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Arch Iran Med. 2020;23(4): 244-248. doi: 10.34172/aim.2020.05
PMID: 32271597

Original Article

A Model for COVID-19 Prediction in Iran Based on China Parameters

Bushra Zareie 1,2 ORCID, Amin Roshani 3 ORCID, Mohammad Ali Mansournia 4 ORCID, Mohammad Aziz Rasouli 2,5 ORCID, Ghobad Moradi 2 * ORCID

Cited by CrossRef: 30

1- Kumari P, Singh H, Singh S. SEIAQRDT model for the spread of novel coronavirus (COVID-19): A case study in India. Appl Intell. 2021;51(5):2818 [Crossref]
2- Hadianfar A, Yousefi R, Delavary M, Fakoor V, Shakeri M, Lavallière M, Cheong S. Effects of government policies and the Nowruz holidays on confirmed COVID-19 cases in Iran: An intervention time series analysis. PLoS ONE. 2021;16(8):e0256516 [Crossref]
3- Haji-Maghsoudi S, Sadeghifar M, Roshanaei G, Mahjub H. The Impact of Control Measures and Holiday Seasons on Incidence and Mortality Rate of COVID-19 in Iran. J Res Health Sci. 2020;20(4):e00500 [Crossref]
4- Kargar S, Pourmehdi M, Paydar M. Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19). Science of The Total Environment. 2020;746:141183 [Crossref]
5- Gerli A, Centanni S, Miozzo M, Virchow J, Sotgiu G, Canonica G, Soriano J. COVID-19 mortality rates in the European Union, Switzerland, and the UK: effect of timeliness, lockdown rigidity, and population density. Minerva Med. 2020;111(4) [Crossref]
6- Alharbi N. Forecasting the COVID-19 Pandemic in Saudi Arabia Using a Modified Singular Spectrum Analysis Approach: Model Development and Data Analysis. JMIRx Med. 2021;2(1):e21044 [Crossref]
7- Chen Y, He H, Liu D, Zhang X, Wang J, Yang Y. Prediction of asymptomatic COVID‐19 infections based on complex network. Optim Control Appl Methods. 2023;44(3):1602 [Crossref]
8- Kim Y, Park C, Ahn J, Jang B, Ashraf I. COVID-19 outbreak prediction using Seq2Seq + Attention and Word2Vec keyword time series data. PLoS ONE. 2023;18(4):e0284298 [Crossref]
9- Liu Y, Xiao Y. COVID-19 Propagation Prediction Model Based on Machine Learning. J Phys: Conf Ser. 2021;1955(1):012094 [Crossref]
10- Safari A, Hosseini R, Mazinani M. A novel deep interval type-2 fuzzy LSTM (DIT2FLSTM) model applied to COVID-19 pandemic time-series prediction. Journal of Biomedical Informatics. 2021;123:103920 [Crossref]
11- Chen J, Li K, Zhang Z, Li K, Yu P. A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19. ACM Comput Surv. 2022;54(8):1 [Crossref]
12- Yaspal B, Jauhar S, Kamble S, Belhadi A, Tiwari S. A data-driven digital transformation approach for reverse logistics optimization in a medical waste management system. Journal of Cleaner Production. 2023;430:139703 [Crossref]
13- Liao Z, Lan P, Liao Z, Zhang Y, Liu S. TW-SIR: time-window based SIR for COVID-19 forecasts. Sci Rep. 2020;10(1) [Crossref]
14- Nassiri H, Mohammadpour S, Dahaghin M, Yuan Q. How do the smart travel ban policy and intercity travel pattern affect COVID-19 trends? Lessons learned from Iran. PLoS ONE. 2022;17(10):e0276276 [Crossref]
15- Feroze N. Assessing the future progression of COVID-19 in Iran and its neighbors using Bayesian models. Infectious Disease Modelling. 2021;6:343 [Crossref]
16- Kalantari M. Forecasting COVID-19 pandemic using optimal singular spectrum analysis. Chaos, Solitons & Fractals. 2021;142:110547 [Crossref]
17- Neslihanoglu S. Nonlinear models: a case of the COVID-19 confirmed rates in top 8 worst affected countries. Nonlinear Dyn. 2021;106(2):1267 [Crossref]
18- Kolivand P, Saberian P, Arabloo J, Behzadifar M, Karimi F, Rajaie S, Moradipour M, Parvari A, Azari S, Abonazel M. Impact of COVID-19 pandemic on road traffic injuries in Iran: An interrupted time-series analysis. PLoS ONE. 2024;19(6):e0305081 [Crossref]
19- et al. J. Regression modeling and correlation analysis spread of COVID-19 data for Pakistan. Int j adv appl sci. 2022;9(3):71 [Crossref]
20- Stăncioi C, Ștefan I, Briciu V, Mureșan V, Clitan I, Abrudean M, Ungureșan M, Miron R, Stativă E, Nanu M, Topan A, Toader D, Nanu I. Solution for the Mathematical Modeling and Future Prediction of the COVID-19 Pandemic Dynamics. Applied Sciences. 2023;13(13):7971 [Crossref]
21- Shankar S, Mohakuda S, Kumar A, Nazneen P, Yadav A, Chatterjee K, Chatterjee K. Systematic review of predictive mathematical models of COVID-19 epidemic. Medical Journal Armed Forces India. 2021;77:S385 [Crossref]
22- Frank T. COVID-19 outbreaks follow narrow paths: A computational phase portrait approach based on nonlinear physics and synergetics. Int J Mod Phys C. 2021;32(08):2150110 [Crossref]
23- Zhihao L, Junpei W, Xiaoliang Z, Huijun N. RESEARCH ON COVID-19 EPIDEMIC BASED ON ARIMA MODEL. J Phys: Conf Ser. 2021;2012(1):012063 [Crossref]
24- Pourmalek F, Rezaei Hemami M, Janani L, Moradi-Lakeh M. Rapid review of COVID-19 epidemic estimation studies for Iran. BMC Public Health. 2021;21(1) [Crossref]
25- Y, Adlakha N. Non-linear dynamics and control of COVID-19 in india revisited : evidence of synergistic, antagonistic and threshold effects. Phys Scr. 2024;99(11):115248 [Crossref]
26- Zand A, Heir A. Environmental impacts of new Coronavirus outbreak in Iran with an emphasis on waste management sector. J Mater Cycles Waste Manag. 2021;23(1):240 [Crossref]

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A Monthly Peer-Reviewed Medical Journal Published by the Academy of Medical Sciences of the I.R. Iran; Indexed in PubMed/MEDLINE, ISI Web of Science, EMBASE, SCOPUS, CINHAL, PASCAL, CSA, SID, ISSN: Print 1029-2977, Online 1735-3947.The impact factor of Archives of Iranian Medicine according to Journal Citation Reports® (JCR®) 2016 is 1.20.