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Background: The purpose of this paper is to study how the Delta variant spread in a China city, and to what extent the non-pharmaceutical prevention measures of local government be effective by reviewing the contact network of COVID-19 cases in Xi'an, China. Methods: We organize the case reports of the Shaanxi Health Commission into a database by text coding and convert them into a network matrix. Then we construct a dynamic contact network for the corresponding analysis and calculate network indicators. we analyze the cases' dynamic contact network structure and intervals between diagnosis time and isolation time by using data visualization, network analysis method, and Ordinary Least Square (OLS) regression. Results: The contact network for this outbreak in Xi'an is very sparse, with a density of less than 0.0001. The contact network is a scale-free network. The average degree centrality is 0.741 and the average PageRank score is 0.0005. The network generated from a single source of infection contains 1371 components. We construct three variables of intervals and analyze the trend of intervals during the outbreak. The mean interval (interval 1) between case diagnosis time and isolation time is − 3.9 days. The mean of the interval (interval 2) between the infector's diagnosis time and the infectee's diagnosis time is 4.2 days. The mean of the interval (interval 3) between infector isolation time and infectee isolation time is 2.9 days. Among the three intervals, only interval 1 has a significant positive correlation with degree centrality. Conclusions: By integrating COVID-19 case reports of a Chinese city, we construct a contact network to analyze the dispersion of the outbreak. The network is a scale-free network with multiple hidden pathways that are not detected. The intervals of patients in this outbreak decreased compared to the beginning of the outbreak in 2020. City lockdown has a significant effect on the intervals that can affect patients' network centrality. Our study highlights the value of case report text. By linking different reports, we can quickly analyze the spread of the epidemic in an urban area. [ABSTRACT FROM AUTHOR]

Background: The outbreak of Coronavirus Disease is causing considerable acute risk to public health and might also have an unanticipated impact on the mental health of children and adolescents in the long run. This study collected data during the national lockdown period in China and aims to understand whether there is a clinically significant difference in anxiety, depression, and parental rearing style when comparing adolescents from Wuhan and other cities in China. This study also intends to examine whether gender, grade in school, single child status, online learning participation, parents' involvement in COVID-19 related work, and parents being quarantined or infected due to the disease would lead to clinically significant differences in anxiety and depression. Beyond that, this study explored the pathways among the different variables in order to better understand how these factors play a part in impacting adolescents' mental health condition.Results: Results showed that there was a statistically significant difference in anxiety symptoms between participants who were from Wuhan compared to other urban areas, but not in depressive symptoms. In addition, participants' grade level, gender, relative being infected, and study online have direct positive predictive value for depressive and anxiety symptoms, whereas location and sibling status have indirect predictive value. Having relatives who participated in COVID-19 related work only had positive direct predictive value toward depression, but not anxiety.Conclusions: This study discovered several risk factors for adolescents' depression and anxiety during the pandemic. It also called for a greater awareness of Wuhan parents' mental wellbeing and recommended a systematic approach for mental health prevention and intervention. [ABSTRACT FROM AUTHOR]