A real-world data validation of the value of early-stage SIR modelling to public health

• Published in: Scientific reports Vol. 13; no. 1; pp. 9164 - 8
• Main Authors: Liu, Taoran, Huang, Jian, He, Zonglin, Zhang, Yin, Yan, Ni, Zhang, Casper J. P., Ming, Wai-Kit
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 06.06.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 692/699/255; 692/700/1538; 692/700/478; 692/700/478/174; COVID-19; COVID-19 - epidemiology; Disease transmission; Epidemic models; Epidemics; Humanities and Social Sciences; Humans; Infectious diseases; Markov Chains; Mathematical models; multidisciplinary; Public Health; SARS-CoV-2; Science; Science (multidisciplinary)

Performance of Susceptible-Infected-Recovered (SIR) model in the early stage of a novel epidemic may be hindered by data availability. Additionally, the traditional SIR model may oversimplify the disease progress, and knowledge about the virus and transmission is limited early in the epidemic, resul...