tetano
Editor, Senior Moderator
Math Biosci Eng
. 2020 Nov 24;18(1):154-165.
doi: 10.3934/mbe.2021008.
Modeling and analysis of COVID-19 based on a time delay dynamic model
Cong Yang[SUP] 1 [/SUP], Yali Yang[SUP] 1 [/SUP], Zhiwei Li[SUP] 1 [/SUP], Lisheng Zhang[SUP] 1 [/SUP]
Affiliations
Abstract
The new type of coronavirus pneumonia is caused by the new type of coronavirus which appeared at the end of 2019. Because of its strong contagiousness, rapid spread and great harm, it has already given countries around the world serious effects. So far there is no clear specific drug. Scientifically grasping the development law of epidemics is extremely important for preventing and controlling epidemics. Since the latent of this epidemic are also highly contagious, traditional infectious disease models cannot accurately describe the regularity of this epidemic transmission. Based on the traditional infectious disease model, an infectious disease model with a time delay is proposed. The time difference is used to characterize the cycle of viral infection and treatment time. Using the epidemic data released in real time, firstly, through the numerical simulation parameter inversion, the minimum error is obtained; then we simulate the development trend of the epidemic according to the dynamics system; finally, we compare and analyze the effectiveness of isolation measures. This article has simulated COVID-19 and analyzed the development of the epidemic in Beijing and Wuhan. By comparing the severity of the epidemic in the two regions, early detection and isolation are still the top priority of epidemic prevention and control.
Keywords: COVID-19; parameter inversion; time delay dynamics system.
. 2020 Nov 24;18(1):154-165.
doi: 10.3934/mbe.2021008.
Modeling and analysis of COVID-19 based on a time delay dynamic model
Cong Yang[SUP] 1 [/SUP], Yali Yang[SUP] 1 [/SUP], Zhiwei Li[SUP] 1 [/SUP], Lisheng Zhang[SUP] 1 [/SUP]
Affiliations
- PMID: 33525085
- DOI: 10.3934/mbe.2021008
Abstract
The new type of coronavirus pneumonia is caused by the new type of coronavirus which appeared at the end of 2019. Because of its strong contagiousness, rapid spread and great harm, it has already given countries around the world serious effects. So far there is no clear specific drug. Scientifically grasping the development law of epidemics is extremely important for preventing and controlling epidemics. Since the latent of this epidemic are also highly contagious, traditional infectious disease models cannot accurately describe the regularity of this epidemic transmission. Based on the traditional infectious disease model, an infectious disease model with a time delay is proposed. The time difference is used to characterize the cycle of viral infection and treatment time. Using the epidemic data released in real time, firstly, through the numerical simulation parameter inversion, the minimum error is obtained; then we simulate the development trend of the epidemic according to the dynamics system; finally, we compare and analyze the effectiveness of isolation measures. This article has simulated COVID-19 and analyzed the development of the epidemic in Beijing and Wuhan. By comparing the severity of the epidemic in the two regions, early detection and isolation are still the top priority of epidemic prevention and control.
Keywords: COVID-19; parameter inversion; time delay dynamics system.