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

Background: Because of high prevalence of coronary artery diseases (CADs) in Iran and their relationship with low physical activity (LPA), this study aimed to measure the epidemic size of LPA, its incidence rate, and its relationship with other CAD risk factors in Kerman, Iran. Methods: About 10,000 adults were randomly recruited through single-stage cluster sampling. Demographic characteristics, biochemical variables, smoking, opium use, mental status, and physical activities were assessed. The relationship between LPA and 7 other CAD risk factors was measured. Five-year incidence rate of LPA was calculated according to the data from the physically active participants in the first phase of the study (n = 3416) who attended the second phase after 5 years. Results: The prevalence of low, moderate, and intense physical activity was 47.2%, 34.8%, and 18.0%, respectively. LPA rose from 45.1% to 62.2% after the age of 25 years. Women had higher LPA than men. Participants with LPA had significantly higher chance of cigarette smoking, diabetes, overweight/obesity, hypertension, and opium addiction. Five-year incidence rate of LPA was 5.1 persons/100 person-years among physically active population. Conclusion: Almost half of the studied population suffering from LPA was at risk of CAD. Such risky lifestyle pattern while worsened in the last 5 years makes the emerging of CAD epidemic unavoidable, if appropriate timely interventions not being in place accordingly.

Background: During the first months of the coronavirus disease 2019 (COVID-19) pandemic, Iran reported high numbers of infections and deaths. In the following months, the burden of this infection decreased significantly, possibly due to the impact of a package of interventions. We modeled the dynamics of COVID-19 infection in Iran to quantify the impacts of these interventions. Methods: We used a modified susceptible-exposed-infected-recovered (SEIR) model to model the COVID-19 epidemic in Iran, from January 21, 2020 to September 21, 2020. We estimated the 95% uncertainty intervals (UIs) using Markov chain Monte Carlo simulation. Under different scenarios, we assessed the effectiveness of non-pharmaceutical interventions (NPIs) including physical distancing measures and self-isolation. We also estimated the time-varying reproduction number (R t ), using our mathematical model and epidemiologic data. Results: If no NPIs were applied, there could have been a cumulative number of 51 800 000 (95% UI: 1 910 000-77 600 000) COVID-19 infections and 266 000 (95% UI: 119 000-476 000) deaths by September 21, 2020. If physical distancing interventions, such as school/border closures and self-isolation interventions had been introduced a week earlier than they were actually launched, 30.8% and 35.2% reduction in the number of deaths and infections respectively could have been achieved by September 21, 2020. The observed daily number of deaths showed that the Rt was one or more than one almost every day during the analysis period. Conclusion: Our models suggest that the NPIs implemented in Iran between January 21, 2020 and September 21, 2020 had significant effects on the spread of the COVID-19 epidemic. Our study also showed that the timely implementation of NPIs showed a profound effect on further reductions in the numbers of infections and deaths. This highlights the importance of forecasting and early detection of future waves of infection and of the need for effective preparedness and response capabilities.

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Background The novel Coronavirus disease 2019 (COVID-19) rapidly became the world’s largest threat to health and the economy in recent times. Prediction of the COVID-19 pandemic’s full impact is a necessary gauge for future policy making, including resource allocation for prevention, mitigation, and control preparedness.Methods We used the extended form of the Susceptible-Exposed-Infected/Infectious-Recovered/Removed (SEIR) model to predict new cases and number of deaths associated to COVID-19. Data from the Ministry of Health and Medical Education of Iran provided relevant parameters for predicting disability-adjusted life years (DALYs). We conducted a review of the literature on COVID-19-like diseases to develop disability weights (DWs) and convened an expert panel to verify their applicability. Beta-PERT distributions were used to calculate DWs for age groups. The minimum and maximum values were 0 and 0.14 for mild to severe disability, respectively.Results The total DALYs for COVID-19 in Iran predicted by our model will be 973 per 100,000 populations from January, 2020 to January, 2021. Overall, 957 years per 100,000 will be from YLLs (98.4% of DALYs) and 16 will be from YLDs (1.6% of DALY). The total DALYs in men will be 1,082 years per 100,000 and 861 per 100,000 in women.Conclusions Our predictions of COVID-19 burden will be useful in determining health priorities and to appropriately allocate resources to prepare for future outbreaks of COVID-19 and similar diseases. We hope this study will contribute to evidence-based health policy making in Iran.