| Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|
|
|---|---|---|
| Article Number | 06010 | |
| Number of page(s) | 7 | |
| Section | Artificial Recognition and Application | |
| DOI | https://doi.org/10.1051/matecconf/202133606010 | |
| Published online | 15 February 2021 | |
Application of computer simulation in the study of infectious disease transmission mechanism
1 School of Economics, Beijing Wuzi University, Beijing, 101149, China
2 School of Information, Renmin University of China, Beijing, 100872, China
* Corresponding author: zhaochengzhenabc@163.com
Major infectious diseases have exerted a serious influence on people's lives. Through quantifying the effect of prevention and control, we can deeply understand the transmission mechanism of infectious diseases. This paper estimates the intensity of detection, the degree of isolation and other indicators, and analyzes the influence mechanism of these indicators on the scale of the epidemic, using computer programming to simulate the extended dynamics model of infectious diseases, based on the infectious disease in Hubei. The mortality rate and recovery rate, according to the data of Hubei, in the model are set as time variables, and the threshold is set at the same time. As a result, the improved analysis mechanism of the model will get more realistic simulation prediction results. It is concluded that isolation measures can effectively control the scale of the epidemic, but there is a phenomenon of marginal utility degression with excessively strict isolation measures by analysing and comparing. The increasing detection efforts will reduce the epidemic duration of the later stage, accelerating the arrival of the epidemic peak, although the peak will be slightly larger. All in all, we can comprehensively consider the testing cost and maintain a moderate detection intensity.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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