The coronavirus disease (COVID-19) brought the world to a halt in March 2020. Various prediction and risk management approaches are being explored worldwide for decision making. This work adopts an advanced mechanistic model and utilizes tools for process safety to propose a framework for risk management for the current pandemic. A parameter tweaking and an artificial neural network-based parameter learning model have been developed for effective forecasting of the dynamic risk. Monte Carlo simulation was used to capture the randomness of the model parameters. A comparative analysis of the proposed methodologies has been carried out by using the susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD) model. A SEIQRD model was developed for four distinct locations: Italy, Germany, Ontario, and British Columbia. The learning-based approach resulted in better outcomes among the models tested in the present study. The layer of protection analysis is a useful framework to analyze the effect of different safety measures. This framework is used in this work to study the effect of non-pharmaceutical interventions on pandemic risk. The risk profiles suggest that a stage-wise releasing scenario is the most suitable approach with negligible resurgence. The case study provides valuable insights to practitioners in both the health sector and the process industries to implement advanced strategies for risk assessment and management. Both sectors can benefit from each other by using the mathematical models and the management tools used in each, and, more importantly, the lessons learned from crises.

2020 年 3 月，冠状病毒 (COVID-19) 使世界陷入停顿。世界范围内正在探索各种预测和风险管理方法以进行决策。这项工作采用先进的机械模型，并利用过程安全工具，提出了当前大流行的风险管理框架。已经开发了参数调整和基于人工神经网络的参数学习模型，用于有效预测动态风险。蒙特卡罗模拟用于捕捉模型参数的随机性。使用易感、暴露、感染、隔离、康复、死亡 (SEIQRD) 模型对所提出的方法进行了比较分析。SEIQRD 模型是为四个不同的地点开发的：意大利、德国、安大略省和不列颠哥伦比亚省。基于学习的方法在本研究中测试的模型中取得了更好的结果。保护分析层是分析不同安全措施效果的有用框架。本工作使用该框架来研究非药物干预措施对大流行风险的影响。风险状况表明，分阶段释放方案是最合适的方法，复苏的可能性可以忽略不计。该案例研究为卫生部门和流程工业的从业者提供了宝贵的见解，以实施风险评估和管理的先进策略。通过使用各自使用的数学模型和管理工具，以及更重要的是从危机中吸取的教训，这两个部门可以相互受益。