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考虑医院基础设施影响的COVID-19动态：对巴西情况的调查

COVID-19 dynamics considering the influence of hospital infrastructure: an investigation into Brazilian scenarios.

作者信息

Pacheco Pedro M C L, Savi Marcelo A, Savi Pedro V

机构信息

Department of Mechanical Engineering, Centro Federal de Educação Tecnológica Celso Suckow da Fonseca - CEFET/RJ, Rio de Janeiro, 20.271.110 Brazil.

Center for Nonlinear Mechanics, COPPE - Department of Mechanical Engineering, Universidade Federal do Rio de Janeiro, P.O. Box 68.503, Rio de Janeiro, RJ 21.941.972 Brazil.

出版信息

Nonlinear Dyn. 2021;106(2):1325-1346. doi: 10.1007/s11071-021-06323-4. Epub 2021 Mar 13.

DOI:10.1007/s11071-021-06323-4
PMID:33746362
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7955701/
Abstract

COVID-19 dynamics is one of the most relevant subjects nowadays, and, in this regard, mathematical modeling and numerical simulations are of special interest. This paper describes COVID-19 dynamics based on a novel version of the susceptible-exposed-infectious-removed model. Removed population is split into recovered and death populations allowing a better comprehension of real situations. Besides, the total population is reduced based on the number of deaths. Hospital infrastructure is also included into the mathematical description allowing the consideration of collapse scenarios. Initially, a model verification is carried out calibrating system parameters with data from China outbreak that is considered a benchmark due the availability of data for the entire cycle. Afterward, Brazil outbreak is of concern, calibrating the model and developing numerical simulations. Results show several scenarios highlighting the importance of social isolation and hospital infrastructure. System dynamics has a strong sensitivity to transmission rate showing the importance of numerical simulations to guide public health decision strategies. Results also show that complex dynamical responses can emerge due to the oscillations of the transmission rate, being associated with distinct infection subsequent waves.

摘要

新冠疫情动态是当下最受关注的主题之一，在这方面，数学建模和数值模拟备受关注。本文基于易感-暴露-感染-康复模型的一个新版本描述了新冠疫情动态。康复人群从移除人群中分离出来，这样能更好地理解实际情况。此外，总人口根据死亡人数减少。医院基础设施也被纳入数学描述中，以便考虑医院不堪重负的情况。最初，通过使用中国疫情数据校准系统参数来进行模型验证，由于整个周期的数据可得性，中国疫情数据被视为一个基准。之后，巴西疫情受到关注，对模型进行校准并开展数值模拟。结果显示了多种情况，突出了社交隔离和医院基础设施的重要性。系统动态对传播率具有很强的敏感性，这表明数值模拟对于指导公共卫生决策策略很重要。结果还表明，由于传播率的波动，可能会出现复杂的动态响应，这与不同的后续感染波相关。

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