论文标题
建模和预测巴西的共同研究的早期演变
Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil
论文作者
论文摘要
我们使用巴西在2020年2月25日至2020年3月30日的最新数据模拟和预测巴西的共同-19大流行的早期演变。该早期不认识疾病在新领土上的流行病学特征的意识，是对感染者的实际疾病的次要疾病的次要宣传和及时的社会疾病的传播，以使蓬勃发展的蓬勃发展。我们使用SIR模型的两种变体，并包括一个参数，该参数包括社会距离措施的影响。短期和长期的预测表明，政府实施的社会疏远政策能够扁平化Covid-19的感染模式。但是，我们的结果还表明，如果此政策持续不足，它只能将感染的峰转移到将来，以使峰值的价值几乎相同。此外，我们的长期模拟预测结束政策的最佳日期。最后，我们表明，无症状个体的比例会影响有症状感染的峰值的幅度，这表明测试人群很重要。
We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter that comprises the effects of social distancing measures. Short and long term forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19. However, our results also show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value. Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population.
