The semi-Markov framework is used to statistically characterize and evaluate the temporal structure of infected-state durations and demonstrates the importance of realistic sojourn-time modeling for understanding epidemic progression and for assessing the limitations of classical Markov-based epidemic models.
It is shown that such a simple model sufficiently reproduces the epidemic dynamics not only qualitatively, but also qualitatively with a high degree of correlation that allows to use it for forecast estimations.
Pachiyappan Duraisamy, Seethalakshmi Ramaswamy, S. Munirathinam et al.· Boletim da Sociedade Paranae...· 0 citations
The derivation of the rigorous sufficient conditions that characterize both the extinction and the long-term persistence of disease dynamics are derived, including a threshold parameter Λ, expressed in terms of the switching exponents ρξ(t) and ζξ(t), from a nonlinear stochastic SIRS epidemic model evolving in a random...
Khalid El Bakkioui, Mourad El Idrissi· Mathematical Biosciences· 0 citations
A stochastic framework for a broad class of heterogeneous SIR epidemic models with persistent individual heterogeneity that provides a unified probabilistic foundation for deterministic epidemic models with persistent individual heterogeneity is developed.
O. Izyumtseva, Wasiur R. KhudaBukhsh, M. Gomes et al.· 0 citations
This framework provides a probabilistically grounded extension of classical deterministic pulse vaccination models and offers new insights into the control of epidemics through scheduled immunization policies.
A retrospective analysis of COVID-19 transmission dynamics across U.S. states using a modified population-based Susceptible-Exposed-Infectious-Asymptomatic-Recovered-Deceased (SEIARD) compartmental model provides insights into state-level epidemic trajectories and supports data-driven decision-making for optimal alloca...
This work constructs, analyzes and simulates a new general SIR epidemiological model for the spread of a generic long-time disease, in which the coefficients of infectivity and death rate are system variables. Diseases, such as COVID-19, have demonstrated clearly that infectivity and death rates can change over time, e...
Emma Breidenich, J. Cooper, Qian-Zhao Huang et al.· Axioms· 0 citations
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