Excess deaths during the COVID-19 pandemic in Iran.

BACKGROUND: The actual number of deaths during the COVID-19 pandemic is expected to be higher than the reported deaths. We aimed to estimate the number of deaths in Iran during the COVID-19 pandemic from December 22, 2019 to March 20, 2022. METHODS: We compared the number of age- and sex-specific deaths reported by Iran's Bureau of Vital Statistics with the predicted deaths estimated using an improved Lee-Carter model. We estimated the number of all-cause excess deaths in three scenarios, including the baseline scenario (without any undercounting of deaths) and 4% and 8% undercounting of all-cause deaths. RESULTS: We estimated 282,378 (95% confidence intervals [CI]: 225,439; 341,951) excess deaths in the baseline model. This number was 303,148 (95% CI: 246,417; 357,823) and 308,486 (95% CI: 250,607; 364,417) in the 4% and 8% scenarios, respectively. During the same period, Iran reported 139,610 deaths as being directly related to COVID-19. The ratio of reported COVID-19 deaths to total excess deaths ranged from 45.2% to 49.4% in the various scenarios. Most excess deaths occurred in the baseline scenario in males (157,552 [95% CI: 125,142; 191,265]) and those aged ≥75 years (102,369 [95% CI: 93,894; 111,188]). CONCLUSIONS: The reported number of COVID-19 deaths was less than half of Iran's estimated number of excess deaths. The results of this study will be helpful for health policymakers' planning, and call for strengthening the timeliness and accuracy of Iran's death registration systems, planning for more accurate monitoring of epidemics, and planning to provide support services for survivors' families.

Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study.

COVID-19 is spreading all over Iran, and Kerman is one of the most affected cities. We conducted this study to predict COVID-19-related deaths, hospitalization, and infected cases under different scenarios (scenarios A, B, and C) by 31 December 2021 in Kerman. We also aimed to assess the impact of new COVID-19 variants and vaccination on the total number of COVID-19 cases, deaths, and hospitalizations (scenarios D, E, and F) using the modified susceptible-exposed-infected-removed (SEIR) model. We calibrated the model using deaths reported from the start of the epidemic to August 30, 2021. A Monte Carlo Markov Chain (MCMC) uncertainty analysis was used to estimate 95% uncertainty intervals (UI). We also calculated the time-varying reproductive number (R t) following time-dependent methods. Under the worst-case scenario (scenario A; contact rate = 10, self-isolation rate = 30%, and average vaccination shots per day = 5,000), the total number of infections by December 31, 2021, would be 1,625,000 (95% UI: 1,112,000-1,898,000) with 6,700 deaths (95% UI: 5,200-8,700). With the presence of alpha and delta variants without vaccine (scenario D), the total number of infected cases and the death toll were estimated to be 957,000 (95% UI: 208,000-1,463,000) and 4,500 (95% UI: 1,500-7,000), respectively. If 70% of the population were vaccinated when the alpha variant was dominant (scenario E), the total number of infected cases and deaths would be 608,000 (95% UI: 122,000-743,000) and 2,700 (95% UI: 700-4,000), respectively. The R t was ≥1 almost every day during the epidemic. Our results suggest that policymakers should concentrate on improving vaccination and interventions, such as reducing social contacts, stricter limitations for gathering, public education to promote social distancing, incensing case finding and contact tracing, effective isolation, and quarantine to prevent more COVID-19 cases, hospitalizations, and deaths in Kerman.

Prevalence and Motives of Social Media Use among the Iranian Population.

Background: Around the world, people are using social media (SM) for different purposes following a wide range of patterns. There is a paucity of studies addressing the issue in the Eastern Mediterranean region. In this population-based study, the frequency and patterns of SM use in Iran were investigated. Materials and Methods: To explore the prevalence and motives of SM use, a sample of 1800 Iranian people aged 10-65 years old (53.5% female) were surveyed. Social media addiction (SMA) was assessed using the Bergen Social Media Addiction Scale. Results: The results revealed that 88.5% (n = 1593) of the participants were SM users, and the average time spent by them in SM was 4.0 ± 3.9 hours. The most common motivations for SM use were communication with others (48.9%), receiving news (40.7%), and surfing the net (40.6%). Besides, burning eyes (31.0%), headache (26.8%), and sleep disturbance (25.1%) were the most common health problems experienced by SM users. The SMA prevalence was 23.1% (95% CI: 21.2, 25.1) (males: 23.8%; females: 22.5%), with a higher rate (26.0%) among adolescents and young people. Conclusion: SM use and SMA appear to be real health challenges in Iran, particularly among youth. Consequently, to decrease the negative impacts of excessive SM use, exploring the motives behind SM use and designing population-based interventions are recommended.

Therapeutic interventions for COVID-19: a living overview of reviews.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide, but safe and effective treatment options remain unavailable. Numerous systematic reviews of varying qualities have tried to summarize the evidence on the available therapeutic interventions for COVID-19. This overview of reviews aims to provide a succinct summary of the findings of systematic reviews on different pharmacological and non-pharmacological therapeutic interventions for COVID-19. METHODS: We searched PubMed, Embase, Google Scholar, Cochrane Database of Systematic Reviews, and WHO database of publications on COVID-19 from 1 December 2019 through to 11 June 2020 for peer-reviewed systematic review studies that reported on potential pharmacological or non-pharmacological therapies for COVID-19. Quality assessment was completed using A MeaSurement Tool to Assess systematic Reviews-2 (AMSTAR-2) measure. RESULTS: Out of 816 non-duplicate studies, 45 were included in the overview. Antiviral and antibiotic agents, corticosteroids, and anti-malarial agents were the most common drug classes used to treat COVID-19; however, there was no direct or strong evidence to support their efficacy. Oxygen therapy and ventilatory support was the most common non-pharmacological supportive care. The quality of most of the included reviews was rated as low or critically low. CONCLUSION: This overview of reviews demonstrates that although some therapeutic interventions may be beneficial to specific subgroups of COVID-19 patients, the available data are insufficient to strongly recommend any particular treatment option to be used at a population level. Future systematic reviews on COVID-19 treatments should adhere to the recommended systematic review methodologies and ensure that promptness and comprehensiveness are balanced.The reviews of this paper are available via the supplemental material section.