February 15, 2024Open Access

Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks

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Authors

DSDiogo H. SilvaUniversidade de São Paulo FRFrancisco A. RodriguesUniversidade Federal de São Carlos SFSilvio C. FerreiraUniversidade Federal de Viçosa

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Implication

Theoretical analysis reveals distinct critical scaling between discrete and continuous mean-field models in complex networks, highlighting how time discretization alters epidemic localization.

Key Points

Discrete epidemic link equations converge to continuous pair quenched mean field theory as the time step approaches zero, but discrete dynamics alter critical epidemic behavior.
Critical exponent theta equals 1 in discrete-time stochastic simulations near the epidemic threshold, diverging from continuous-time scaling of 1/(3-gamma) on power-law networks.
Theoretical model comparisons and stochastic simulations show that larger time steps amplify localization, highlighting how temporal discretization skews epidemic threshold estimates.

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Silva et al. (2024) studied this question.

synapsesocial.com/papers/68e79181b6db643587702eee https://doi.org/10.48550/arxiv.2402.10166

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Implication

Theoretical analysis reveals distinct critical scaling between discrete and continuous mean-field models in complex networks, highlighting how time discretization alters epidemic localization.

Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks

Discussion

Member takes

Implication

Key Points

Cite This Study

Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks

Discussion

Member takes

Implication

Key Points

Cite This Study

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