Background:The continuous mutation of severe acute respiratory syndrome coronavirus 2 has made the coronavirus disease 2019(COVID-19)pandemic complicated to predict and posed a severe challenge to the Beijing 2022Wint...Background:The continuous mutation of severe acute respiratory syndrome coronavirus 2 has made the coronavirus disease 2019(COVID-19)pandemic complicated to predict and posed a severe challenge to the Beijing 2022Winter Olympics and Winter Paralympics held in February and March 2022.Methods:During the preparations for the Beijing 2022 Winter Olympics,we established a dynamic model with pulsedetection and isolation efect to evaluate the efect of epidemic prevention and control measures such as entry policies,contact reduction,nucleic acid testing,tracking,isolation,and health monitoring in a closed-loop managementenvironment,by simulating the transmission dynamics in assumed scenarios.We also compared the importance ofeach parameter in the combination of intervention measures through sensitivity analysis.Results:At the assumed baseline levels,the peak of the epidemic reached on the 57th day.During the simulationperiod(100 days),13,382 people infected COVID-19.The mean and peak values of hospitalized cases were 2650and 6746,respectively.The simulation and sensitivity analysis showed that:(1)the most important measures to stopCOVID-19 transmission during the event were daily nucleic acid testing,reducing contact among people,and dailyhealth monitoring,with cumulative infections at 0.04%,0.14%,and 14.92%of baseline levels,respectively(2)strictlyimplementing the entry policy and reducing the number of cases entering the closed-loop system could delay thepeak of the epidemic by 9 days and provide time for medical resources to be mobilized;(3)the risk of environmentaltransmission was low.Conclusions:Comprehensive measures under certain scenarios such as reducing contact,nucleic acid testing,health monitoring,and timely tracking and isolation could efectively prevent virus transmission.Our research resultsprovided an important reference for formulating prevention and control measures during the Winter Olympics,andno epidemic spread in the closed-loop during the games indirectly proved the rationality of our research results.展开更多
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 effective...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.Main text: 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.Conclusion: 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.展开更多
文摘Background:The continuous mutation of severe acute respiratory syndrome coronavirus 2 has made the coronavirus disease 2019(COVID-19)pandemic complicated to predict and posed a severe challenge to the Beijing 2022Winter Olympics and Winter Paralympics held in February and March 2022.Methods:During the preparations for the Beijing 2022 Winter Olympics,we established a dynamic model with pulsedetection and isolation efect to evaluate the efect of epidemic prevention and control measures such as entry policies,contact reduction,nucleic acid testing,tracking,isolation,and health monitoring in a closed-loop managementenvironment,by simulating the transmission dynamics in assumed scenarios.We also compared the importance ofeach parameter in the combination of intervention measures through sensitivity analysis.Results:At the assumed baseline levels,the peak of the epidemic reached on the 57th day.During the simulationperiod(100 days),13,382 people infected COVID-19.The mean and peak values of hospitalized cases were 2650and 6746,respectively.The simulation and sensitivity analysis showed that:(1)the most important measures to stopCOVID-19 transmission during the event were daily nucleic acid testing,reducing contact among people,and dailyhealth monitoring,with cumulative infections at 0.04%,0.14%,and 14.92%of baseline levels,respectively(2)strictlyimplementing the entry policy and reducing the number of cases entering the closed-loop system could delay thepeak of the epidemic by 9 days and provide time for medical resources to be mobilized;(3)the risk of environmentaltransmission was low.Conclusions:Comprehensive measures under certain scenarios such as reducing contact,nucleic acid testing,health monitoring,and timely tracking and isolation could efectively prevent virus transmission.Our research resultsprovided an important reference for formulating prevention and control measures during the Winter Olympics,andno epidemic spread in the closed-loop during the games indirectly proved the rationality of our research results.
基金This research was supported by the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China(2021YFF0306000)the National Natural Science Foundation of China(81973102)+5 种基金Public Health Talents Training Program of Shanghai Municipality(GWV-10.2-XD21)the Shanghai New Three-year Action Plan for Public Health(GWV-10.1-XK16)13th Five-Year National Science and Technology Major Project for Infectious Diseases(2018ZX10725-509)Key projects of the PLA logistics Scientific research Program(BHJ17J013)the Natural Science Funds of Hebei(Grant No.D2019502010)the Fundamental Research Funds for the Central Universities(No.2021MS074).
文摘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.Main text: 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.Conclusion: 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.
