Literature DB >> 32271595

The Exponentially Increasing Rate of Patients Infected with COVID-19 in Iran.

Leila Moftakhar1, Mozhgan Seif2.   

Abstract

BACKGROUND: Coronavirus, the cause of severe acute respiratory syndrome (COVID-19), is rapidly spreading around the world. Since the number of corona positive patients is increasing sharply in Iran, this study aimed to forecast the number of newly infected patients in the coming days in Iran.
METHODS: The data used in this study were obtained from daily reports of the Iranian Ministry of Health and the datasets provided by the Johns Hopkins University including the number of new infected cases from February 19, 2020 to March 21, 2020. The autoregressive integrated moving average (ARIMA) model was applied to predict the number of patients during the next thirty days.
RESULTS: The ARIMA model forecasted an exponential increase in the number of newly detected patients. The result of this study also show that if the spreading pattern continues the same as before, the number of daily new cases would be 3574 by April 20.
CONCLUSION: Since this disease is highly contagious, health politicians need to make decisions to prevent its spread; otherwise, even the most advanced and capable health care systems would face problems for treating all infected patients and a substantial number of deaths will become inevitable.
© 2020 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Entities:  

Keywords:  COVID19; Forecast; Iran

Mesh:

Year:  2020        PMID: 32271595     DOI: 10.34172/aim.2020.03

Source DB:  PubMed          Journal:  Arch Iran Med        ISSN: 1029-2977            Impact factor:   1.354


  13 in total

1.  Estimating the Prevalence and Mortality of Coronavirus Disease 2019 (COVID-19) in the USA, the UK, Russia, and India.

Authors:  Yongbin Wang; Chunjie Xu; Sanqiao Yao; Yingzheng Zhao; Yuchun Li; Lei Wang; Xiangmei Zhao
Journal:  Infect Drug Resist       Date:  2020-09-29       Impact factor: 4.003

2.  Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA).

Authors:  K E ArunKumar; Dinesh V Kalaga; Ch Mohan Sai Kumar; Govinda Chilkoor; Masahiro Kawaji; Timothy M Brenza
Journal:  Appl Soft Comput       Date:  2021-02-08       Impact factor: 6.725

3.  Knowledge, Attitudes, and Practices Among the General Population During COVID-19 Outbreak in Iran: A National Cross-Sectional Online Survey.

Authors:  Edris Kakemam; Djavad Ghoddoosi-Nejad; Zahra Chegini; Khalil Momeni; Hamid Salehiniya; Soheil Hassanipour; Hosein Ameri; Morteza Arab-Zozani
Journal:  Front Public Health       Date:  2020-12-10

4.  Rapid Assessment of Price Instability and Paucity of Medicines and Protection for COVID-19 Across Asia: Findings and Public Health Implications for the Future.

Authors:  Brian Godman; Mainul Haque; Salequl Islam; Samiul Iqbal; Umme Laila Urmi; Zubair Mahmood Kamal; Shahriar Ahmed Shuvo; Aminur Rahman; Mustafa Kamal; Monami Haque; Iffat Jahan; Md Zakirul Islam; Mohammad Monir Hossain; Santosh Kumar; Jaykaran Charan; Rohan Bhatt; Siddhartha Dutta; Jha Pallavi Abhayanand; Yesh Sharma; Zikria Saleem; Thuy Nguyen Thi Phuong; Hye-Young Kwon; Amanj Kurdi; Janney Wale; Israel Sefah
Journal:  Front Public Health       Date:  2020-12-14

Review 5.  Using data mining techniques to fight and control epidemics: A scoping review.

Authors:  Reza Safdari; Sorayya Rezayi; Soheila Saeedi; Mozhgan Tanhapour; Marsa Gholamzadeh
Journal:  Health Technol (Berl)       Date:  2021-05-07

6.  Factors associated with survival of Iranian patients with COVID-19: comparison of Cox regression and mixture cure model.

Authors:  Mozhgan Seif; Mehdi Sharafi; Haleh Ghaem; Farzaneh Kasraei
Journal:  Trop Dis Travel Med Vaccines       Date:  2022-03-01

7.  Epidemiological Features and Predictors of Mortality in Patients with COVID-19 with and without Underlying Hypertension.

Authors:  Leila Moftakhar; Elahe Piraee; Mohammad Mohammadi Abnavi; Parisa Moftakhar; Habibollah Azarbakhsh; Aliasghar Valipour
Journal:  Int J Hypertens       Date:  2021-10-19       Impact factor: 2.420

8.  Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy.

Authors:  Gaetano Perone
Journal:  Eur J Health Econ       Date:  2021-08-04

9.  Epidemiological characteristics of patients with COVID-19 in Southwest of Iran from February 19 to June 20, 2020.

Authors:  Habibollah Azarbakhsh; Kimia Jokari; Leila Moftakhar; Mousa Ghelichi Ghojogh; Azimeh Karimyan; Shokrollah Salmanzadeh; Mehrdad Parian Zeitooni; Rozhan Khezri; Aliasghar Valipour
Journal:  Med J Islam Repub Iran       Date:  2021-09-13

10.  Systematic review of predictive mathematical models of COVID-19 epidemic.

Authors:  Subramanian Shankar; Sourya Sourabh Mohakuda; Ankit Kumar; P S Nazneen; Arun Kumar Yadav; Kaushik Chatterjee; Kaustuv Chatterjee
Journal:  Med J Armed Forces India       Date:  2021-07-26
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