Non-Markovian SIR epidemic spreading model of COVID-19
Lasko Basnarkov1,2, Igor Tomovski2, Trifce Sandev2,3,4
1SS. Cyril and Methodius University, Faculty of Computer Science and Engineering, Rudzer Boshkovikj 16, P.O. Box 393, 1000 Skopje, Macedonia.
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 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.
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