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Background: Using the WHO STEPwise approach to NCD risk factor surveillance (STEPS), first round of Iran’s STEPS completed in 2005. It has been repeated six times afterward. Here we report the results of 2016 round on the population characteristics and prevalence of diabetes and prediabetes, along with an assessment of the country-level performance on diabetes care in Iran. Methods: Using a proportional-to-size cluster random sampling method, the STEPS 2016 included 18947 subjects aged≥25 years who matched the criteria (non-missing information on diabetes self-report, and biomarkers). For the analyses, survey design methods with weighted samples were employed. Different definitions of diabetes (biomarker-based, self-report, anti-diabetes medication use, or a combination) and prediabetes (different cutpoints of the biomarker) were calculated and presented. Results: An estimated 5171035 persons aged≥25 years or 10.6% (95% CI: 10.0%–11.1%) had diabetes according to the serologic diagnosis of diabetes (FPG≥126 mg/dL) or the use of at least one anti-diabetes medication (1896 out of 18947). Employing the serologic diagnosis of diabetes among those who responded no to the self-reported question, 2.7% (2.5%–3.0%) of the population were not aware of their diabetes compared to 11.5% (10.9%-12.0%) who were diabetics according to the just self-reported question. Defining prediabetes as 100≤FPG9%) was found in 18.4% (16.3%-20.6%) of the patients with self-reported diabetes. Conclusion: Since 2005, the prevalence of diabetes in Iran has been on a gradual increase in both genders with an increasing gap between females and males.

Background: 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. Methods: 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. Results: 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. Conclusion: 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.