Suppress traffic-driven epidemic spreading in weighted network

Shao, Fei; Zhao, Wei; Chang, Zinan

doi:10.1007/s10586-018-2268-y

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Duan et al employed heterogeneous and stochastic agent-based models to analyze the characteristics of infectious diseases’ super spreaders [ 18 ]. Researchers also paid attention to epidemic dynamics in heterogeneous networks with different connectivities [ 19 , 20 , 21 ], and went forward and investigated epidemic spread in weighted networks representing the heterogeneity of individual interaction strengths [ 22 , 23 , 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Matrix-Based Formulation of Heterogeneous Individual-Based Models of Infectious Diseases: Using SARS Epidemic as a Case Study

Duan

2021

IJERPH

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Heterogeneities of individual attributes and behaviors play an important role in the complex process of epidemic spreading. Compared to differential equation-based system dynamical models of infectious disease transmission, individual-based epidemic models exhibit the advantage of providing a more detailed description of realities to capture heterogeneities across a population. However, the higher granularity and resolution of individual-based epidemic models comes with the cost of increased computational complexities, which result in difficulty in formulating individual-based epidemic models with mathematics. Furthermore, it requires great effort to understand and reproduce existing individual-based epidemic models presented by previous researchers. We proposed a mathematical formulation of heterogeneous individual-based epidemic models using matrices. Matrices and vectors were applied to represent individual attributes and behaviors. We derived analytical results from the matrix-based formulations of individual epidemic models, and then designed algorithms to force the computation of matrix-based individual epidemic models. Finally, we used a SARS epidemic control as a case study to verify the matrix-based formulation of heterogeneous individual-based epidemic models.

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