed Ridza Wahiddin & Zeeshan Bhatti, 2017. "Robustness of Dengue Complex Network under Targeted versus Random Attack," Complexity, Hindawi, vol. 2017, pages 1-12, January.
    • Handle: RePEc:hin:complx:2515928
    DOI: 10.1155/2017/2515928
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    1. Samir Bhatt & Peter W. Gething & Oliver J. Brady & Jane P. Messina & Andrew W. Farlow & Catherine L. Moyes & John M. Drake & John S. Brownstein & Anne G. Hoen & Osman Sankoh & Monica F. Myers & Dylan , 2013. "The global distribution and burden of dengue," Nature, Nature, vol. 496(7446), pages 504-507, April.
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    1. P.B., Divya & Lekha, Divya Sindhu & Johnson, T.P. & Balakrishnan, Kannan, 2022. "Vulnerability of link-weighted complex networks in central attacks and fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    2. Li, Yijia & Hu, Xiaoxiao & Zhao, Peng, 2021. "On the reliability of a voting system under cyber attacks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Malik, Hafiz Abid Mahmood & Abid, Faiza & Wahiddin, Mohamed Ridza & Waqas, Ahmad, 2021. "Modeling of internal and external factors affecting a complex dengue network," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    4. Rita Der Sarkissian & Chadi Abdallah & Jean-Marc Zaninetti & Sara Najem, 2020. "Modelling intra-dependencies to assess road network resilience to natural hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 121-137, August.
    5. Zhe Li & Xinyu Huang, 2023. "Identifying Influential Spreaders Using Local Information," Mathematics, MDPI, vol. 11(6), pages 1-14, March.
    6. Qing Cai & Mahardhika Pratama & Sameer Alam, 2019. "Interdependency and Vulnerability of Multipartite Networks under Target Node Attacks," Complexity, Hindawi, vol. 2019, pages 1-16, November.

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