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.
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Posted 02 Jun, 2020
Posted 02 Jun, 2020
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
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