Epidemiology

Purposes: The purpose of this study was to determine the epidemiology of coronavirus anxiety and the demographic factors related to it in Qazvin, Iran. Method: The method used in this study was descriptive-survey. Its statistical population included all Qazvin citizens in the spring of 2020. A total number of 1167 participants were recruited by convenient sampling and via an online questionnaire distributed on social media. They answered the demographic features and corona disease anxiety scale (CDAS) questionnaires.Their data were imported into the statistical software SPSS 25 and analyzed using the descriptive and inferential statistical tests like frequency test, percentile frequency, and Kruskal Wallis. results: The results of the analyses showed that the prevalence of coronavirus anxiety among Qazvin citizens was 13.54%. There was no significant difference between coronavirus anxiety level and its related factors in different “gender” and “educational background” groups. But still, in different “age” and “marital status” groups, a significant difference was found. Discussion: The results of the current study show that as people grow older,coronavirus anxiety level and its related factors increases. Conclusion: it can be concluded that coronavirus anxiety level and its related factors is higher among the older people when compared with the younger ones.

The Coronavirus disease (Covid-19) is one of the infectious and contagious ones called 2019-nCoV acute respiratory disease. Its outbreak was first reported on December 31, 2019, in the Chinese city of Wuhan that quickly spread throughout the country within a few weeks and spread to several other countries, including Italy, the United States, and Germany, within a month. This disease was officially reported in Iran on February 19, 2020. It is important to detect and analyze high risk zones and establish regulations according to the data and the analyses of Geographic Information System (GIS) in epidemiological situations. Meanwhile, the GIS, with its location nature, can be effective in preventing the breakdown of Covid-19 by displaying and analyzing the dangerous zones where people infected with the disease. In fact, recognizing regions based on the risk of getting the disease can influence social restriction policies and urban movement rules in order to prepare daily and weekly plans in different urban regions. In this applied and analytical research, high and low risk zones of Tehran have been identified by using the random forest algorithm which is used for both classification and regression. The algorithm builds decision trees on data samples and then predicts data from each of them, and finally chooses the best solution. In this research, 7 effective criteria have been used in the level of risk of regions toward Covid-19 virus, which is: subway paths and bus for rapid transits, hospitals, administrative and commercial complexes, passageways, population densities and urban traffic. After providing the map of high-risk zones of Covid-19, the Receiver Operating Characteristic curve (ROC) has been used for evaluation. The area under the curve (AUC) obtained from ROC shows an accuracy of 98.8%, which means the high accuracy of this algorithm in predicting high and low zones toward getting the Covid-19 disease.

INTRODUCTION: Iran, especially the Sistan-Baluchestan province, is one of the countries with the highest rates of accidents and traffic-related deaths. The present study aimed to evaluate traffic accidents referred to hospitals and the Forensic Medicine Department in Nikshahr in Sistan-Baluchestan province, Iran, during 2014-2018. METHODS: In this retrospective descriptive and analytical study, the statistical population included traffic accidents referred to hospitals and the Department of Forensic Medicine in Nikshahr. The data related to the variables of age, gender, location of the accident (inside or outside urban areas, rural roads), condition of the injured, severity of the injury, and the time of the accident were collected using a checklist. After determining the descriptive statistical indicators, the incidents were analyzed using chi-square and correlation tests. FINDINGS: During the study years in Nikshahr, a total of 3,669 people were involved in road accidents, out of whom 339 cases lost their lives. The highest rate of accidents (36%; n=1321) was in the age group of 19-29 years. Regarding education, 3, 260 (88.8%) crash victims were illiterate and without a university degree, while 409 (11.15%) cases had academic education. It was also detected that 1,879 (51.2%) accident victims were motorcycle riders with reported fractures, severe injuries, head injuries, and death. CONCLUSION: The results of the current pointed to the high rate of traffic-related deaths in Nikshahr, especially in summer. Therefore, prevention management is necessary to reduce traffic accidents and fatalities.

Introduction: playing the instrument in different groups of society is increasing day by day. Therefore, it seems necessary to pay attention to musculoskeletal imbalances and their problems in musicians. Methods: 90 instrumentalists, including 26 wood wind players (age: 28.46 ± 4.62 years, BMI: 26.59 ± 2.11), 37 string players (age 28.18 ± 7 years, BMI: 24.92 ± 3.60), and 27 percussionists (age: 31.88 ± 6.6 years, BMI: 24.95 ± 3.32) Were selected to participate in this study. Upper and lower extremities were assessed. For statistical analysis ANOVA, Scheffe and Kruskal-Wallis statistical tests were performed in SPSS version 16 with a significance level of 0.05. Results: The results of this study did not show significant differences between the degree of musculoskeletal imbalances of kyphosis and lordosis between the study groups (p˃0.05). Results in musculoskeletal imbalances of scoliosis(Sig = 0.001), forward head(Sig = 0.001), uneven shoulder(Sig = 0.001), torticollis(sig = 0.001), scapular dyskinesia (Sig = 0.006) were showed the significant differences between the groups(p˂0.05). Conclusion: According to the results, some musculoskeletal imbalances in the group of wood wind instrumentalists showed a higher intensity and prevalence. These variabilities between different groups of musicians indicate different physical and postural needs to play different instruments.