Basnarkov Lasko, Tomovski Igor, Sandev Trifce, Kocarev Ljupco
SS. Cyril and Methodius University, Faculty of Computer Science and Engineering, Rudzer Boshkovikj 16, P.O. Box 393, 1000 Skopje, Macedonia.
Macedonian Academy of Sciences and Arts, Bul. Krste Misirkov, 2, P.O. Box 428, 1000 Skopje, Macedonia.
Chaos Solitons Fractals. 2022 Jul;160:112286. doi: 10.1016/j.chaos.2022.112286. Epub 2022 Jun 7.
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.
我们基于新冠疫情的特征引入了非马尔可夫SIR传染病传播模型，考虑了离散时间和连续时间版本。感染强度和恢复期的分布可以采用任意形式。通过对这些函数进行相应选择，结果表明该模型可简化为经典的马尔可夫情形。针对传染性和恢复的任意函数，通过解析方法确定了疫情阈值，并进行了数值验证。通过对2020年春季意大利、西班牙和英国第一波疫情进行建模，展示了该模型的相关性。
