ABSTRACT
BackgroundThis study aims to estimate the prevalence of COVID-19 in the general population of Iran. MethodsThe target population was all Iranian people aged six years and older in the country. A stratified random sampling design was used to select 28,314 subjects from among the individuals registered in the electronic health record systems used in primary health care in Iran. Venous blood was taken from each participant and tested for the IgG antibody against COVID-19. The prevalence of COVID-19 was estimated at provincial and national levels after adjusting for the measurement error of the laboratory test, non-response bias, and sampling design. ResultsOf the 28,314 Iranians selected, 11,256 (39.75%) participated in the study. Of these, 5406 (48.0%) were male, and 6851 (60.9%) lived in urban areas. The mean (standard deviation) participant age was 35.89 (18.61) years. The adjusted prevalence of COVID-19 until August 20, 2020 was estimated as 14.2% (95% uncertainty interval: 13.3%, 15.2%), which was equal to 11,958,346 (95% confidence interval: 11,211,011-12,746,776) individuals. The prevalence of infection was 14.6%, 13.8%, 16.6%, 11.7%, and 19.4% among men, women, urban population, rural population, and individuals [≥]60 years of age, respectively. Ardabil, Golestan, and Khuzestan provinces had the highest prevalence, and Alborz, Hormozgan, and Kerman provinces had the lowest. ConclusionsBased on the study results, a large proportion of the Iranian population had not yet been infected by COVID-19. The observance of hygienic principles and social restrictions should therefore continue until the majority of the population has been vaccinated.
Subject(s)
COVID-19ABSTRACT
Background: Iran is one of the countries that has been overwhelmed with COVID-19. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios. Methods: We developed a Susceptible-Exposed-Infected-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 (UI). Findings: 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% (i.e. 550,000) and change the epidemic peak from 66,000 on June 9th to 9,400 on March 1st. Scenario E also reduces the hospitalizations by 92% (i.e. 74,500), and deaths by 93% (i.e. 7,800). Interpretation: With no approved vaccination or therapy, we found physical distancing and isolation that includes public awareness and case-finding/isolation of 40% of infected people can reduce the burden of COVID-19 in Iran by 90% by mid-June.