论文标题
COVID-19大流行：意大利，欧洲和美国未发现病例的流动性依赖性SEIR模型
COVID-19 pandemic: a mobility-dependent SEIR model with undetected cases in Italy, Europe and US
论文作者
论文摘要
目的：描述Covid-19大流行的第一波，重点是未发现的情况并评估不同的锁骨后情况。设计：研究介绍了一个SEIR隔间模型，考虑到未检测到的案例的特定区域部分，流动性限制的影响以及采用的个人保护措施，例如戴口罩和经常洗手。设置和参与者：该模型通过所有意大利地区，一些欧洲国家和美国的数据进行实验验证。主要结果度量：模型结果的准确性是通过平均绝对百分比误差（MAPE）和Lewis标准来衡量的；拟合参数与以前的文献非常吻合。结果：估计不同国家的流行曲线以及未发现和无症状病例的数量，这可能代表不久的将来的主要感染来源。该模型应用于Hubei案例研究，这是放松移动性限制的第一个地方。结果显示不同的情况。流动性和采用个人保护措施极大地影响了感染的动态，确定了巨大而快速的继发性峰值或更延迟且易于管理的峰值。结论：数学模型可以为医疗保健决策者提供有用的见解，以确定未来爆发的最佳策略。
OBJECTIVES: to describe the first wave of the COVID-19 pandemic with a focus on undetected cases and to evaluate different post-lockdown scenarios. DESIGN: the study introduces a SEIR compartmental model, taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions, and the personal protective measures adopted, such as wearing a mask and washing hands frequently. SETTING AND PARTICIPANTS: the model is experimentally validated with data of all the Italian regions, some European countries, and the US. MAIN OUTCOME MEASURES: the accuracy of the model results is measured through the mean absolute percentage error (MAPE) and Lewis criteria; fitting parameters are in good agreement with previous literature. RESULTS: the epidemic curves for different countries and the amount of undetected and asymptomatic cases are estimated, which are likely to represent the main source of infections in the near future. The model is applied to the Hubei case study, which is the first place to relax mobility restrictions. Results show different possible scenarios. Mobility and the adoption of personal protective measures greatly influence the dynamics of the infection, determining either a huge and rapid secondary epidemic peak or a more delayed and manageable one. CONCLUSIONS: mathematical models can provide useful insights for healthcare decision makers to determine the best strategy in case of future outbreaks.
