A Report on Statistics of an Online Self-screening Platform for COVID-19 and Its Effectiveness in Iran

Document Type : Original Article


1 Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

2 Center for Communicable Diseases Control, Ministry of Health & Medical Education, Tehran, Iran

3 School of Medicine, Department of Pharmacology, Shahid Beheshti University of Medical Sciences, Tehran, Iran

4 Digestive Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran

5 Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran


The most recent emerging infectious disease, coronavirus disease 2019 (COVID-19), is pandemic now. Iran is a country with community transmission of the disease. Telehealth tools have been proved to be useful in controlling public health disasters. We developed an online self-screening platform to offer a population-wide strategy to control the massive influx to medical centers.
We developed a platform operating based on given history by participants, including sex, age, weight, height, location, primary symptoms and signs, and high risk past medical histories. Based on a decision-making algorithm, participants were categorized into four levels of suspected cases, requiring diagnostic tests, supportive care, not suspected cases. We made comparisons with Iran STEPs (STEPwise approach to Surveillance) 2016 study and data from the Statistical Centre of Iran to assess population representativeness of data. Also, we made a comparison with officially confirmed cases to investigate the effectiveness of the platform. A multilevel mixed-effects Poisson regression was used to check the association of visiting platform and deaths caused by COVID-19.
About 310 000 individuals participated in the online self-screening platform in 33 days. The majority of participants were in younger age groups, and males involved more. A significant number of participants were screened not to be suspected or needing supportive care, and only 10.4% of males and 12.0% of females had suspected results of COVID-19. The penetration of the platform was assessed to be acceptable. A correlation coefficient of 0.51 was calculated between suspected results and confirmed cases of the disease, expressing the platform’s effectiveness.
Implementation of a proper online self-screening tool can mitigate population panic during wide-spread epidemics and relieve massive influx to medical centers. Also, an evidence-based education platform can help fighting infodemic. Noticeable utilization and verified effectiveness of such platform validate the potency of telehealth tools in controlling epidemics and pandemics.


Main Subjects

  1. Milinovich GJ, Williams GM, Clements AC, Hu W. Internet-based surveillance systems for monitoring emerging infectious diseases. Lancet Infect Dis. 2014;14(2):160-168. doi:10.1016/s1473-3099(13)70244-5
  2. Del Rio C, Malani PN. COVID-19-new insights on a rapidly changing epidemic. JAMA. 2020;323(14):1339-1340. doi:10.1001/jama.2020.3072
  3. Smith AC, Thomas E, Snoswell CL, et al. Telehealth for global emergencies: implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare. 2020;26(5):309-313.   doi:10.1177/1357633x20916567
  4. Tuite AR, Bogoch, II, Sherbo R, Watts A, Fisman D, Khan K. Estimation of coronavirus disease 2019 (COVID-19) burden and potential for international dissemination of infection from Iran. Ann Intern Med. 2020;172(10):699-701. doi:10.7326/m20-0696
  5. Confirmed Cases and Deaths by Country, Territory, or Conveyance. 2020; https://www.worldometers.info/coronavirus/.  Accessed March 27, 2020.
  6. Zhai Y, Wang Y, Zhang M, et al. From isolation to coordination: how can telemedicine help combat the Covid-19 outbreak? medRxiv. 2020. doi:10.1101/2020.02.20.20025957
  7. Zhong BL, Luo W, Li HM, et al. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int J Biol Sci. 2020;16(10):1745-1752. doi:10.7150/ijbs.45221
  8. Abdi M. Coronavirus disease 2019 (COVID-19) outbreak in Iran: actions and problems. Infect Control Hosp Epidemiol. 2020;41(6):754-755. doi:10.1017/ice.2020.86
  9. Hollander JE, Carr BG. Virtually perfect? telemedicine for Covid-19. N Engl J Med. 2020;382(18):1679-1681. doi:10.1056/NEJMp2003539
  10. Lurie N, Carr BG. The role of telehealth in the medical response to disasters. JAMA Intern Med. 2018;178(6):745-746. doi:10.1001/jamainternmed.2018.1314
  11. Giwa A, Desai A. Novel coronavirus COVID-19: an overview for emergency clinicians. Emerg Med Pract. 2020;22(2 Suppl 2):1-21.
  12. Srinivasa Rao ASR, Vazquez JA. Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine. Infect Control Hosp Epidemiol. 2020;41(7):826-830. doi:10.1017/ice.2020.61
  13. Gostic K, Gomez AC, Mummah RO, Kucharski AJ, Lloyd-Smith JO. Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19. Elife. 2020;9. doi:10.7554/eLife.5557
  14. Rossman H, Keshet A, Shilo S, et al. A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys. Nat Med. 2020;26(5):634-638. doi:10.1038/s41591-020-0857-9
  15. De Paoli P. Bio-banking in microbiology: from sample collection to epidemiology, diagnosis and research. FEMS Microbiol Rev. 2005; 29(5):897-910. doi:10.1016/j.femsre.2005.01.005
  16. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223):497-506. doi:10.1016/s0140-6736(20)30183-5
  17. CDC. Coronavirus (COVID-19). https://www.cdc.gov/coronavirus/2019-ncov/index.html.  Accessed March 27, 2020.
  18. World Health Organization (WHO). Coronavirus Disease (COVID-19) Pandemic. WHO; 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019.  Accessed March 27, 2020.
  19. COVID19 Epidemiology Committee. Clinical guidelines for COVID-19. http://corona.behdasht.gov.ir/.  Published 2020.
  20. Djalalinia S, Modirian M, Sheidaei A, et al. Protocol design for large-scale cross-sectional studies of surveillance of risk factors of non-communicable diseases in Iran: STEPs 2016. Arch Iran Med. 2017;20(9):608-616.
  21. Statistical Centre of Iran. https://www.amar.org.ir/.  Accessed 12 May 2020, 2020.
  22. Rising rural body-mass index is the main driver of the global obesity epidemic in adults. Nature. 2019;569(7755):260-264. doi:10.1038/s41586-019-1171-x
  23. COVID19 Epidemiology Committee. Diagnosis and treatment flowchart of COVID19 in outpatient and inpatient medical sections. 2020; http://dme.behdasht.gov.ir/uploads/Felo_Tashkish.pdf.  Accessed March 27, 2020.
  24. RABIT. https://rabit.info/#triology.  Accessed May 12, 2020.
  25. DIGIT. https://digit.rabit.info/.  Accessed May 12, 2020.
  26. VIZIT. https://vizit.report/en/index.html.  Accessed May 12, 2020, 2020.
  27. SUMIT. https://rabit.info/#sumit.  Accessed May 12, 2020, 2020.
  28. Sakamoto Y, Ishiguro M, Kitagawa G. Akaike Information Criterion Statistics. Dordrecht, The Netherlands: D. Reidel; 1986:81.
  29. Carpintero ERJ, Tavares EC, Souza DCN, et al. Benefits in using the telehealth: a necessary reflection. Lat Am J Telehealth. 2016;3(2):175-182.
  30. COVID-19 self-assessment website. https://salamat.gov.ir/.  Accessed May 12, 2020.
  31. Leung GM, Leung K. Crowdsourcing data to mitigate epidemics. Lancet Digit Health. 2020;2(4):e156-e157. doi:10.1016/s2589-7500(20)30055-8
  32. Cinelli M, Quattrociocchi W, Galeazzi A, et al. The COVID-19 social media infodemic. Sci Rep. 2020;10(1):16598. doi:10.1038/s41598-020-73510-5
  33. Zarocostas J. How to fight an infodemic. Lancet. 2020;395(10225):676. doi:10.1016/s0140-6736(20)30461-x
  34. Dorsey ER, Topol EJ. State of telehealth. N Engl J Med. 2016; 375(2):154-161. doi:10.1056/NEJMra1601705
  35. Simmons S, Alverson D, Poropatich R, D’Iorio J, DeVany M, Doarn CR. Applying telehealth in natural and anthropogenic disasters. Telemed J E Health. 2008;14(9):968-971. doi:10.1089/tmj.2008.0117
  36. Wade VA, Eliott JA, Hiller JE. Clinician acceptance is the key factor for sustainable telehealth services. Qual Health Res. 2014;24(5):682-694. doi:10.1177/1049732314528809
  37. COVID Symptom Study. https://covid.joinzoe.com/.  Accessed May 9, 2020, 2020.
  38. COVID-19 Screening Tool. 2020; https://www.apple.com/covid19. Accessed May 9, 2020.
  39. Segal E, Zhang F, Lin X, et al. Building an international consortium for tracking coronavirus health status. Nat Med. 2020;26(8):1161-1165. doi:10.1038/s41591-020-0929-x
Volume 11, Issue 7
July 2022
Pages 1069-1077
  • Receive Date: 10 June 2020
  • Revise Date: 15 November 2020
  • Accept Date: 06 December 2020
  • First Publish Date: 18 January 2021