Abstract：
BACKGROUND: The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic\'s development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future.
METHODS: A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted.
CONCLUSIONS: There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases.
METHODS: A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted.
CONCLUSIONS: There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases.
摘要：
背景：2019年冠状病毒病（COVID-19）流行，被认为是近一个世纪以来最严重的全球公共卫生事件，严重影响了全球200多个国家和地区。要有效预防和控制疫情,研究人员广泛采用动态模型来预测和模拟疫情的发展，了解传播规律，评估干预措施的效果，告知疫苗接种策略，并协助制定防控措施。在这次审查中,本研究旨在梳理COVID-19动态模型中使用的隔室结构，为今后COVID-19等传染病的动态建模提供参考。
方法：对用于COVID-19建模的房室结构进行了范围审查。在这次范围审查中，对2021年5月14日之前发表的241篇研究文章进行了分析，以更好地了解COVID-19建模中使用的模型类型和隔室结构。分析了三种类型的动力学模型：基于易感-暴露-感染-恢复（SEIR）模型扩展的隔室模型，元种群模型，和基于代理的模型。基于SEIR模型的扩展隔室主要是根据COVID-19的传输特性，公共卫生干预措施，和年龄结构。元种群模型和基于代理的模型，作为更复杂的模型结构的权衡，一般采用基本易感-暴露-感染-恢复或简单扩张的隔室结构。
结论：有很多模型可以了解COVID-19的传播，并有助于预防和控制策略。研究人员根据实际情况建造隔间，研究目标和所用模型的复杂性。由于COVID-19的流行仍然不确定，对人类构成了重大挑战，研究人员仍然需要动态模型作为预测动态的主要工具，评估干预效果，为制定防控策略提供科学依据。本研究中审查的隔室结构为COVID-19的未来建模提供了指导，也为其他传染病的动态建模提供了建议。
方法：对用于COVID-19建模的房室结构进行了范围审查。在这次范围审查中，对2021年5月14日之前发表的241篇研究文章进行了分析，以更好地了解COVID-19建模中使用的模型类型和隔室结构。分析了三种类型的动力学模型：基于易感-暴露-感染-恢复（SEIR）模型扩展的隔室模型，元种群模型，和基于代理的模型。基于SEIR模型的扩展隔室主要是根据COVID-19的传输特性，公共卫生干预措施，和年龄结构。元种群模型和基于代理的模型，作为更复杂的模型结构的权衡，一般采用基本易感-暴露-感染-恢复或简单扩张的隔室结构。
结论：有很多模型可以了解COVID-19的传播，并有助于预防和控制策略。研究人员根据实际情况建造隔间，研究目标和所用模型的复杂性。由于COVID-19的流行仍然不确定，对人类构成了重大挑战，研究人员仍然需要动态模型作为预测动态的主要工具，评估干预效果，为制定防控策略提供科学依据。本研究中审查的隔室结构为COVID-19的未来建模提供了指导，也为其他传染病的动态建模提供了建议。
