Modeling of internal and external factors affecting a complex dengue network

Malik, Hafiz Abid Mahmood; Abid, Faiza; Wahiddin, Mohamed Ridza; Waqas, Ahmad

doi:10.1016/j.chaos.2021.110694

Cited by 8 publications

(4 citation statements)

References 18 publications

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“…If A. aegypti bites any person and that person acquires the dengue virus (DENV), they also become the source of DENV. Figure 3 [11] depicts the transmission of DENV from an infected individual to another mosquito (not of the A. aegypti species) via a mosquito bite [3,5]. In addition, dengue symptoms often develop 4-14 days after a mosquito bite.…”

Section: Dengue Virus Outbreakmentioning

confidence: 99%

Network Formation and Analysis of Dengue Complex Network

Malik¹

2023

Infectious Diseases

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Several efforts have been made and are constantly being made to keep the Aedes aegypti virus under control. Numerous scholars are involved in the study of medicine, while others are working in computer science and mathematics to model the spread of this disease. This study will help to comprehend how this epidemic sickness behaves. A complex network has been established from the complex dengue phenomenon. We have evaluated dengue network topology by pondering scale-free network properties. The network’s resilience in tracking the dengue epidemic is measured by systematically removing nodes and links. The primary hubs of this network are emphasized, and the vulnerability of the network structure has been examined through an in-depth investigation of the dengue virus’s spreading behavior. Understanding the intricate web of dengue outbreaks relies heavily on geographic representation. The applied method on the dengue epidemic network and the results will be added as scientific additions to the literature on complex networks. Different network analysis metrics have been applied (closeness centrality, betweenness centrality, eigenvector centrality, network density), and the network’s stability has been evaluated. This network is extremely vulnerable to targeted attacks; results showed that after removing 8% of focal hubs, 34% of the network is destroyed.

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Section: Dengue Virus Outbreakmentioning

confidence: 99%

Network Formation and Analysis of Dengue Complex Network

Malik¹

2023

Infectious Diseases

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“…Simulations on network models were carried out, as in [15] ), who made a network model with the purpose of investigating the possible influence of vaccination and vector control on the virus transmission network. Malik et al [16] developed a network model that simulates possible internal and external factors that can cause or contribute to dengue virus transmission.…”

Section: Introductionmentioning

confidence: 99%

Complex network analysis of arboviruses in the same geographic domain: Differences and similarities

Santos

Miranda

Saba

et al. 2023

Chaos, Solitons & Fractals

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“…With the rapid expansion of computer science and data science in recent years, the research on the spread of network epidemics has entered a golden era, garnering significant interest from academics in mathematics, physics, and public health [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Immunization strategies for simplicial irreversible epidemic on simplicial complex

Zhang

et al. 2022

Front. Phys.

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Higher-order networks can be used to describe the interaction of multiple entities in real-world collective behaviors such as dining, conference attendance, and public transportation use. Collective behavior is often one of the main reasons for “super-spreading events” during epidemics. How to propose effective immunization strategies is a Frontier research topic in network science and public health. To the best of our knowledge, there is a lack of systematic research on immunization strategies for epidemics on higher-order networks. We use synthetic networks and real-world networks as underlying structures to construct simplicial complexes to describe higher-order interaction networks, including pairwise and group interactions, and then propose a simplicial irreversible epidemic spreading model (i.e., simplicial Susceptible-Infected-Removed model). The temporal evolution process of nodes in different states in the system is described by extending the Microscopic Markov Chain Approach. Based on the node degree index and betweenness index, immunization strategies are proposed on the higher-order networks. Through theoretical analysis and numerical simulations, we discuss the effects of different higher-order infection rates, immunization ratios, and immunization strategies on the simplicial irreversible epidemic spread. Under some specific parameter configurations, we observe continuous growth, discontinuous growth, reduction of outbreak threshold, etc.

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Modeling of internal and external factors affecting a complex dengue network

Cited by 8 publications

References 18 publications

Network Formation and Analysis of Dengue Complex Network

Network Formation and Analysis of Dengue Complex Network

Complex network analysis of arboviruses in the same geographic domain: Differences and similarities

Immunization strategies for simplicial irreversible epidemic on simplicial complex

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