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SEIARN: Intelligent Early Warning Model of Epidemic Spread Based on LSTM Trajectory Prediction
Mathematics ; 10(17):3046, 2022.
Article in English | MDPI | ID: covidwho-1997702
ABSTRACT
A SEIARN compartment model with the asymptomatic infection and secondary infection is proposed to predict the trend of COVID-19 more accurately. The model is extended according to the propagation characteristics of the novel coronavirus, the concepts of the asymptomatic infected compartment and secondary infection are introduced, and the contact rate parameters of the improved model are updated in real time by using the LSTM trajectory, in order to make accurate predictions. This SEIARN model first builds on the traditional SEIR compartment model, taking into account the asymptomatic infection compartment and secondary infection. Secondly, it considers the disorder of the trajectory and uses the improved LSTM model to predict the future trajectory of the current patients and cross-track with the susceptible patients to obtain the contact rate. Then, we conduct real-time updating of exposure rates in the SEIARN model and simulation of epidemic trends in Tianjin, Xi'an, and Shijiazhuang. Finally, the comparison experiments show that the SEIARN model performs better in prediction accuracy, MSE, and RMSE.

Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Mathematics Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Mathematics Year: 2022 Document Type: Article