Investigating the relationship between occupation and SARS-CoV2.

BACKGROUND: Coronaviruses are a large family of viruses that have symptoms ranging from simple symptoms of colds to severe respiratory syndromes. In December 2019, cases of unknown pneumonia first appeared in Wuhan, China. OBJECTIVE: The purpose of this study was to investigate the relationship between occupation and COVID-19 in the Ardabil Imam Khomeini hospital. METHODS: This research was conducted as a cross-sectional and descriptive study. The questionnaires used in this study included demographic information to obtain the required information such as age, sex, clinical symptoms, underlying disease, type of drug used, smoking, occupation, hours of work, number of daily clients, use of mask or shield, type of working hours, weight and height and body mass index, number family, place of residence, role in the family, presence of an infected person in the family, communication with the suspect, observance or non-observance of health protocols. Our sample size consisted of 774 subjects, all patients at the Ardabil Imam Khomeini Hospital. The subjects were selected randomly. RESULTS: The results of this study showed that the mean age of patients was 56.70 years, with a standard deviation of 18.20 years. Three hundred and sixty participants (46.5%) were female, and 414 (53.5%) were male. In terms of occupation distribution, 317 patients (41%) were housewives. In addition, 57 people (7.4%) were farmers or ranchers. CONCLUSION: In general, it can be concluded that due to severity of infection and threat posed by Coronavirus and the risk of infections between different occupations like the taxi driver and medical staff, it is very important to find out what jobs are in the big threat.

The COVID-19 pandemic's true death toll in Iran after two years: an interrupted time series analysis of weekly all-cause mortality data.

INTRODUCTION: This study aimed to investigate overall and age group/region/sex-specific excess all-cause mortality from the inception of the COVID-19 pandemic in Iran until February 2022. METHODS: Weekly all-cause mortality data were obtained for the period March 2015 until February 2022. We conducted interrupted time series analyses, using a generalized least-square regression model to estimate excess mortality after the COVID-19 pandemic. Using this approach, we estimated the expected post-pandemic death counts based on five years of pre-pandemic data and compared the results with observed mortality during the pandemic. RESULTS: After the COVID-19 pandemic, we observed an immediate increase (1,934 deaths per week, p = 0.01) in weekly all-cause mortality. An estimated 240,390 excess deaths were observed in two years after the pandemic. Within the same period, 136,166 deaths were officially attributed to COVID-19. The excess mortality was greatest among males compared with females (326 versus 264 per 100k), with an increasing trend by age group. There is a clear increased excess mortality in the central and northwestern provinces. CONCLUSION: We found that the full mortality burden during the outbreak has been much heavier than what is officially reported, with clear differences by sex, age group, and geographical region.

Risk-Taking Behaviors Considering Internet Gaming Disorder among Iranian University Students: A Latent Class Analysis.

BACKGROUND: Dangerous behaviors adversely affect the health of adolescents and young adults. This study aimed to identify the subgroups of college students based on the parameters of risky behavior and analyze the impact of demographic factors and internet gaming disorder (IGD) belonging to each class. STUDY DESIGN: A cross-sectional study. METHODS: The study was conducted on 1355 students through a multi-stage random sampling method in 2020. A survey questionnaire was used to collect data, and all students completed 1294 sets of questionnaires. The data were analyzed using t test and latent class analysis (LCA) through SPSS and PROC LCA in SAS 9.2 software. RESULTS: Three latent classes have been identified as low-risk (75%), tobacco smoker (8%), and high-risk (17%). There was a high possibility of risky behavior in the third class. Marital status (being single) (OR = 2.28, 95% CI: 1.19-4.37), unemployment (having no job) along with education (OR = 1.56, 95% CI: 1.04-2.33), and IGD (OR = 1.06, 95% CI: 1.04-1.09) increased the risk of inclusion in the tobacco smoker class. Moreover, unemployment (having no job) along with education (OR = 1.43, 95% CI: 1.11-1.84) increased the chance of being in the high-risk class. CONCLUSION: According to the findings of this study, 25% of the students were tobacco smokers or were in the high-risk class. The results of this study may help develop and evaluate preventive strategies that simultaneously take into account different behaviors.

Case fatality rate of COVID-19: a systematic review and meta-analysis.

OBJECTIVE: The ongoing novel coronavirus disease 2019 (COVID-19) is the leading cause of morbidity and mortality due to its contagious nature and absence of vaccine and treatment. Although numerous primary studies reported extremely variable case fatality rate (CFR) of COVID-19, no review study attempted to estimate the CFR of COVID-19. The current systematic review and meta-analysis were aimed to assess the pooled CFR of COVID-19. METHODS: Electronic databases: PubMed, Science Direct, Scopus, and Google Scholar were searched to retrieve the eligible primary studies that reported CFR of COVID-19. Keywords: ("COVID-19"OR "COVID-2019" OR "severe acute respiratory syndrome coronavirus 2"OR "severe acute respiratory syndrome coronavirus 2" OR "2019-nCoV" OR "SARS-CoV-2" OR "2019nCoV" OR (("Wuhan" AND ("coronavirus" OR "coronavirus")) AND (2019/12[PDAT] OR 2020[PDAT]))) AND ("mortality "OR "mortality" OR ("case" AND "fatality" AND "rate") OR "case fatality rate") were used as free text and MeSH term in searching process. A random-effects model was used to estimate the CFR in this study. I2 statistics, Cochran's Q test, and T2 were used to assess the functional heterogeneity between included studies. RESULTS: The overall pooled CFR of COVID 19 was 10.0%(95% CI: 8.0-11.0); P < 0.001; I2 = 99.7). The pooled CFR of COVID-19 in general population was 1.0% (95% CI: 1.0-3.0); P < 0.001; I2 = 94.3), while in hospitalized patients was 13.0% (95% CI: 9.0-17.0); P < 0.001, I2 = 95.6). The pooled CFR in patients admitted in intensive care unit (ICU) was 37.0% (95% CI: 24.0-51.0); P < 0.001, I2 = 97.8) and in patients older than 50 years was 19.0% (95% CI: 13.0-24.0); P < 0.001; I2 = 99.8). CONCLUSION: The present review results highlighted the need for transparency in testing and reporting policies and denominators used in CFR estimation. It is also necessary to report the case's age, sex, and the comorbidity distribution of all patients, which essential in comparing the CFR among different segments of the population.

Epidemiological characteristics and mortality risk factors among COVID-19 patients in Ardabil, Northwest of Iran.

BACKGROUND: Coronavirus disease highly contagious, is prevalent in all age and sex groups infecting the respiratory system. The present study seeks to investigate the epidemiology and effective factors in mortality of patients with COVID-19 in Ardabil province, northwestern Iran. METHODS: In a retrospective study, the hospitalized patients with laboratory-diagnosed COVID-19 between February to August 2020 were enrolled. The data registration portal was designated according to Iranian Ministry of Health and Medical Education guidelines. In this portal, demographic information, clinical presentation, laboratory and imaging data were registered for patients in all hospitals in the same format. The Hosmer-Lemeshow strategy was used for variable selection in a multiple model. RESULTS: Of the patients involved 2812(50.3%) were male and 150 (2.7%) had contact with a confirmed case of COVID-19 in the last 14 days. Pre-existing comorbidity was reported in 1310 (23.4%) patients. Of all patients, 477(8.5%) died due to COVID-19. the result of the multiple logistic regression model indicated that after adjusting for other factors, higher age (OR = 3.11), fever or chills (OR = 1.61), shortness of breath (OR = 1.82), fatigue (OR = 0.71), headache (OR = 0.64), runny nose (OR = 1.54), Skeletal muscle pain (OR = 1.53), hospitalization (OR = 5.66), and hospitalization in ICU (OR = 5.12) were associated with death. CONCLUSIONS: Hospitalization had the strongest effect on mortality followed by hospitalization in ICU, and higher age. This study showed that having some extra-pulmonary symptoms in contrast with pulmonary symptoms can predict as good prognostic factors.