| Autor: |
Sima Rafiei, Touraj Harati Khalilabad, Amir Jafari, Sajad Shafiekhani, Vahid Sadeghi, Nematollah Gheibi |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Polish Journal of Medical Physics and Engineering. 27:241-249 |
| ISSN: |
1898-0309 |
| DOI: |
10.2478/pjmpe-2021-0029 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
