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Coronavirus(COVID-19)Outbreak Prediction Using Epidemiological Models of Richards Gompertz Logistic Ratkowsky and SIRD
Ahmad Sedaghat; Seyed Amir Abbas Oloomi; Mahdi Ashtian Malayer; Nima Rezaei; Amir MOSAVI.
Affiliation
  • Ahmad Sedaghat; School of Engineering, Australian College of Kuwait Safat 13015, Kuwait
  • Seyed Amir Abbas Oloomi; Department of Mechanical Engineering, Yazd Branch Azad University, Yazd, Iran
  • Mahdi Ashtian Malayer; Young Researchers and Elite Club, Yazd Branch, Azad University, Yazd, Iran
  • Nima Rezaei; School of Medicine, Tehran University of Medical Sciences Tehran, Iran
  • Amir MOSAVI; Obuda University
Preprint in En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20240580
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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ABSTRACT
On 30 July 2020, a total number of 301,530 diagnosed COVID-19 cases were reported in Iran, with 261,200 recovered and 16,569 dead. The COVID-19 pandemic started with 2 patients in Qom city in Iran on 20 February 2020. Accurate prediction of the end of the COVID-19 pandemic and the total number of populations affected is challenging. In this study, several widely used models, including Richards, Gompertz, Logistic, Ratkowsky, and SIRD models, are used to project dynamics of the COVID-19 pandemic in the future of Iran by fitting the present and the past clinical data. Iran is the only country facing a second wave of COVID-19 infections, which makes its data difficult to analyze. The present studys main contribution is to forecast the near-future of COVID-19 trends to allow non-pharmacological interventions (NPI) by public health authorities and/or government policymakers. We have divided the COVID-19 pandemic in Iran into two waves, Wave I, from February 20, 2020 to May 4, 2020, and Wave II from May 5, 2020, to the present. Two statistical methods, i.e., Pearson correlation coefficient (R) and the coefficient of determination (R2), are used to assess the accuracy of studied models. Results for Wave I Logistic, Ratkowsky, and SIRD models have correctly fitted COVID-19 data in Iran. SIRD model has fitted the first peak of infection very closely on April 6, 2020, with 34,447 cases (The actual peak day was April 7, 2020, with 30,387 active infected patients) with the re-production number R0=3.95. Results of Wave II indicate that the SIRD model has precisely fitted with the second peak of infection, which was on June 20, 2020, with 19,088 active infected cases compared with the actual peak day on June 21, 2020, with 17,644 cases. In Wave II, the re-production number R0=1.45 is reduced, indicating a lower transmission rate. We aimed to provide even a rough project future trends of COVID-19 in Iran for NPI decisions. Between 180,000 to 250,000 infected cases and a death toll of between 6,000 to 65,000 cases are expected in Wave II of COVID-19 in Iran. There is currently no analytical method to project more waves of COVID-19 beyond Wave II.
License
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Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint