In this paper, we present an age-structured SEIR model that uses contact patterns to reflect the physical distance measures implemented in Portugal to control the COVID-19 pandemic. By using these matrices and proper estimates for the parameters in the model, we were able to ascertain the impact of mitigation strategies employed in the past. Results show that the March 2020 lockdown had an impact on disease transmission, bringing the effective reproduction number ($\mathcal{R}\left(t\right)$) below 1. We estimate that there was an increase in the transmission after the initial lift of the measures on 6 May 2020 that resulted in a second wave that was curbed by the October and November measures. December 2020 saw an increase in the transmission reaching an $\mathcal{R}\left(t\right)$ = 1.45 in early January 2021. Simulations indicate that the lockdown imposed on the 15 January 2021 might reduce the intensive care unit (ICU) demand to below 200 cases in early April if it lasts at least 2 months. As it stands, the model was capable of projecting the number of individuals in each infection phase for each age group and moment in time.

中文翻译：

---

非药理学策略对葡萄牙控制COVID-19流行的影响的数学模型

在本文中，我们提出了一种年龄结构的SEIR模型，该模型使用接触模式反映了葡萄牙实施的物理距离测量方法，以控制COVID-19大流行。通过使用这些矩阵和模型中参数的正确估计，我们能够确定过去采用的缓解策略的影响。结果表明，2020年3月的封锁对疾病传播产生了影响，带来了有效的繁殖数量（$\mathcal{[R}（Ť）$）低于1.我们估计，在2020年5月6日首次取消措施之后，传输增加，导致第二波浪潮受到10月和11月措施的遏制。2020年12月，变速箱的传输量达到了$\mathcal{[R}（Ť）$= 2021年1月上旬= 1.45，模拟表明，如果持续至少2个月，则2021年1月15日实施的封锁可能会将重症监护病房（ICU）的需求减少到4月初的200例以下。就目前而言，该模型能够预测每个年龄段和每个时刻在每个感染阶段的人数。