论文标题
巴伊亚和巴西圣卡塔琳娜的COVID-19（SARS-COV-2）大流行的最佳控制问题
Optimal Control Concerns Regarding the COVID-19 (SARS-CoV-2) Pandemic in Bahia and Santa Catarina, Brazil
论文作者
论文摘要
COVID-19大流行是21世纪最深刻的健康危机。 SARS-COV-2病毒于2020年3月左右抵达巴西，其社会和经济强烈反弹是灾难性的。在本文中，研究了如何使用模型预测控制（MPC）来计划适当的社会距离政策，以减轻巴伊亚和圣卡塔琳娜州的大流行效应，这是巴西不同地区，文化和人口人群的两个州。此外，使用优化程序确定了这两个状态的易感感染重新授予的（SIRD）模型的参数。该过程的控制输入是将社会隔离指南传递给了人口。设计了两种MPC策略：a）集中式MPC，该集中式MPC协调两个州的单个控制策略； b）一个分散的策略，为每个状态求解一个优化。模拟结果显示出可以说明和比较这两种控制策略。该框架是处理这种大流行现象的准则。
The COVID-19 pandemic is the profoundest health crisis of the 21rst century. The SARS-CoV-2 virus arrived in Brazil around March, 2020 and its social and economical backlashes are catastrophic. In this paper, it is investigated how Model Predictive Control (MPC) could be used to plan appropriate social distancing policies to mitigate the pandemic effects in Bahia and Santa Catarina, two states of different regions, culture, and population demography in Brazil. In addition, the parameters of Susceptible-Infected-Recovered-Deceased (SIRD) models for these two states are identified using an optimization procedure. The control input to the process is a social isolation guideline passed to the population. Two MPC strategies are designed: a) a centralized MPC, which coordinates a single control policy for both states; and b) a decentralized strategy, for which one optimization is solved for each state. Simulation results are shown to illustrate and compare both control strategies. The framework serves as guidelines to deals with such pandemic phenomena.
