<abstract xmlns="http://www.w3.org/1999/xhtml">

<italic>Background:</italic> Mathematical and predictive modeling approaches can be used in COVID-19 crisis to forecast the trend of new cases for healthcare management purposes. Given the COVID-19 disease pandemic, the prediction of the epidemic trend of this disease is so important.
<italic>Methods:</italic> We constructed an SEIR (Susceptible-Exposed-Infected-Recovered) model on the COVID-19 outbreak in Iran. We estimated model parameters by the data on notified cases in Iran in the time window 1/22/2020 – 20/7/2021. Global sensitivity analysis is performed to determine the correlation between epidemiological variables and SEIR model parameters and to assess SEIR model robustness against perturbation to parameters. We Combined Adaptive Neuro-Fuzzy Inference System (ANFIS) as a rigorous time series prediction approach with the SEIR model to predict the trend of COVID-19 new cases under two different scenarios including social distance and non-social distance.
<italic>Results:</italic> The SEIR and ANFIS model predicted new cases of COVID-19 for the period February 7, 2021, till August 7, 2021. Model predictions in the non-social distancing scenario indicate that the corona epidemic in Iran may recur as an immortal oscillation and Iran may undergo a recurrence of the third peak.
<italic>Conclusion:</italic> Combining parametrized SEIR model and ANFIS is effective in predicting the trend of COVID-19 new cases in Iran.
</abstract>

Background: Mathematical and predictive modeling approaches can be used in COVID-19 crisis to forecast the trend of new cases for healthcare management purposes. Given the COVID-19 disease pandemic, the prediction of the epidemic trend of this disease is so important.
Methods: We constructed an SEIR (Susceptible-Exposed-Infected-Recovered) model on the COVID-19 outbreak in Iran. We estimated model parameters by the data on notified cases in Iran in the time window 1/22/2020 – 20/7/2021. Global sensitivity analysis is performed to determine the correlation between epidemiological variables and SEIR model parameters and to assess SEIR model robustness against perturbation to parameters. We Combined Adaptive Neuro-Fuzzy Inference System (ANFIS) as a rigorous time series prediction approach with the SEIR model to predict the trend of COVID-19 new cases under two different scenarios including social distance and non-social distance.
Results: The SEIR and ANFIS model predicted new cases of COVID-19 for the period February 7, 2021, till August 7, 2021. Model predictions in the non-social distancing scenario indicate that the corona epidemic in Iran may recur as an immortal oscillation and Iran may undergo a recurrence of the third peak.
Conclusion: Combining parametrized SEIR model and ANFIS is effective in predicting the trend of COVID-19 new cases in Iran.

Trend and prediction of COVID-19 outbreak in Iran: SEIR and ANFIS model

Departments of Biomedical Engineering, School of Medicine

Department of Health Economics, School of Health Management and Information Sciences

Department of Healthcare Management, School of Health

Polish Journal of Medical Physics and Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Trend and prediction of COVID-19 outbreak in Iran: SEIR and ANFIS model"}

Background: Mathematical and predictive modeling approaches can be used in COVID-19 crisis to forecast the trend of new cases for healthcare management...

Trend and prediction of COVID-19 outbreak in Iran: SEIR and ANFIS model

Publié en ligne: 27 sept. 2021

Pages: 241 - 249

DOI: https://doi.org/10.2478/pjmpe-2021-0029

Mots clés
coronavirus disease 2019 (COVID-19), Susceptible-Exposed-Infectious-Recovered (SEIR), Adaptive Neuro-Fuzzy Inference System (ANFIS), global sensitivity analysis

© 2021 Sajad Shafiekhani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Trend and prediction of COVID-19 outbreak in Iran: SEIR and ANFIS model

Publié en ligne: 27 sept. 2021

Pages: 241 - 249

DOI: https://doi.org/10.2478/pjmpe-2021-0029

Mots cléscoronavirus disease 2019 (COVID-19), Susceptible-Exposed-Infectious-Recovered (SEIR), Adaptive Neuro-Fuzzy Inference System (ANFIS), global sensitivity analysis

© 2021 Sajad Shafiekhani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
coronavirus disease 2019 (COVID-19), Susceptible-Exposed-Infectious-Recovered (SEIR), Adaptive Neuro-Fuzzy Inference System (ANFIS), global sensitivity analysis