E-cigarettes are widely advertised, while the potential risks of e-cigarette use have been reported among adolescents. This study assessed online e-cigarette information exposure and its association with adolescents’ e-cigarette use in Shanghai, China. A total of 12,470 students aged 13–18 years participated. A questionnaire collected information on students’ sociodemographic factors, e-cigarette information exposure, cigarette use, e-cigarette use, and e-cigarette use intention. A multivariate logistic regression was performed to assess correlates of exposure to e-cigarette information and the association between e-cigarette information exposure and e-cigarette use. Overall, 73.9% of students knew about e-cigarettes and the primary sources of information were the internet (42.4%), movies/TV (36.4%), bulletin boards in retail stores or supermarkets (34.9%), advertising flyers (33.9%), and friends (13.8%). Students who had friends using e-cigarettes were curious about e-cigarettes and showed a greater monthly allowance; smokers and females were at a higher risk of social media and website exposure. Moreover, online information exposure (social media exposure, website exposure, and total internet exposure) was significantly associated with the intention to use e-cigarettes. The enforcement of regulations on online e-cigarette content should be implemented. Moreover, efforts to prevent young people from using e-cigarettes may benefit from targeting students at a higher risk of online e-cigarette information exposure.

In 2020, the lockdown of Wuhan due to the outbreak of COVID‐19 impacted various aspects of local college students' life and may further negatively affect their psychological state. This study was conducted among 652 Wuhan local college students during the quarantine of this city. We assessed their psychological state using Depression‐Anxiety‐Stress Scale 21 and evaluated their living condition including diet, schedule, recreational activities, social contact, academic life, and attention paid to pandemic news. Results showed that 16.87% of the students reported stress, 28.68% with anxiety, and 35.12% had depression. According to multivariate logistic regression analysis, having a medical background was associated with higher stress levels; students who had an irregular diet and schedule were more likely to develop stress, anxiety, and depression; students with their academic life affected had a higher prevalence of anxiety and depression. By studying local students in the hardest‐hit area during the pandemic, our findings can provide references for the improvement of college students' mental health in the long term.

Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

ObjectiveThis study investigated adolescents' social-environmental exposure to e-cigarettes in association with e-cigarette use in Shanghai, China. We also explored these differences by gender and school type.MethodsSixteen thousand one hundred twenty-three students were included by a stratified random cluster sampling, and the number was weighted according to selection probability. Association between social environment exposure and e-cigarette use was examined by multivariate logistic regressions.ResultsThere were 35.07, 63.49, 75.19, 9.44, and 18.99% students exposed to secondhand e-cigarette aerosol (SHA), e-cigarette sales, e-cigarette information, parents' and friends' e-cigarette use. Students exposed to SHA (aOR = 1.73, 95% CI 1.40–2.14), e-cigarette sales from ≥2 sources (aOR = 1.55, 95% CI 1.18–2.03), e-cigarette information exposure from ≥2 sources (aOR = 1.39, 95% CI 1.05–1.83), and having a social e-smoking environment (friends' e-cigarette use: aOR = 2.56, 95% CI 2.07–3.16; parents' e-cigarette use: aOR = 1.54, 95% CI 1.17–2.02) were significantly associated with their intention to use e-cigarettes. More girls were exposed to e-cigarette sales in the malls, e-cigarette information at points of sale and on social media (P < 0.01), and exposure to sales from ≥2 sources were associated with girls' intention to use e-cigarettes (aOR = 1.84, 95% CI 1.22–2.78). However, boys were more likely to be exposed to friends' e-cigarette use (P < 0.001), and having friends using e-cigarettes was associated with greater intention to use them in boys (aOR = 2.64, 95% CI 1.97–3.55). Less vocational high school students were exposed to parents' e-cigarette use (P < 0.001), but they were more likely to use e-cigarettes in the future after being exposed (aOR = 2.27, 95% CI 1.50–3.43). A similar phenomenon was observed between junior high students and their exposure to SHA.ConclusionsThis study reported adolescents' high exposure rates to the social environment of e-cigarettes. Exposure to SHA, e-cigarette sales from ≥2 sources, e-cigarette information from ≥2 sources and having a social e-smoking environment were related to adolescents' intention to use e-cigarettes. Differences in gender and school type were observed. More attention should be paid to girls, and different interventions should be designed for different types of school students. Additionally, comprehensive tobacco control policies are needed.

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