التفاصيل البيبلوغرافية
| العنوان: |
Forecasting Wave-like Patterns of COVID-19 Daily Infected Cases in Iran |
| المؤلفون: |
Konarasinghe, K.M.U.B |
| المصدر: |
Journal of New Frontiers in Healthcare and Biological Sciences, 2(1), 39-56, (2021-07-05) |
| بيانات النشر: |
Zenodo |
| سنة النشر: |
2021 |
| المجموعة: |
Zenodo |
| مصطلحات موضوعية: |
COVID -19, Seasonal behavior, Daily Infected Cases, SCM |
| الوصف: |
The COVID -19 means Corona (CO), Virus (VI), Disease (D), and year 2019 (19), which is COVID-19. The pandemic first appeared in 2019, grabbed more than 177,885,850 infected cases and 3,850,529 death total reported up to date. Iran had been the second Middle East country severely hit by the COVID-19. At present daily infected cases shows a declining trend in Iran. It is a good sign and motivation to combat COVID -19. Hence, the study has designed to forecast the daily infected cases of COVID -19 in Iran. The daily infected cases of Iran for the period of 22nd January 2020 to 17th June 2021 were obtained from the World Health Organization (WHO) database. The pattern recognition of the daily cases examined by time series plots and Auto Correlation Function (ACF). The Sama Circular Model (SCM) and the Seasonal Auto-Regressive Integrated Moving Average (SARIMA) were tested to forecast the daily infected cases. The models were validated by using the Anderson Darling test, ACF, and Ljung-Box Q (LBQ)-test. Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD) are the measurements of errors used in both model fitting and verification processes to assess the forecasting ability of the models. The results of the study revealed that both SCM and SARIMA were satisfied all validation criterion, but the performance of SCM was extremely higher than SARIMA. It had been concluded that the SCM is the most suitable model to forecast daily infected cases in Iran. It is strongly recommended to test whether the wave like patterns exist in infected cases of the other countries as well. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| Relation: |
https://doi.org/10.5281/zenodo.5071362; https://doi.org/10.5281/zenodo.5071363; oai:zenodo.org:5071363 |
| DOI: |
10.5281/zenodo.5071363 |
| الاتاحة: |
https://doi.org/10.5281/zenodo.5071363 |
| Rights: |
info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: |
edsbas.E505DCA2 |
| قاعدة البيانات: |
BASE |