Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece.
School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece.
Int J Environ Res Public Health. 2020 Sep 8;17(18):6525. doi: 10.3390/ijerph17186525.
The self-organizing mechanism is a universal approach that is widely followed in nature. In this work, a novel self-organizing model describing diffusion over a lattice is introduced. Simulation results for the model's active lattice sites demonstrate an evolution curve that is very close to those describing the evolution of infected European populations by COVID-19. The model was further examined against real data regarding the COVID-19 epidemic for seven European countries (with a total population of 290 million) during the periods in which social distancing measures were imposed, namely Italy and Spain, which had an enormous spread of the disease; the successful case of Greece; and four central European countries: France, Belgium, Germany and the Netherlands. The value of the proposed model lies in its simplicity and in the fact that it is based on a universal natural mechanism, which through the presentation of an equivalent dynamical system apparently documents and provides a better understanding of the dynamical process behind viral epidemic spreads in general-even pandemics, such as in the case of COVID-19-further allowing us to come closer to controlling such situations. Finally, this model allowed the study of dynamical characteristics such as the memory effect, through the autocorrelation function, in the studied epidemiological dynamical systems.
自组织机制是一种普遍遵循的自然法则。在这项工作中,引入了一种新的描述晶格扩散的自组织模型。对模型的活性晶格点的模拟结果表明,其演化曲线与描述 COVID-19 感染欧洲人群的演化非常接近。该模型还针对意大利和西班牙这两个疾病传播严重的国家,以及希腊这一成功案例,以及法国、比利时、德国和荷兰这四个中欧国家在实施社交距离措施期间的 COVID-19 疫情的真实数据进行了检验。该模型的价值在于其简单性以及基于普遍自然机制的事实,通过呈现等效动力系统,该模型显然记录并提供了对病毒流行传播背后的动力学过程的更好理解,即使是大流行,如 COVID-19 疫情,也使我们能够更好地控制这种情况。最后,该模型还通过自相关函数研究了所研究的流行病学动力系统中的记忆效应等动力学特征。