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Multi-chain Fudan-CCDC model for COVID-19-a revisit to Singapore's case.
Pan, Hanshuang; Shao, Nian; Yan, Yue; Luo, Xinyue; Wang, Shufen; Ye, Ling; Cheng, Jin; Chen, Wenbin.
  • Pan H; School of Mathematical Sciences, Fudan University, Shanghai, 200433 China.
  • Shao N; School of Mathematical Sciences, Fudan University, Shanghai, 200433 China.
  • Yan Y; School of Mathematics, Shanghai University of Finance and Economics, Shanghai, 200433 China.
  • Luo X; School of Mathematics, Shanghai University of Finance and Economics, Shanghai, 200433 China.
  • Wang S; School of Mathematical Sciences, Fudan University, Shanghai, 200433 China.
  • Ye L; Daishan County Center for Disease Control and Prevention, Daishan, 316200 China.
  • Cheng J; School of Mathematical Sciences, Fudan University, Shanghai, 200433 China.
  • Chen W; Shanghai Key Laboratory for Contemporary Applied Mathematics, Fudan University, Shanghai, 200433 China.
Quant Biol ; 8(4): 325-335, 2020.
Article in English | MEDLINE | ID: covidwho-947080
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ABSTRACT

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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Quant Biol Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Quant Biol Year: 2020 Document Type: Article