Analysis of models of infectious disease dynamics of COVID-19

VernacularTitle:新型冠状病毒肺炎（COVID-19）传染病预测模型分析
Author: Yashu LIU ^{1
,

2} ; Qiun WU ^{1
,

2} ; Yihan LU ³ ; Yuhong ZHAO ^{1
,

2}
Author Information

1. Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 117004, China
2. Clinical Research Center, Shengjing Hospital of China Medical University Shenyang 117004, China
3. Fudan School of Public Health, Shanghai 200433, China
Publication Type:Journal Article
Keywords: COVID-19; New coronavirus; Prediction models; Prevention strategies
From: Journal of Public Health and Preventive Medicine 2020;31(3):10-13
CountryChina
Language:Chinese
Abstract: 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.