[Establishment of early warning indicators of SARS-CoV-2 Omicron variant in Tianjin].

In this study, Delphi method was used to conduct a questionnaire survey on 12 experts to determine the indicators system and the corresponding weight for early warning features of SARS-CoV-2 Omicron in Tianjin.The positive indexes of experts in three rounds of consultations were both 100%. The experts' authority coefficient was 0.79. The Kendall's W coordination coefficients were 0.375, 0.356 and 0.385 respectively (all P<0.05). The indicators system for early warning features of 2019-nCoV Omicron variant had 5 first-level indicators, 10 second-level indicators and 52 third-level indicators. The weight of each indicator was also determined.

Analysis of Sentiment Tendency Based on Major Public Health Events

The outbreak of the COVID-19 has seriously affected the lives of the public. On the network platform, there has been a lot of controversy about this issue, which caused panic among the people. Accurate Sentiment propensity analysis of user statements on various platforms can better guide public opinion and avoid unnecessary panic. This paper classifies data based on the Naive Bayesian algorithm because the traditional Naive Bayesian algorithm does not consider that the feature weights of the same feature word in different classes are different when classifying. Under the strong hypothesis of independence between features, the same feature word has the same importance, which will reduce the accuracy of the classifier. Therefore, this paper uses an improved TF-IDF algorithm to weight it and performs classification experiments. The experimental results show that this model can achieve better performance in text classification. © 2022 IEEE.

[Psychological and behavioral functioning of children and adolescents during long-term home-schooling].

Objective: To study the characteristics and risk factors of psychological and behavioral problems of children and adolescents of different ages and genders in long-term home-schooling during the coronavirus disease-2019 pandemic. Further, to provide scientific basis for more targeted psychological intervention and coping strategies in the future. Methods: A cross-sectional survey using an online questionnaire was conducted on students aged 6-16 years old in five representative cities of North (Beijing), East (Shanghai), West (Chongqing), South (Guangzhou) and Middle (Wuhan) in China. In this study, the social behavior and psychological abnormalities which was defined as the positive of any dimension were investigated in multiple dimensions during long-term home-schooling. The influencing factors of psycho-behavioral problems were analyzed by Logistic regression, and the confounding factors were corrected with graded multivariable adjustment. Results: A total of 6 906 valid questionnaires were collected including 3 592 boys and 3 314 girls, of whom 3 626 were children (6-11 years old) and 3 280 were adolescents (12-16 years old). The positive detection rate of psychosocial-behavioral problems were 13.0% (900/6 906) totally, 9.6% (344/3 592) in boys and 16.8% (556/3 314) in girls respectively, and 7.3%(142/1 946) in boys aged 6-11, 14.0%(235/1 680) in girls aged 6-11, 12.3%(202/1 646) in boys aged 12-16, 19.6%(321/1 634) in girls aged 12-16 respectively. There were significant differences between the psychological problems group and the non-psychological problems group in gender, parent-offspring conflict, number of close friends, family income change, sedentary time, homework time, screen exposure time, physical activity, dietary problems (χ²=78.851, 285.264, 52.839, 26.284, 22.778, 11.024, 10.688, 36.814, 70.982, all P<0.01). The most common symptoms in boys aged 6-11 years were compulsive activity, schizoid and depression, in girls aged 6-11 years were schizoid/compulsive activity, hyperactivity and social withdrawal, in boys aged 12-16 years were hyperactivity, compulsive activity and aggressive behavior, and in girls aged 12-16 years were schizoid, anxiety/compulsive activity and depression/withdrawal, respectively. After graded multivariable adjustment, besides the common risk factors, homework time and online study time were the risk factors of 6-11 years old groups [boys OR(95%CI): 1.750 (1.32-2.32), 1.214(1.00-1.47), girls: 1.579(1.25-1.99), 1.222(1.05-1.42), all P<0.05], videogames time were the risk factors of 12-16 years old groups [ boys: 2.237 (1.60-3.13), girls: 1.272 (1.00-1.61), all P<0.05]. Conclusions: Some children and adolescents may have psychological and behavioral problems during long-term home-schooling. The psychological and behavioral manifestations differed in age and gender subgroups, which deserve special attention in each subgroups. Schools, families and specialists should actively provide precise psychological support and comprehensive intervention strategies according to special features and risk factors.