Estimating COVID-19-Related Infections, Deaths, and Hospitalizations in Iran Under Different Physical Distancing and Isolation Scenarios

Document Type : Original Article


1 HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

2 Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran

3 Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

4 Department of Epidemiology and Biostatistics, Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA

5 Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

6 Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran

7 Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

8 Prevention of Cardiovascular Disease Research Center, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

9 School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada


Iran is one of the first few countries that was hit hard with the coronavirus disease 2019 (COVID-19) pandemic. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios.

We developed a susceptible-exposed-infected/infectious-recovered/removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UIs).
Under scenario A, we estimated 5 196 000 (UI 1 753 000-10 220 000) infections to happen till mid-June with 966 000 (UI 467 800-1 702 000) hospitalizations and 111 000 (UI 53 400-200 000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (ie, 550 000) and change the epidemic peak from 66 000 on June 9, to 9400 on March 1, 2020. Scenario E also reduces the hospitalizations by 92% (ie, 74 500), and deaths by 93% (ie, 7800).

With no approved vaccination or therapy available, we found physical distancing and isolation that include public awareness and case-finding and isolation of 40% of infected people could reduce the burden of COVID-19 in Iran by 90% by mid-June.



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Main Subjects

  1. COVID-19 Coronavirus Pandemic. Worldometers website.
  2. Daily Situation Report on Coronavirus disease (COVID-19) in Iran; June 5, 2020.
  3. World Health Organization (WHO). Eastern Mediterranean Region COVID-19 Affected Countries.   Accessed April 13, 2020.
  4. Trottier H, Philippe P. Deterministic modeling of infectious diseases: applications to measles and other similar infections. Internet J Infect Dis. 2001;2(1):1-10.
  5. Lekone PE, Finkenstädt BF. Statistical inference in a stochastic epidemic SEIR model with control intervention: Ebola as a case study. Biometrics. 2006;62(4):1170-1177. doi:10.1111/j.1541-0420.2006.00609.x
  6. Wearing HJ, Rohani P, Keeling MJ. Appropriate models for the management of infectious diseases. PLoS Med. 2005;2(7):e174. doi:10.1371/journal.pmed.0020174
  7. Community-Based Measures to Mitigate the Spread of Coronavirus Disease (COVID-19) in Canada.  Accessed April 10, 2020.
  8. Centers for Disease Control and Prevention (CDC). Social Distancing, Quarantine, and Isolation.  Accessed April 8, 2020.
  9. Daily Situation Report on Coronavirus disease (COVID-19) in Iran; April 11, 2020.  Accessed April 11, 2020.
  10. Haghdoost AA, Gooya MM, Baneshi MR. Modelling of H1N1 flu in Iran. Arch Iran Med. 2009;12(6):533-541.
  11. Arregui S, Aleta A, Sanz J, Moreno Y. Projecting social contact matrices to different demographic structures. PLoS Comput Biol. 2018;14(12):e1006638. doi:10.1371/journal.pcbi.1006638
  12. Mossong J, Hens N, Jit M, et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med. 2008;5(3):e74. doi:10.1371/journal.pmed.0050074
  13. Ibuka Y, Ohkusa Y, Sugawara T, et al. Social contacts, vaccination decisions and influenza in Japan. J Epidemiol Community Health. 2016;70(2):162-167. doi:10.1136/jech-2015-205777
  14. Hoang T, Coletti P, Melegaro A, et al. A systematic review of social contact surveys to inform transmission models of close-contact infections. Epidemiology. 2019;30(5):723-736. doi:10.1097/ede.0000000000001047
  15. Prem K, Cook AR, Jit M. Projecting social contact matrices in 152 countries using contact surveys and demographic data. PLoS Comput Biol. 2017;13(9):e1005697. doi:10.1371/journal.pcbi.1005697
  16. Keeling MJ, Rohani P. Modeling Infectious Diseases in Humans and Animals. Princeton: Princeton University Press; 2011.
  17. Vynnycky E, White RG. An Introduction to Infectious Disease Modelling. Oxford: Oxford University Press; 2010.
  18. van den Driessche P, Watmough J. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math Biosci. 2002;180:29-48. doi:10.1016/s0025-5564(02)00108-6
  19. COVID-19 Coronavirus / Death Rate. Worldometer website. Published May 14, 2020.
  20. Carcione JM, Santos JE, Bagaini C, Ba J. A simulation of a COVID-19 epidemic based on a deterministic SEIR model. Front Public Health. 2020;8:230. doi:10.3389/fpubh.2020.00230
  21. Ghaffarzadegan N, Rahmandad H. Simulation-based estimation of the spread of COVID-19 in Iran. medRxiv. 2020. doi:10.1101/2020.03.22.20040956
  22. Daily Situation Report on Coronavirus disease (COVID-19) in Iran; April 18, 2020.  Accessed April 18, 2020.
  23. Coronavirus: Iranians Urged to Stay Home During Holiday. BBC. March 19, 2020.  Accessed April 8, 2020
  24. Iranian Press Review: Iranians Ignore Coronavirus Travel Warning Ahead of Nowruz Holiday. Middle East Eye website.  Accessed April 10, 2020
  25. Prem K, Liu Y, Russell TW, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health. 2020;5(5):e261-e270. doi:10.1016/s2468-2667(20)30073-6
  26. Iran Reports its First 2 Cases of the New Coronavirus. The Times of Israel. February 19, 2020. Accessed April 10, 2020.
  27. Healthcare Worker in Iran Discusses Effects of U.S. Sanctions. NPR website.  Accessed April 11, 2020.
  28. Danaei G, Harirchi I, Sajadi HS, Yahyaei F, Majdzadeh R. The harsh effects of sanctions on Iranian health. Lancet. 2019;394(10197):468-469. doi:10.1016/s0140-6736(19)31763-5
  29. Ferguson NM, Laydon D, Nedjati-Gilani G, et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College London; 2020. doi:10.25561/77482
  30. Jia J, Ding J, Liu S, et al. Modeling the control of COVID-19: impact of policy interventions and meteorological factors. arXiv200302985. 2020.