Today, with the emergence of new technologies and massive data, big data analysis has attracted the attention of researchers, industries and universities on a global scale. The present research aims to explore students’ attitude to big data analysis in different fields of study. The present cross-sectional study was conducted with students at different universities and fields of study in Iran. A questionnaire was developed. This questionnaire explored students’ attitude toward big data analysis. To this aim, 359 university students participated in the research. The data were analyzed using descriptive and inferential statistics. The age of the students ranged between 25 and 34 years. 55.2% were female and 54% were economically active. 40.9% had a work experience of less than a year. The academic degree of the majority of participants was master’s degree. 93.9% of the participants believed that big data analysis was essential for the country. 43.2% maintained that big data mostly belonged to the communication industry. 28.1% perceived MATLAB useful software for analysis. 40.9% were familiar with the benefits of analysis. Engage in economic activities, less than 1 year of experience and studies for a Master’s degree showed to be significantly correlated with familiarity with the benefits of big data (p≤0.01). Such issues as high costs, managers’ unfamiliarity and lack of expertise and complexity were raised by the respondents. Considering the undeniable benefits of big data analysis, it seems essential to familiarize university students with these analyses through particular training courses, conferences and so on.

Introduction: This critical study was aimed to investigate the utility of the Global Health Security Index (GHSI) in predicting the current COVID-19 responses.Material and Methods: Number of infected patients, deaths, incidence and the death rate per 100,000 populations related to 55 countries per week for 26 weeks were extracted. The relationship of GHSI scores and country preparedness for the pandemic was compared.Results: According to the GHSI, the incidence rate in most prepared countries was higher than the incidence rate in the more prepared countries, and which was higher than the incidence rate in the least prepared countries. However, Prevention, Detection and reporting, Rapid response, Health system, compliance with international norms and Risk environment, as well as Overall, the incidence and death rate per 100,000 people have not been like this.Conclusion: Due to mismatch between the GHSI score and fact about COVID-19 incidence, it seems necessary to investigate the factors involved in this discrepancy.

The purpose of this study was to evaluate the students' familiarity from different universities of Mashhad with the benefits, applications and challenges of Big Data analysis. This is a cross-sectional study that was conducted on students of different fields, including Medical Engineering, Medical Informatics, Medical Records and Health Information Management in Mashhad-Iran. A questionnaire was designed. The designed questionnaire evaluated the opinion of students regarding benefits, challenges and applications of Big Data analytics. 200 students participated and participants' opinions were evaluated descriptively and analytically. Most students were between 20 and 30 years old. 43.5% had no work experience. Current and previous field of study of most of the students were HIT, HIM, and Medical Records. Most of the participants in this study were undergraduates. 61.5% were economically active, 54.5% were exposed to Big Data. The mean scores of participants in benefits, applications, and challenges section were 3.71, 3.68, and 3.71, respectively, and process management was significant in different age groups (p=0.046), information, modelling, research, and health informatics across different fields of studies were significant (p=0.015, 0.033, 0.001, 0.024) Information and research were significantly different between groups (p=0.043 and 0.019), research in groups with / without economic activity was significant (p= 0.017) and information in exposed / non-exposed to Big Data groups was significant (p=0.02). Despite the importance and benefits of Big Data analytics, students' lack of familiarity with the necessity and importance is significant. The field of study and level of study does not appear to have an effect on the degree of knowledge of individuals regarding Big Data analysis. The design of technical training courses in this field may increase the level of knowledge of individuals regarding Big Data analysis.