Influenza is a common childhood disease and protecting children by predicting the positive rate of influenza virus is important as vaccines are not routinely administered in China. Our study aims to describe the epidemiology of influenza viruses among children in Wuhan, China during the past nine influenza seasons (2007-2015) and to predict the positive rate of different types of influenza virus in the future. During the last nine influenza seasons (2007-2015), a total of 10,232 nasopharyngeal swabs collected from pediatric outpatients (age <15years) with influenza-like illness (ILI) infections in two sentinel children's hospitals were examined for influenza A and B by real-time one step RT-PCR. An autoregressive integrated moving average (ARIMA) model was used to fit the time series and to predict the future (first half of 2016) positive rates of different types of influenza virus. A total of 1,341 specimens were positive for influenza A and 490 for influenza B. The majority of infected patients were 1-11 years old (87.7%). The ARIMA model could effectively predict the positive rate of influenza virus in a short time. ARIMA(0,0,11), SARIMA(1,0,0)(0,1,1)12, ARIMA(0,0,1) and SARIMA(0,0,1)(1,0,1)12 were suitable for B(Victoria), B(Yamagata), A(H1N1)pdm09, and A(H3N2), respectively. Additional policies must be formulated to prevent and control influenza. The wide use of influenza vaccines, especially for influenza B, especially for influenza B(Yamagata) and B(Victoria), can potentially reduce the effects of influenza on children of China.

Objectives Chinese county hospitals have been excessively enlarging their scale during the healthcare reform since 2009. The purpose of this paper is to examine the technical efficiency and productivity of county hospitals during the reform process, and to determine whether, and how, efficiency is affected by various factors. Setting and participants 114 sample county hospitals were selected from Henan province, China, from 2010 to 2012. Outcome measures Data envelopment analysis was employed to estimate the technical and scale efficiency of sample hospitals. The Malmquist index was used to calculate productivity changes over time. Tobit regression was used to regress against 4 environmental factors and 5 institutional factors that affected the technical efficiency. Results (1) 112 (98.2%), 112 (98.2%) and 104 (91.2%) of the 114 sample hospitals ran inefficiently in 2010, 2011 and 2012, with average technical efficiency of 0.697, 0.748 and 0.790, respectively. (2) On average, during 2010–2012, productivity of sample county hospitals increased by 7.8%, which was produced by the progress in technical efficiency changes and technological changes of 0.9% and 6.8%, respectively. (3) Tobit regression analysis indicated that government subsidy, hospital size with above 618 beds and average length of stay assumed a negative sign with technical efficiency; bed occupancy rate, ratio of beds to nurses and ratio of nurses to physicians assumed a positive sign with technical efficiency. Conclusions There was considerable space for technical efficiency improvement in Henan county hospitals. During 2010–2012, sample hospitals experienced productivity progress; however, the adverse change in pure technical efficiency should be emphasised. Moreover, according to the Tobit results, policy interventions that strictly supervise hospital bed scale, shorten the average length of stay and coordinate the proportion among physicians, nurses and beds, would benefit hospital efficiency.

Objectives. Infectious disease knowledge and behaviors are key elements that ensure student health and safety. This study explores the impact of health education on student knowledge and behaviors toward infectious diseases and determines the factors affecting infectious diseases knowledge and behaviors among students in Gansu, China. Methods. A cross-sectional study and three sampling methods were used in two counties, 12 schools, and 32 classes in Gansu, China, from 2012 to 2013. Collected data included the following: (1) sociodemographic characteristics of 2002 students (1001 participants in the intervention group and 1001 in the control group); (2) accuracy of student knowledge and behaviors toward infectious diseases based on comparison of intervention and control groups through X2 test; and (3) mean scores on knowledge and behavior of students with different characteristics toward infectious diseases, as analyzed through analysis of variance (ANOVA). Multiple linear regression was conducted to analyze factors affecting student knowledge and behaviors toward infectious diseases. Results. Statistically significant differences were observed among eight items of infectious disease transmission and treatment knowledge between intervention and control groups (P<0.001). Average accuracies of knowledge and behaviors toward infectious diseases reached 72.23% and 60.03%. Significant differences were observed in six items on student behavior in rural and urban areas (P<0.001). Health education, household register, and county affected scores of student knowledge and behaviors toward infectious diseases (P<0.05). Gender and education level also affected scores of student behaviors toward infectious diseases (P<0.001). Conclusions. Health education contributes to student knowledge and behaviors toward infectious diseases. Students in the control group need intensified health education on infectious diseases. Health education needs to pay particular attention to rural students, all male students, and students at senior high school level living on campus.

Background: Elevated triglyceride (TG) levels are a biomarker for cardiovascular disease (CVD) risk. The correlation between serum uric acid (SUA) and TG concentrations in adults or obese children is well established. However, studies on SUA and TG in children with short stature are limited. Aim: To determine the relationship between SUA and TG levels in short children and adolescents. Method: This was a cross-sectional evaluation of a cohort of 1095 patients with short stature (720 males and 375 females). The related clinical characteristics, including anthropometric and biochemical parameters, were determined. Results: Smooth curve fitting, adjusted for potential confounders was performed, which indicated the existence of a non-linear relationship between these measures. Piecewise multivariate linear analysis revealed a significant positive relationship between SUA and TG at SUA concentrations over 7 mg/dL (β = 0.13, 95% CI: 0.05–0.22, P = 0.002) but no significant correlation at lower SUA levels (β = 0.01, 95% CI: 0.01–0.04, P = 0.799). Furthermore, a stratified analysis was performed to appraise changes in this relationship for different sexes and standard deviation levels of body mass index (BMI). The non-linear relationship remained consistent in males and females with BMI standard deviation scores (BMI SDS) ≥ 0, with inflection points of 6.71 mg/dL and 3.93 mg/dL, respectively. Within these two groups, SUA and TG levels showed a positive association when SUA levels were higher than the inflection point (β = 0.21, 95% CI: 0.11–0.31, P < 0.001 for males and β = 0.1, 95% CI: 0.03–0.17, P = 0.005 for females). However, a specific relationship was not observed at lower SUA levels. No significant relationships were found between SUA and TG levels in males and females with BMI SDS < 0. Conclusion: The present study identified the non-linear association of SUA and TG levels with short children and adolescents. This relationship was based on BMI status. This finding suggests that health status should be considered for short stature children with high SUA levels, especially in children with a high BMI standard deviation score.

Objective Township hospitals (THs) are important components of the three-tier rural healthcare system of China. However, the efficiency and productivity of THs have been questioned since the healthcare reform was implemented in 2009. The objective of this study is to analyse the efficiency and productivity changes in THs before and after the reform process. Setting and participants A total of 48 sample THs were selected from the Xiaogan Prefecture in Hubei Province from 2008 to 2014. Outcome measures First, bootstrapping data envelopment analysis (DEA) was performed to estimate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of the sample THs during the period. Second, the bootstrapping Malmquist productivity index was used to calculate the productivity changes over time. Results The average TE, PTE and SE of the sample THs over the 7-year period were 0.5147, 0.6373 and 0.7080, respectively. The average TE and PTE increased from 2008 to 2012 but declined considerably after 2012. In general, the sample THs experienced a negative shift in productivity from 2008 to 2014. The negative change was 2.14%, which was attributed to a 23.89% decrease in technological changes (TC). The sample THs experienced a positive productivity shift from 2008 to 2012 but experienced deterioration from 2012 to 2014. Conclusions There was considerable space for TE improvement in the sample THs since the average TE was relatively low. From 2008 to 2014, the sample THs experienced a decrease in productivity, and the adverse alteration in TC should be emphasised. In the context of healthcare reform, the factors that influence TE and productivity of THs are complex. Results suggest that numerous quantitative and qualitative studies are necessary to explore the reasons for the changes in TE and productivity.

The current wave and future trend of the novel coronavirus disease 2019 (COVID-19) has triggered public uncertainty, causing unbearable psychological pressure on people. A cross-sectional online questionnaire was conducted among back-to-school students in Wuhan from 31 August 2020, to 14 September 2020, by using convenience sampling. A total of 1017 participants voluntarily provided sociodemographic characteristics and accomplished the following scales: the Intolerance of Uncertainty Scale (IUS-12), the Social Support Scale (SSQ), the Generalized Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), and the Insomnia Severity Index-7 (ISI-7). Results revealed that the levels of anxiety, depression, and insomnia were moderate, moderate and subthreshold, respectively. A one-way multivariate analysis of variance indicated that those with different attitudes toward the trajectory of the COVID-19 epidemic in China showed significantly different results in anxiety and depression (p < 0.001). Moderation modeling implicated that social support significantly moderated the predictive relationship between intolerance of uncertainty and mental health variables including anxiety and depression, but failed on insomnia. Findings indicate that back-to-school students in Wuhan experience mental health problems and improving social support measures could buffer the effect of intolerance of uncertainty with respect to COVID-19 on mental health.