论文标题
建模由于19号造成的死亡率：一种贝叶斯方法
Modelling death rates due to COVID-19: A Bayesian approach
论文作者
论文摘要
目的：估计秘鲁19号死亡人数。设计：通过从中国Codiv-19造成的每日死亡人数和秘鲁当局的数据获得的先验信息，我们为秘鲁的死亡人数构建了一个预测性的贝叶斯非线性模型。暴露：COVID-19。结果：死亡人数。结果：假设干预水平与中国实施的干预水平相似，秘鲁的死亡总数预计为612（95％CI：604.3-833.7）。第一次报告死亡后63天，将观察到99％的预期死亡。估计死亡人数的屈曲点估计为第26天（95％CI：25.1-26.8）。结论：这些估计可以帮助当局监测流行病并实施策略，以管理Covid-19-19的大流行。
Objective: To estimate the number of deaths in Peru due to COVID-19. Design: With a priori information obtained from the daily number of deaths due to CODIV-19 in China and data from the Peruvian authorities, we constructed a predictive Bayesian non-linear model for the number of deaths in Peru. Exposure: COVID-19. Outcome: Number of deaths. Results: Assuming an intervention level similar to the one implemented in China, the total number of deaths in Peru is expected to be 612 (95%CI: 604.3 - 833.7) persons. Sixty four days after the first reported death, the 99% of expected deaths will be observed. The inflexion point in the number of deaths is estimated to be around day 26 (95%CI: 25.1 - 26.8) after the first reported death. Conclusion: These estimates can help authorities to monitor the epidemic and implement strategies in order to manage the COVID-19 pandemic.
