A Modified SAIR Model for the Spread of COVID-19 in China

Yijun Guo

2021

Abstract

The study aims to modify the SIR model with consideration of asymptomatic patients for the spread of COVID-19 in China. The data is obtained from the National Health Commission of the PRC. Data fitting based on Chinese epidemic data is conducted to find the value of parameters. Besides, sensitivity analysis is applied on parameters, and the new modified model is compared with model having a similar structure in the previous study. For further investigation, the basic reproduction number, R0, turning point and ratio between asymptomatic and total infected ones are calculated. The fitting and sensitivity analysis reveals that loss of immunity, ratio between infection rate of asymptomatic ones and infected ones will not significantly influence the SAIR model. The analysis results also show that structure of previous model with related infection rates does not work well on chosen data. On the contrary, transformation rate from asymptomatic ones to infected patients plays a critical role in the epidemic. mentioned above. Further evaluation shows that it can be used as a reference for the arrangement of testing. The model can be used to predict the general evolution of the disease spread. The increase of the transformation rate can alleviate the spread of disease. Transformation rate can be interpreted as the frequency of testing, which further confirms the necessity of these methods and provides some application values. The model is plausible but more analysis is still needed to evaluate the different conditions to apply.

Paper Citation

in Harvard Style

Guo Y. (2021). A Modified SAIR Model for the Spread of COVID-19 in China. In Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA, ISBN 978-989-758-589-0, pages 197-207. DOI: 10.5220/0011159100003437

in Bibtex Style

@conference{pmbda21,
author={Yijun Guo},
title={A Modified SAIR Model for the Spread of COVID-19 in China},
booktitle={Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,},
year={2021},
pages={197-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011159100003437},
isbn={978-989-758-589-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,
TI - A Modified SAIR Model for the Spread of COVID-19 in China
SN - 978-989-758-589-0
AU - Guo Y.
PY - 2021
SP - 197
EP - 207
DO - 10.5220/0011159100003437