Carballosa Alejandro, Balsa-Barreiro José, Boullosa Pablo, Garea Adrián, Mira Jorge, Miramontes Ángel, Muñuzuri Alberto P
Group of Nonlinear Physics, Fac. Physics, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.
Galician Center for Mathematical Research and Technology (CITMAga), 15782 Santiago de Compostela, Spain.
Chaos Solitons Fractals. 2022 Jul;160:112156. doi: 10.1016/j.chaos.2022.112156. Epub 2022 May 26.
By March 14th 2022, Spain is suffering the sixth wave of the COVID-19 pandemic. All the previous waves have been intimately related to the degree of imposed mobility restrictions and its consequent release. Certain factors explain the incidence of the virus across regions revealing the weak locations that probably require some medical reinforcements. The most relevant ones relate with mobility restrictions by age and administrative competence, i.e., spatial constrains. In this work, we aim to find a mathematical descriptor that could identify the critical communities that are more likely to suffer pandemic outbreaks and, at the same time, to estimate the impact of different mobility restrictions. We analyze the incidence of the virus in combination with mobility flows during the so-called (roughly from August 1st to November 30th, 2020) using a SEIR compartmental model. After that, we derive a mathematical descriptor based on linear stability theory that quantifies the potential impact of becoming a hotspot. Once the model is validated, we consider different confinement scenarios and containment protocols aimed to control the virus spreading. The main findings from our simulations suggest that the confinement of the economically non-active individuals may result in a significant reduction of risk, whose effects are equivalent to the confinement of the total population. This study is conducted across the totality of municipalities in Spain.
截至2022年3月14日,西班牙正遭受新冠疫情的第六波冲击。此前的所有疫情波次都与实施的流动性限制程度及其随后的解除密切相关。某些因素解释了病毒在各地区的发病率,揭示了可能需要一些医疗增援的薄弱地区。最相关的因素与按年龄和行政权限实施的流动性限制有关,即空间限制。在这项工作中,我们旨在找到一个数学描述符,它可以识别更有可能遭受疫情爆发的关键社区,同时估计不同流动性限制的影响。我们使用SEIR分区模型分析了在所谓的“(大致从2020年8月1日至11月30日)期间病毒发病率与流动情况的结合。之后,我们基于线性稳定性理论推导出一个数学描述符,以量化成为热点地区的潜在影响。一旦模型得到验证,我们考虑不同的封锁方案和遏制措施以控制病毒传播。我们模拟的主要结果表明,对经济不活跃个体的封锁可能会导致风险显著降低,其效果等同于对全体人口的封锁。这项研究覆盖了西班牙的所有市镇。