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Method Article
Jichao Sun
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The current outbreak of coronavirus disease 2019 (COVID-19) has recently been declared as a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. This protocol introduced a new model named Dynamic-Susceptible-Exposed-Infective-Quarantined (D-SEIQ), by making appropriate modifications of the Susceptible-Exposed-Infective-Recovered (SEIR) model and integrating machine learning based parameter optimization under epidemiological rational constraints. The model could be applied to forecast the long-term trend of the current COVID-19 epidemic. The parameters obtained by the model could help assess the effectiveness of prevention and intervention strategies on epidemic control in different countries.
Keywords
Coronavirus disease 2019, Forecasting model, machine learning, Dynamic-Susceptible-Exposed-Infective-Quarantined
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An open repository of community-contributed protocols sponsored by Nature Research.
Learn more about Protocol Exchange
Method Article
Jichao Sun
Corresponding Author
Version History
CURRENT STATUS: Posted
Version 1
Posted 02 Jun, 2020
No community comments so far
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The current outbreak of coronavirus disease 2019 (COVID-19) has recently been declared as a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. This protocol introduced a new model named Dynamic-Susceptible-Exposed-Infective-Quarantined (D-SEIQ), by making appropriate modifications of the Susceptible-Exposed-Infective-Recovered (SEIR) model and integrating machine learning based parameter optimization under epidemiological rational constraints. The model could be applied to forecast the long-term trend of the current COVID-19 epidemic. The parameters obtained by the model could help assess the effectiveness of prevention and intervention strategies on epidemic control in different countries.
Figure 1
No financial interest was involved
This is a list of supplementary files associated with this preprint. Click to download.
Loading...
Associated Publications
- Not available