Modeling and forecasting the spread tendency of the COVID-19 in China

Sun，Deshun1; Duan，Li1; Xiong，Jianyi1; Wang，Daping1,2

2020-12-01

10.1186/s13662-020-02940-2

Advances in Difference Equations   影响因子和分区

1687-1839

1687-1847

To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed, the death and the cured are 99.8%, 99.8% and 99.6%, respectively. The average forecasting error rates of the infected, the removed, the death and the cured are 0.78%, 0.75%, 0.35% and 0.83%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.

Control strategy COVID-19 Forecasting Mathematical modeling Parameter estimation

SCI

英语

其他

China Postdoctoral Science Foundation[2020M672829][2020T130081ZX] ; Shenzhen Science and Technology Innovation Commission[KQTD20170331100838136][JCYJ20170817172023838][JCYJ20170306092215436][JCYJ20170412150609690][JCYJ20170413161649437][JCYJ20170413161800287]

Mathematics

Mathematics, Applied ; Mathematics

WOS:000571912300001

SPRINGER

2-s2.0-85090908987

Scopus

1.Shenzhen Key Laboratory of Tissue Engineering,Shenzhen Laboratory of Digital Orthopedic Engineering,Guangdong Provincial Research Center for Artificial Intelligence and Digital Orthopedic Technology,Shenzhen Second People’s Hospital (The First Hospital Affiliated to Shenzhen University,Health Science Center),Shenzhen,518035,China
2.Department of Biomedical Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Sun，Deshun,Duan，Li,Xiong，Jianyi,et al. Modeling and forecasting the spread tendency of the COVID-19 in China[J]. Advances in Difference Equations,2020,2020(1).

Sun，Deshun,Duan，Li,Xiong，Jianyi,&Wang，Daping.(2020).Modeling and forecasting the spread tendency of the COVID-19 in China.Advances in Difference Equations,2020(1).

Sun，Deshun,et al."Modeling and forecasting the spread tendency of the COVID-19 in China".Advances in Difference Equations 2020.1(2020).