Faculty of Informatics & Telecommunications, University of Ioannina, Arta, Greece.
Faculty of Informatics & Telecommunications, University of Ioannina, Arta, Greece; Institute of Health Sciences Education, Barts and the London School of Medicine & Dentistry (Malta campus), Queen Mary University of London, Victoria, Malta.
Epidemics. 2023 Sep;44:100706. doi: 10.1016/j.epidem.2023.100706. Epub 2023 Jul 5.
The SARS-CoV-2 infection (COVID-19) pandemic created an unprecedented chain of events at a global scale, with European counties initially following individual pathways on the confrontation of the global healthcare crisis, before organizing coordinated public vaccination campaigns, when proper vaccines became available. In the meantime, the viral infection outbreaks were determined by the inability of the immune system to retain a long-lasting protection as well as the appearance of SARS-CoV-2 variants with differential transmissibility and virulence. How do these different parameters regulate the domestic impact of the viral epidemic outbreak? We developed two versions of a mathematical model, an original and a revised one, able to capture multiple factors affecting the epidemic dynamics. We tested the original one on five European countries with different characteristics, and the revised one in one of them, Greece. For the development of the model, we used a modified version of the classical SEIR model, introducing various parameters related to the estimated epidemiology of the pathogen, governmental and societal responses, and the concept of quarantine. We estimated the temporal trajectories of the identified and overall active cases for Cyprus, Germany, Greece, Italy and Sweden, for the first 250 days. Finally, using the revised model, we estimated the temporal trajectories of the identified and overall active cases for Greece, for the duration of the 1230 days (until June 2023). As shown by the model, small initial numbers of exposed individuals are enough to threaten a large percentage of the population. This created an important political dilemma in most countries. Force the virus to extinction with extremely long and restrictive measures or merely delay its spread and aim for herd immunity. Most countries chose the former, which enabled the healthcare systems to absorb the societal pressure, caused by the increased numbers of patients, requiring hospitalization and intensive care.
SARS-CoV-2 感染（COVID-19）大流行在全球范围内引发了前所未有的连锁事件，欧洲国家最初在应对全球医疗保健危机时各自采取了不同的策略，之后在适当疫苗可用时才组织协调了公共疫苗接种运动。在此期间，病毒感染的爆发是由于免疫系统无法保持持久的保护，以及具有不同传染性和毒力的 SARS-CoV-2 变体的出现。这些不同的参数如何调节病毒疫情在国内的影响？我们开发了两个版本的数学模型，一个原始版本和一个修订版本，能够捕捉影响疫情动态的多个因素。我们在五个具有不同特征的欧洲国家对原始模型进行了测试，并在其中一个国家（希腊）对修订后的模型进行了测试。为了开发模型，我们使用了经典 SEIR 模型的修改版本，引入了与病原体估计流行病学、政府和社会反应以及隔离概念相关的各种参数。我们估计了塞浦路斯、德国、希腊、意大利和瑞典在最初 250 天内的确诊和总活跃病例的时间轨迹。最后，使用修订后的模型，我们估计了希腊在 1230 天（截至 2023 年 6 月）期间的确诊和总活跃病例的时间轨迹。正如模型所示，少量的暴露个体就足以威胁到很大比例的人口。这在大多数国家造成了一个重要的政治困境。是用极其漫长和严格的措施迫使病毒灭绝，还是仅仅延迟其传播并追求群体免疫。大多数国家选择了前者，这使医疗保健系统能够承受因住院和重症监护需求增加而导致的社会压力。
