Non-Markovian SIR epidemic spreading model of COVID-19

We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete-and continuous-time versions. The distributions of infection intensity and recovery period may take an arbitrary form. 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, Spain and the UK, in the spring, 2020.(c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

We introduce a non-Markovian SIR epidemic spreading model inspired by the characteristics of COVID-19, by considering discrete and continuous-time versions. By selecting appropriate functions, the model can be reduced to the classical Markovian case. The relevance of the model is demonstrated by modeling the first wave of the epidemic in Italy, Spain, and the UK in spring 2020.