Analysis of models of infectious disease dynamics of COVID-19 / 公共卫生与预防医学

Objectives To analyze the studies about predicting COVID-19 by math models, to provide evidences and experiences to reduce the hazard of COVID-19. Methods PubMed, CNKI and other databases were searched for studies involving math models of COVID-19, and the studies were compared with each other and the real data. Results A total of 21 publications were included. SIR, SEIR and other models were used to predict the prevalence and evaluate the interventions. The results were predicted by SEIR+CAQ model were the closest to the actual situation. And the control measures have effectively restrained COVID-19. Conclusion Characteristics of COVID-19 and prevention measures should be concerned, when predicting the epidemic trend of COVID-19.