论文标题
通过广义SEIR模型对巴西的Covid-19的流行分析
Epidemic analysis of COVID-19 in Brazil by a generalized SEIR model
论文作者
论文摘要
我们将采用广义SEIR模型来研究巴西Covid-19的爆发。特别是，我们想解释很长一段时间内感染水平上升水平的预测，在该国人口最多的州中重叠的当地爆发重叠。在中国爆发期间先前使用的模型中启发的时间依赖性动态SEIR模型被用来分析感染，恢复和死亡的时间轨迹。该模型的参数随时间而变化，并且考虑使用非线性最小二乘法。从2020年4月8日开始的模拟得出的结论是，巴西达到高峰的时间将在2020年7月21日，总累积感染案件约为982,000人；此外，估计的总死亡病例最终将达到192K。除此之外，在7月中旬左右的每日新感染病例和死亡病例中，巴西将达到高峰，每天被感染50k案件和近6.0K死亡。
We shall apply a generalized SEIR model to study the outbreak of COVID-19 in Brazil. In particular, we would like to explain the projections of the increase in the level of infection over a long period of time, overlapping large local outbreaks in the most populous states in the country. A time-dependent dynamic SEIR model inspired in a model previously used during the outbreak in China was used to analyses the time trajectories of infected, recovered, and deaths. The model has parameters that vary with time and are fitted considering a nonlinear least-squares method. The simulations starting from April 8, 2020, concluded that the time for a peak in Brazil will be in July 21, 2020 with total cumulative infected cases around 982K people; in addition, an estimated total death case will reach to 192K in the end. Besides that, Brazil will reach a peak in terms of daily new infected cases and death cases around the middle of July with 50K cases of infected and almost 6.0K daily deaths.
