Psychological state and its correlates of local college students in Wuhan during COVID-19 pandemic.

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.

Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan.

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.