In this work, we employ a data-fitted compartmental model to visualize the progression and behavioural response to COVID-19 that match provincial case data in Ontario, Canada from February to June of 2020. This is a “rear-view mirror” glance at how this region has responded to the 1st wave of the pandemic, when testing was sparse and NPI measures were the only remedy to stave off the pandemic. We use an SEIR-type model with age-stratified subpopulations and their corresponding contact rates and asymptomatic rates in order to incorporate heterogeneity in our population and to calibrate the time-dependent reduction of Ontario-specific contact rates to reflect intervention measures in the province throughout lockdown and various stages of social-distancing measures. Cellphone mobility data taken from Google, combining several mobility categories, allows us to investigate the effects of mobility reduction and other NPI measures on the evolution of the pandemic. Of interest here is our quantification of the effectiveness of Ontario's response to COVID-19 before and after provincial measures and our conclusion that the sharp decrease in mobility has had a pronounced effect in the first few weeks of the lockdown, while its effect is harder to infer once other NPI measures took hold.

Purpose Education is a human right and access to high quality education is key to sustainable socioeconomic development. Improving the quality of higher education institutes is essential for generating the productive human resources. Assessing the quality of higher education from the students’ perspective can be considered a crucial factor in the monitoring of service quality in universities. The purpose of this paper is to evaluate the quality of educational services in a higher education institute, the Kermanshah University of Medical Sciences (KUMS), in the west of Iran. Design/methodology/approach A multistage sampling method was used to select 346 students from the KUMS, who were enrolled in the second semester of the academic year 2015-2016. The SERVQUAL questionnaire was used to gather data on students’ perceptions and their expectations about the quality of educational services. The authors used a statistical significance level of 0.05 to examine the gap between the students’ expectations and their perceptions of service quality in five dimensions, namely tangibles, responsiveness, reliability, empathy and assurance. Findings The results showed that there was a negative service quality gap in all five dimensions. The overall mean score of students’ expectations and their perceptions was 3.19±0.44 and 2.4±0.45, respectively. The score gap between the overall mean score of perceptions and expectations of students was −0.79, which was statistically significant (p<0.0001). The highest and lowest quality gaps were related to the assurance (−0.84) and tangible (−0.70) dimensions, respectively. Originality/value The study indicated that the quality of educational services provided in the KUMS did not meet students’ expectations in five dimensions of service quality. Thus, it warrants further investigations to determine how to improve the quality of educational services in higher education institutes such as the KUMS.

Background The outbreak of Coronavirus disease, which originated in Wuhan, China in 2019, has affected the lives of billions of people globally. Throughout 2020, the reproduction number of COVID-19 was widely used by decision-makers to explain their strategies to control the pandemic. Methods In this work, we deduce and analyze both initial and effective reproduction numbers for 12 diverse world regions between February and December of 2020. We consider mobility reductions, mask wearing and compliance with masks, mask efficacy values alongside other non-pharmaceutical interventions (NPIs) in each region to get further insights in how each of the above factored into each region’s SARS-COV-2 transmission dynamic. Results We quantify in each region the following reductions in the observed effective reproduction numbers of the pandemic: i) reduction due to decrease in mobility (as captured in Google mobility reports); ii) reduction due to mask wearing and mask compliance; iii) reduction due to other NPI’s, over and above the ones identified in i) and ii). Conclusion In most cases mobility reduction coming from nationwide lockdown measures has helped stave off the initial wave in countries who took these types of measures. Beyond the first waves, mask mandates and compliance, together with social-distancing measures (which we refer to as other NPI’s) have allowed some control of subsequent disease spread. The methodology we propose here is novel and can be applied to other respiratory diseases such as influenza or RSV.

Background: Academic satisfaction is considered one of the most important factors affecting academic achievement among students. The purpose of the present study was to determine the relationship between academic satisfaction and academic achievement among students at

Background: Road accidents are a major cause of deaths, injuries, and financial losses globally, especially in developing countries. Iran is one of the countries with a high rate of road accidents causing considerable damage in different domains. Therefore, in order to tackle this problem, we need to examine its causes. Objectives: The aim of the present study was to examine the association of risky driving behavior with impulsiveness, attentional bias, and decision-making styles. Patients and Methods: This was a descriptive-correlational study. The sample included 117 male drivers, aged 20 - 34 years, attending car insurance agencies in Tehran. The participants were selected using the convenience sampling method. The data were gathered using the Manchester Driver Behavior Questionnaire (DBQ), the Barratt Impulsiveness Scale (BIS), the Decision-Making Style Scale (DMS), and the Dot Probe Task to assess attentional bias. All data analysis was conducted using Pearson correlation coefficient and multiple regression analysis, by using SPSS, version 22. Results: According to the results of the Pearson correlation coefficient, risky driving behavior was significantly correlated with impulsiveness subscales (P < 0.01) and attentional bias (P < 0.05). In addition, significant relationships were observed between risky driving behaviors and three decision-making styles, including rational (P < 0.05), spontaneous (P < 0.01), and avoidant (P < 0.01). Conclusions: Based on the study results, impulsivity, decision-making styles, and attentional bias as factors influencing drivers’ cognitive skills related to driving, could explain the increase in the frequency of risky driving behavior.