We present a new deterministic discrete time compartmental model of COVID-19 that explicitly considers relevant delays related to the stages of the disease, its diagnosis and report system, allowing to represent the presence of imported cases In addition to developing the model equations we describe an automatic parameter fitting mechanism using official data on the spread of the virus in Argentina The result consistently reflects the behaviour of the disease with respect to characteristic times: latency, infectious period, report of cases (confirmed and dead) and allows for detecting automatically changes in the reproductive number and in the mortality factor We also analyse the model's prediction capability and present simulation results assuming different future scenarios We include a usage of the model in a closed loop control scheme, where the explicit presence of delays plays a key role in projecting more realistic dynamics than that of classic continuous time models IEEE

中文翻译：

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具有显式延迟的阿根廷 COVID-19 传播的离散时间建模

我们提出了一种新的 COVID-19 确定性离散时间分区模型，该模型明确考虑了与疾病阶段、诊断和报告系统相关的相关延迟，允许表示输入病例的存在。除了开发模型方程外，我们还描述了一个使用阿根廷病毒传播官方数据的自动参数拟合机制 结果一致地反映了疾病在特征时间方面的行为：潜伏期、传染期、病例报告（确诊和死亡），并允许自动检测再生数和死亡率因素 我们还分析了模型的预测能力，并在假设不同的未来情景的情况下给出了模拟结果 我们在闭环控制方案中包含了模型的使用，与经典的连续时间模型 IEEE