Multi-chain Fudan-CCDC model for COVID-19—a revisit to Singapore's case

• 作者: Hanshuang Pan Nian Shao Yue Yan Xinyue Luo Shufen Wang Ling Ye Jin Cheng Wenbin Chen
• 来源期刊: 定量生物学（英文版）
• 年，卷（期）: 2020,（4）
• 所属期刊栏目: RESEARCH ARTICLES
• 页码范围: 325-335
• 页数: 11页
• 语种: 英文

摘要

Background:COVID-19 has been impacting on the whole world critically and constantly since late December 2019.Rapidly increasing infections has raised intense worldwide attention.How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control.Methods:We propose the multi-chain Fudan-CCDC model based on the original single-chain model in[Shao et al.2020]to describe the evolution of COVID-19 in Singapore.Multi-chains can be considered as the superposition of several single chains with different characteristics.We identify the parameters of models by minimizing the penalty function.Results:The numerical simulation results exhibit the multi-chain model performs well on data fitting.Though unsteady the increments are,they could still fall within the range of ±30％fluctuation from simulation results.Conclusion:The multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak.It can also explain the data from those countries where the single-chain model shows deviation from the data.