We investigate the spreading of SARS-CoV-2 in the state of Alagoas, northeast of Brazil, via an adaptive susceptible-infected-removed (SIR) model featuring dynamic recuperation and propagation rates. Input parameters are defined based on data made available by Alagoas Secretary of Health from April 19, 2020 on. We provide with the evolution of the basic reproduction number R0 and reproduce the historical series of the number of confirmed cases with less than 10% error. We offer predictions, from November 16 forward, over the epidemic situation in the near future and show that it will keep decelerating. Furthermore, the same model can be used to study the epidemic dynamics in other countries with great easiness and accuracy.

中文翻译：

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通过自适应 SIR 模型在巴西阿拉戈斯州演变 SARS-CoV-2

我们通过具有动态恢复和传播速率的自适应易感感染移除 (SIR) 模型调查 SARS-CoV-2 在巴西东北部阿拉戈斯州的传播。输入参数是根据阿拉戈斯卫生部长从 2020 年 4 月 19 日起提供的数据定义的。我们提供基本再生数的演变R0并重现历史序列的确诊病例数小于10%错误。从 11 月 16 日起，我们对近期的疫情进行预测，并表明疫情将继续减速。此外，同样的模型可以非常容易和准确地用于研究其他国家的流行病动态。