Non-Markovian SIR epidemic spreading model

Abstract

We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete- and continuous-time versions. The incubation period, delayed infectiousness and the distribution of the recovery period are modeled with general functions. By taking corresponding choice of these functions, it is shown that the model reduces to the classical Markovian case. The epidemic threshold is analytically determined for arbitrary functions of infectivity and recovery and verified numerically. The relevance of the model is shown by modeling the first wave of the epidemic in Italy, in the spring, 2020.

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Cited by in corpus (3)

• Non-Markovian epidemic spreading on temporal networks
• A four compartment epidemic model with retarded transition rates
• Evanescent random walker on networks: Hitting times, budget renewal, and survival dynamics