Tzamali Eleftheria, Sakkalis Vangelis, Tzedakis Georgios, Spanakis Emmanouil G, Tzanakis Nikos
Computational Biomedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), 70013 Heraklion, Greece.
Department of Respiratory Medicine, University Hospital of Heraklion, Medical School, University of Crete, 71003 Heraklion, Greece.
Vaccines (Basel). 2023 Mar 24;11(4):722. doi: 10.3390/vaccines11040722.
The regulation policies implemented, the characteristics of vaccines, and the evolution of the virus continue to play a significant role in the progression of the SARS-CoV-2 pandemic. Numerous research articles have proposed using mathematical models to predict the outcomes of different scenarios, with the aim of improving awareness and informing policy-making. In this work, we propose an expansion to the classical SEIR epidemiological model that is designed to fit the complex epidemiological data of COVID-19. The model includes compartments for vaccinated, asymptomatic, hospitalized, and deceased individuals, splitting the population into two branches based on the severity of progression. In order to investigate the impact of the vaccination program on the spread of COVID-19 in Greece, this study takes into account the realistic vaccination program implemented in Greece, which includes various vaccination rates, different dosages, and the administration of booster shots. It also examines for the first time policy scenarios at crucial time-intervention points for Greece. In particular, we explore how alterations in the vaccination rate, immunity loss, and relaxation of measures regarding the vaccinated individuals affect the dynamics of COVID-19 spread. The modeling parameters revealed an alarming increase in the death rate during the dominance of the delta variant and before the initiation of the booster shot program in Greece. The existing probability of vaccinated people becoming infected and transmitting the virus sets them as catalytic players in COVID-19 progression. Overall, the modeling observations showcase how the criticism of different intervention measures, the vaccination program, and the virus evolution has been present throughout the various stages of the pandemic. As long as immunity declines, new variants emerge, and vaccine protection in reducing transmission remains incompetent; monitoring the complex vaccine and virus evolution is critical to respond proactively in the future.
所实施的管控政策、疫苗特性以及病毒的演变在新冠疫情的发展过程中持续发挥着重要作用。众多研究文章提议使用数学模型来预测不同情形的结果,以提高认知并为政策制定提供依据。在这项工作中,我们对经典的SEIR流行病学模型进行了扩展,旨在拟合新冠疫情复杂的流行病学数据。该模型包含了已接种疫苗者、无症状感染者、住院患者和死亡者的类别,根据病情发展的严重程度将人群分为两个分支。为了研究疫苗接种计划对希腊新冠疫情传播的影响,本研究考虑了希腊实施的实际疫苗接种计划,其中包括不同的接种率、不同剂量以及加强针的接种。它还首次考察了希腊在关键时间干预点的政策情景。特别是,我们探讨了接种率的变化、免疫力丧失以及针对已接种者措施的放宽如何影响新冠疫情传播的动态。建模参数显示,在希腊德尔塔变种占主导且加强针接种计划启动之前,死亡率出现了惊人的上升。已接种疫苗者感染并传播病毒的现有概率使他们成为新冠疫情发展中的催化因素。总体而言,建模观察结果展示了在疫情的各个阶段,对不同干预措施、疫苗接种计划和病毒演变的批评是如何存在的。只要免疫力下降、新变种出现且疫苗在减少传播方面的保护作用仍然不足,监测复杂的疫苗和病毒演变对于未来积极应对至关重要。