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Prediction of COVID-19 cases with epidemiological and time series models
International Journal of Medical Engineering and Informatics, (2024)
DOI: 10.1504/IJMEI.2023.10060974
Аннотация
This work analyses the official data of coronavirus and predicts the evolution of the epidemic in Nepal. The generalised SEIR model has been applied with hybrid of ETS-ARIMA time series model for the time series analysis and predictions of evolution of COVID-19 cases. The prediction has been made for 30 days using the past data of thirteen months. The prediction made by generalised SEIR model has been corrected using two time series models, ETS and ARIMA model. The predicted error by ARIMA model is added to the prediction made by generalised SEIR model. Use of generalised SEIR model along with ETS and ARIMA model improves the time series prediction of coronavirus spread in case of Nepal as compared to the generalised SEIR model. Also, the SEIR-ETS-ARIMA model reduces the estimation error as compared to SEIRD-ARIMA model. Improvement in all quality measures, MAE, MSE, RMSE and MAPE has been observed.
