The rapid spread of the coronavirus disease (COVID-19) has become a global threat affecting almost all countries in the world. As countries reach the infection peak, it is planned to return a new normal under different coexistence conditions in order to reduce the economic effects produced by the total or partial closure of companies, universities, shops, etc. Under such circumstances, the use of mathematical models to evaluate the transmission risk of COVID-19 in various facilities represents an important tool in assisting authorities to make informed decisions. On the other hand, agent-based modeling is a relatively new approach to model complex systems composed of agents whose behavior is described using simple rules. Different from classical mathematical models (which consider a homogenous population), agent-based approaches model individuals with distinct characteristics and provide more realistic results. In this paper, an agent-based model to evaluate the COVID-19 transmission risks in facilities is presented. The proposed scheme has been designed to simulate the spatiotemporal transmission process. In the model, simulated agents make decisions depending on the programmed rules. Such rules correspond to spatial patterns and infection conditions under which agents interact to characterize the transmission process. The model also includes an individual profile for each agent, which defines its main social characteristics and health conditions used during its interactions. In general, this profile partially determines the behavior of the agent during its interactions with other individuals. Several hypothetical scenarios have been considered to show the performance of the proposed model. Experimental results have demonstrated that the simulations provide useful information to produce strategies for reducing the transmission risks of COVID-19 within the facilities.

冠状病毒病（COVID-19）的迅速传播已成为影响几乎世界所有国家的全球性威胁。随着国家达到感染高峰，计划减少不同共存条件下的新常态，以减少公司，大学，商店等全部或部分关闭所产生的经济影响。在这种情况下，使用数学评估各种设施中COVID-19传播风险的模型，是协助当局做出明智决定的重要工具。另一方面，基于代理的建模是一种相对较新的方法，可以对由代理组成的复杂系统建模，这些代理的行为使用简单的规则进行描述。与经典数学模型（考虑同质总体）不同，基于主体的方法对具有不同特征的个人进行建模，并提供更实际的结果。本文提出了一种基于代理的模型来评估设施中COVID-19的传播风险。提出的方案已被设计为模拟时空传输过程。在模型中，模拟代理根据编程规则做出决策。这些规则对应于媒介物相互作用以表征传播过程的空间模式和感染条件。该模型还包括每个代理的个人档案，该档案定义了其主要社会特征和互动过程中使用的健康状况。通常，此配置文件部分确定了代理与其他个体交互期间的行为。已经考虑了几种假设方案来说明所提出模型的性能。实验结果表明，该模拟提供了有用的信息，可用于制定降低设施内COVID-19传播风险的策略。