Results in Physics ( IF 5.3 ) Pub Date : 2021-07-16 , DOI: 10.1016/j.rinp.2021.104555 Carlos G Aguilar-Madera 1 , Gilberto Espinosa-Paredes 2 , E C Herrera-Hernández 3 , Jorge A Briones Carrillo 1 , J Valente Flores-Cano 1 , Víctor Matías-Pérez 1
In this work, we analyze the spreading of Covid-19 in Mexico using the spatial SEIRD epidemiologic model. We use the information of the 32 regions (states) that conform the country, such as population density, verified infected cases, and deaths in each state. We extend the SEIRD compartmental epidemiologic with diffusion mechanisms in the exposed and susceptible populations. We use the Fickian law with the diffusion coefficient proportional to the population density to encompass the diffusion effects. The numerical results suggest that the epidemiologic model demands time-dependent parameters to incorporate non-monotonous behavior in the actual data in the global dynamic. The diffusional model proposed in this work has great potential in predicting the virus spreading on different scales, i.e., local, national, and between countries, since the complete reduction in people mobility is impossible.
中文翻译:
Covid-19 在墨西哥的传播:扩散方法
在这项工作中,我们使用空间 SEIRD 流行病学模型分析了 Covid-19 在墨西哥的传播。我们使用符合全国的32个地区(州)的信息,例如每个州的人口密度、确诊感染病例和死亡人数。我们通过暴露人群和易感人群中的扩散机制扩展了 SEIRD 区室流行病学。我们使用菲克定律,其扩散系数与人口密度成正比,以涵盖扩散效应。数值结果表明,流行病学模型需要与时间相关的参数,以将非单调行为纳入全球动态的实际数据中。这项工作中提出的扩散模型在预测病毒在不同规模(即地方、全国和国家之间)的传播方面具有巨大潜力,因为完全减少人员流动是不可能的。