We present a classic SEIR model taking into account the daily movements of individuals in different places. The model also takes into account partial confinement of individuals. This model is coupled with a model of protection against the epidemic by the use of masks. We are studying the effects of combined confinement and protection measures on the dynamics of the epidemic. We consider a constant proportion of asymptomatic people. We assume that symptomatic infected people may change their urban travel behavior due to the disease which causes them to travel less to places where they used to move and to stay at home more often. We present a sensitivity study with respect to the parameters. We show that the combination of the use of masks with almost complete release of confinement makes it possible to avoid the occurrence of a secondary peak of the epidemic. The model predicts that a total release of confinement can be successful for an epidemic of \({\mathcal {R}}_0 = 2.5\) if on average a proportion of \(60\%\) of the population wears masks of \(60\%\) efficacy. However, if \(10\%\) of the population remains confined, the same goal can be achieved with a proportion of \(80\%\) of the population wearing masks with efficacy of the order of \(40\%\).

我们提出了一个经典的SEIR模型，考虑到个人在不同地方的日常活动。该模型还考虑了个人的部分限制。该模型与口罩防疫模型相结合。我们正在研究隔离和防护相结合的措施对疫情动态的影响。我们考虑无症状人群的固定比例。我们假设有症状的感染者可能会因疾病而改变他们的城市出行行为，导致他们减少前往曾经搬过的地方，而更多地呆在家里。我们提出了关于参数的敏感性研究。我们证明，使用口罩与几乎完全解除限制相结合，可以避免疫情二次高峰的发生。该模型预测，如果平均有\(60\%\)的人口佩戴口罩，那么对于\({\mathcal {R}}_0 = 2.5\)的流行病，完全解除限制就可以成功。 (60\%\)功效。然而，如果\(10\%\)的人口仍然受到限制，那么通过\(80\%\)的人口佩戴口罩的比例可以达到同样的目标，其功效约为\(40\%\) ） 。