Researchers used a hybrid model (a combination of health resource demand model and disease transmission model), Bayesian model, and susceptible-exposed-infectious-removed (SEIR) model to predict health service utilization and deaths and mixed-effect nonlinear regression. Further, they used the mixture model to predict the number of confirmed cases and deaths or to predict when the curve would flatten. In this article, we show, through scenarios developed using system dynamics methodology, besides close to real-world results, the detrimental effects of ignoring social distancing guidelines (in terms of the number of people infected, which decreased as the percentage of noncompliance decreased).

中文翻译：

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在建立COVID-19确认案例模型中使用系统动力学方法

研究人员使用混合模型（健康资源需求模型和疾病传播模型的组合），贝叶斯模型和易感性传染病去除模型（SEIR）来预测卫生服务利用和死亡以及混合效应非线性回归。此外，他们使用混合模型来预测确诊病例和死亡人数或预测曲线何时变平。在本文中，我们展示了通过使用系统动力学方法开发的方案，除了接近真实结果之外，忽略社会疏离准则的有害影响（就感染人数而言，随着违规人数的减少而减少） 。