We present a model for the COVID-19 epidemic that offers analytical expressions for the newly registered and latent cases. This model is based on an epidemic branching process with latency that is greatly simplified when the bare memory kernel is given by an exponential function as observed in this pandemic. We expose the futility of the concept of “bending the curve” of the epidemic as long as the number of latent cases is not depleted. Our model offers the possibility of laying out different scenarios for the evolution of the epidemic in different countries based on the most recent observations and in terms of only two constants obtained from clinical trials.

我们提出了COVID-19流行病的模型，该模型为新近注册和潜在病例提供了分析表达式。该模型基于带有时延的流行病分支过程，当通过这种流行病中观察到的指数函数给裸内存内核提供时，该过程将大大简化。只要潜伏病例的数量没有耗尽，我们就暴露了流行病“弯曲曲线”这一概念是徒劳的。我们的模型提供了根据最新观察结果以及仅从临床试验中获得的两个常数为不同国家的流行病发展规划不同情景的可能性。