Airborne spread of the virus appears to explain this large community outbreak of SARS, and future efforts at prevention and control must take into consideration the potential for airborne spread of this virus.

The prevalence of depression may be affected by changes in psychiatric practices and the availability of online mental health information in the past two decades. This study aimed to evaluate the aggregate prevalence of depression in communities from different countries between 1994 and 2014 and to explore the variations in prevalence stratified by geographical, methodological and socio-economic factors. A total of 90 studies were identified and met the inclusion criteria (n = 1,112,573 adults) with 68 studies on single point prevalence, 9 studies on one-year prevalence, and 13 studies on lifetime prevalence of depression. A random-effects model meta-analysis that was performed to calculate the aggregate point, one-year and lifetime prevalence of depression calculated prevalences of 12.9%, 7.2% and 10.8% respectively. Point prevalence of depression was significantly higher in women (14.4%), countries with a medium human development index (HDI) (29.2%), studies published from 2004 to 2014 (15.4%) and when using self-reporting instruments (17.3%) to assess depression. Heterogeneity was identified by meta-regression and subgroup analysis, and response rate, percentage of women and year of publication, respectively, were determined contribute to depression prevalence. This meta-analysis allows benchmarking of the prevalence of depression during the era when online health information emerged, facilitating future comparisons.

Depression affects almost one-third of medical students globally but treatment rates are relatively low. The current findings suggest that medical schools and health authorities should offer early detection and prevention programmes, and interventions for depression amongst medical students before graduation.

Objective: To provide a comprehensive picture of mental health problems (MHPs) in Brazilian medical students by documenting their prevalence and association with co-factors. Methods: We systematically searched the MEDLINE/PubMed, SciELO, LILACS, and PsycINFO databases for cross-sectional studies on the prevalence of MHPs among medical students in Brazil published before September 29, 2016. We pooled prevalences using a random-effects meta-analysis, and summarized factors associated with MHP. Results: We included 59 studies in the analysis. For meta-analyses, we identified the summary prevalence of different MHPs, including depression (25 studies, prevalence 30.6%), common mental disorders (13 studies, prevalence 31.5%), burnout (three studies, prevalence 13.1%), problematic alcohol use (three studies, prevalence 32.9%), stress (six studies, prevalence 49.9%), low sleep quality (four studies, prevalence 51.5%), excessive daytime sleepiness (four studies, prevalence 46.1%), and anxiety (six studies, prevalence 32.9%). Signs of lack of motivation, emotional support, and academic overload correlated with MHPs. Conclusion: Several MHPs are highly prevalent among future physicians in Brazil. Evidence-based interventions and psychosocial support are needed to promote mental health among Brazilian medical students.

This meta-analysis aimed to evaluate the association between childhood and adolescent obesity and depression. We systematically searched PubMed, PsycInfo, EMBASE and Science Direct for studies that compared prevalence of depression and depressive symptoms in normal weight and obese children and adolescents. Observational studies were included if they reported body mass index and assessed depression by validated instruments or diagnostic interviews. Quality assessment was performed using the Newcastle-Ottawa scale. We used the random-effect model to calculate the pooled odds ratios, standard mean differences (SMDs) and subgroup analysis. Findings for a total of 51,272 participants were pooled across 18 studies and examined. Our analyses demonstrated a positive association between childhood and adolescent obesity and depression (pooled odds ratio = 1.34, 95% confidence interval [CI]: 1.1-1.64, p = 0.005) and more severe depressive symptoms (SMD = 0.23, 95% CI: 0.025-0.44, p = 0.028) in the obese groups. Overweight subjects were not more likely to have either depression (pooled odds ratio = 1.16, 95% CI: 0.93-1.44, p = 0.19) or depressive symptoms (SMD = 0, 95% CI: -0.101 to 0.102, p = 0.997). Non-Western and female obese subjects were significantly more likely to have depression and severe depressive symptoms (p < 0.05). In conclusion, obese children and adolescents are more likely to suffer from depression and depressive symptoms, with women and non-Western people at higher risk.

The burnout syndrome is characterized by emotional exhaustion, depersonalization, and reduced personal achievement. Uncertainty exists about the prevalence of burnout among medical and surgical residents. Associations between burnout and gender, age, specialty, and geographical location of training are unclear. In this meta-analysis, we aimed to quantitatively summarize the global prevalence rates of burnout among residents, by specialty and its contributing factors. We searched PubMed, PsycINFO, Embase, and Web of Science to identify studies that examined the prevalence of burnout among residents from various specialties and countries. The primary outcome assessed was the aggregate prevalence of burnout among all residents. The random effects model was used to calculate the aggregate prevalence, and heterogeneity was assessed by I2 statistic and Cochran’s Q statistic. We also performed meta-regression and subgroup analysis. The aggregate prevalence of burnout was 51.0% (95% CI: 45.0–57.0%, I2 = 97%) in 22,778 residents. Meta-regression found that the mean age (β = 0.34, 95% CI: 0.28–0.40, p < 0.001) and the proportion of males (β = 0.4, 95% CI = 0.10–0.69, p = 0.009) were significant moderators. Subgroup analysis by specialty showed that radiology (77.16%, 95% CI: 5.99–99.45), neurology (71.93%, 95% CI: 65.78–77.39), and general surgery (58.39%, 95% CI: 45.72–70.04) were the top three specialties with the highest prevalence of burnout. In contrast, psychiatry (42.05%, 95% CI: 33.09–51.58), oncology (38.36%, 95% CI: 32.69–44.37), and family medicine (35.97%, 95% CI: 13.89–66.18) had the lowest prevalence of burnout. Subgroup analysis also found that the prevalence of burnout in several Asian countries was 57.18% (95% CI: 45.8–67.85); in several European countries it was 27.72% (95% CI: 17.4–41.11) and in North America it was 51.64% (46.96–56.28). Our findings suggest a high prevalence of burnout among medical and surgical residents. Older and male residents suffered more than their respective counterparts.

Results-Significant associations were found between hospital admissions for all respiratory diseases, all cardiovascular diseases, chronic obstructive pulmonary diseases, and heart failure and the concentrations of all four pollutants. Admissions for asthma, pneumonia, and influenza were significantly associated with NO 2 , O 3, and PM 10 . Relative risk (RR) for admissions for respiratory disease for the four pollutants ranged from 1.013 (for SO 2 ) to 1.022 (for O 3 ), and for admissions for cardiovascular disease, from 1.006 (for PM 10 ) to 1.016 (for SO 2 ). Those aged >65 years were at higher risk. Significant positive interactions were detected between NO 2 , O 3 , and PM 10 , and between O 3 and winter months. Conclusions-Adverse health eVects are evident at current ambient concentrations of air pollutants. Further reduction in air pollution is necessary to protect the health of the community, especially that of the high risk group. (Occup Environ Med 1999;56:679-683)

The increasing application of Artificial Intelligence (AI) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI in health and medicine. A total of 27,451 papers that were published between 1977 and 2018 (84.6% were dated 2008–2018) were retrieved from the Web of Science platform. The descriptive analysis examined the publication volume, and authors and countries collaboration. A global network of authors’ keywords and content analysis of related scientific literature highlighted major techniques, including Robotic, Machine learning, Artificial neural network, Artificial intelligence, Natural language process, and their most frequent applications in Clinical Prediction and Treatment. The number of cancer-related publications was the highest, followed by Heart Diseases and Stroke, Vision impairment, Alzheimer’s, and Depression. Moreover, the shortage in the research of AI application to some high burden diseases suggests future directions in AI research. This study offers a first and comprehensive picture of the global efforts directed towards this increasingly important and prolific field of research and suggests the development of global and national protocols and regulations on the justification and adaptation of medical AI products.