Background Patient-reported outcomes (PROs) are essential for assessing symptomatic adverse events (AEs) from a patient perspective, which significantly impact the quality of life and clinical outcomes in patients with glioma. However, no validated patient-reported outcome measures (PROMs) exist to quantify symptomatic AEs in adult-type diffuse gliomas. Methods The study was conducted in two parts. First, we developed a customised Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) scale for adult-type diffuse gliomas using the Simplified Chinese PRO-CTCAE® item library, informed by initial item screening, patient pilot testing, and a two-round Delphi survey. Delphi experts were recruited through the National Glioma Multidisciplinary Team (MDT) Alliance (NGMA) and invited by email in June 2022 (1st round) and August 2022 (2nd round). We subsequently conducted a multicentre, prospective, observational cohort study (VERONICA) at 13 glioma treatment centres in China between September 2022 and March 2025. Eligible participants were adults aged 18 years or older with a diagnosis of adult-type diffuse glioma, who were able to understand and complete the questionnaires; patients with severe cognitive impairment, severe language dysfunction, or other conditions precluding questionnaire completion were excluded. The primary outcome was the psychometric performance of the customised PRO-CTCAE scale, including test-retest reliability, convergent validity, known-groups validity, and responsiveness, evaluated longitudinally across repeated study visits. VERONICA is registered with ClinicalTrials.gov, NCT05486923. Findings For the Delphi survey, all seven invited experts from six centres participated in 1st round (response rate 100·0%), with moderate agreement in symptom rankings (Kendall's W = 0·415; p < 0·001). In 2nd round, 16 of 20 invited experts from 14 centres participated (response rate 80·0%), with consistent agreement in expert ratings (Kendall's W = 0·351; p < 0·001). The final version of the customised PRO-CTCAE scale comprised 53 items covering 31 symptoms, together with one open-ended free-text item. For VERONICA, 450 participants were enrolled across 13 glioma treatment centres. Mean age was 49·1 years (SD 12·8), and the mean Karnofsky Performance Status (KPS) at baseline (Visit 2) was 72·2 (SD 17·1). 424 provided data eligible for at least one prespecified psychometric analysis. Test-retest reliability was acceptable (intraclass correlation coefficient [ICC] ≥0·70 for 47 of 53 items). Convergent validity was supported by correlations in the expected direction with matched European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) domains, with predominantly moderate-to-strong associations (25 items with r ≥ 0·50). Known-groups validity was supported by discrimination between KPS <70 and ≥70 (Cohen's d ≥ 0·20 for 49 of 53 items; p < 0·05 for 43 of 49 items). In Global Impression of Change (GIC)-anchored responsiveness analyses, 37 items showed standardised response means (SRMs) ≥0·20 among participants reporting worsened overall status. Interpretation The customised PRO-CTCAE scale showed robust psychometric performance for adult-type diffuse gliomas. Remote, longitudinal administration supports low-burden quantification of patient-reported symptomatic AEs in clinical trials and routine neuro-oncology practice. Future work should assess implementation in routine care and clinical trials, and extend translation, cultural adaptation, and validation across different languages. Funding Beijing Medical Award Foundation; Shanghai Municipal Health Commission; Department of Science and Technology of Ningxia Hui Autonomous Region; Huashan Hospital, Fudan University (Clinical Research Project).

Background Rotavirus is a principal etiological agent of severe acute gastroenteritis in young children, for which vaccination constitutes the cornerstone of prophylactic intervention. However, to our knowledge, few studies have comprehensively assessed the differential population impacts of alternative rotavirus vaccination strategies within China. This study was therefore conducted to quantify the effect of vaccination on the epidemiological dynamics of rotavirus-associated gastroenteritis in Shanghai. Methods An age-structured Susceptible-Infected-Recovered-Susceptible (SIRS-type) compartmental model incorporating the effects of vaccine interventions was developed. Epidemiological data on reported cases were sourced from the infectious disease surveillance system. Scenario-based simulations were employed to evaluate vaccine efficacy and the prospective outcomes of strategic adjustments to the vaccination program. Results The model demonstrated a high degree of fit with observed epidemiological data over the calibration period from July 2015 to April 2024 (R2 = 0.747, RMSE = 58.55 cases/month; LOO R2 = 0.423). The implementation of the RotaTeq vaccination program resulted in an estimated cumulative reduction of 20.0% (95% CI: 18.9–21.6%) in the whole population and 24.6% (95% CI: 23.0–26.5%) among children under 5 years, relative to a no-RotaTeq counterfactual. Simulations indicated that optimizing the vaccination schedule of the Lanzhou lamb rotavirus vaccine (LLR) and augmenting coverage rates are effective strategies for outbreak mitigation. The introduction of Lanzhou lamb reassortant rotavirus vaccine, live, oral, trivalent (LLR3) and oral hexavalent reassortant rotavirus vaccine (WH-HRV) would further reduce the disease burden across all age groups, potentially controlling the epidemic to a minimal endemic level post-2029. Conclusions The incidence of rotavirus-associated gastroenteritis in Shanghai exhibited a discernible downward trend between 2015 and 2024, a decline associated with substantial contribution from the introduction of the RotaTeq vaccine. The optimization of existing vaccination protocols, in conjunction with the deployment of novel vaccines, is anticipated to be crucial for achieving more comprehensive and sustained control of rotavirus transmission in Shanghai.

BACKGROUND:Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory tract infections (ALRIs) in children. To guide policymaking on controlling RSV-associated ALRIs (RSV-ALRIs) in China, we estimated the national, regional, and provincial burdens of RSV-ALRIs and associated hospitalizations for children under 5 years old. METHODS:We systematically identified publications about RSV-ALRIs in China with epidemiological data before 2020. We compared seasonality data from this period with data during the COVID-19 epidemic. We built a dataset to assess RSV-ALRI burden by age and region, using a generalized linear mixed-effects model and a conceptual proportionality framework to assess hospitalization rates. A risk factor-based model were used to estimate regional and provincial RSV-ALRI incidence. FINDINGS:Children aged 0 to 12 months had the highest risk of RSV-ALRI and associated hospitalization. Provincial variations existed, with some southern provinces exhibiting higher incidence and some western provinces higher hospitalization rates. The COVID-19 epidemic shifted RSV hospitalization peaks to early autumn (Guangdong, Shanghai), whereas Hubei and Shandong demonstrated delayed peak onset compared with the pre-pandemic period. INTERPRETATION:Our study of the burden RSV-ALRIs in China identified obvious heterogeneity by age and region. These findings highlight the need for targeted RSV vaccination strategies and resource allocation prioritizing high-risk groups and areas. FUNDING:This work was supported by the Shanghai Municipal Science and Technology Major Project (Grant No. ZD2021CY001), the National Natural Science Foundation of China (Grant No. 82073612), and Shanghai New Three-year Action Plan for Public Health (GWVI-1, GWVI-11.1-03 and GWVI-11.1-01).

BACKGROUND:Understanding how respiratory infectious diseases spread across cities of different socioeconomic tiers is crucial for regionally targeted interventions. However, most spatial prediction frameworks neglect the combined influence of urban hierarchy and human mobility in shaping transmission risk. METHODS AND FINDINGS:We integrated large-scale intercity mobility data into an agent-based branching process model to simulate the spatial diffusion of respiratory pathogens across mainland China. Three COVID-19 outbreaks were used for validation: the Omicron outbreak in Shanghai, the Delta outbreak in Nanjing, and a multi-provincial Delta outbreak in northwestern China. We applied the framework to model the spread of SARS-CoV-2 (Omicron variant) and Influenza A to quantify tier-specific transmission risks. Tiers denote a hierarchical classification of Chinese cities based on concentration of commercial resources, transportation hub centrality, etc., ranging from super-tier metropolises to lower-tier cities. Predicted first arrival times showed strong agreement with observed data (r = 0.68 and 0.76), and mobility-based predictions more accurately identified outbreak origins than distance-based approaches. Markedly different tier-dependent diffusion patterns were observed across pathogens. Influenza A exhibited stable and stratified diffusion, with transmission confined mainly within the same or adjacent urban tiers and limited cross-tier seeding. In contrast, SARS-CoV-2 (Omicron) initially concentrated in super-tier and tier-1 cities but rapidly spread to lower-tier cities, producing a pronounced hierarchical pattern of spread that quickly diminished tier-level differences in transmission risk. Across pathogens, higher-tier cities consistently faced greater early importation risk; however, this disparity persisted for Influenza A but was rapidly attenuated for Omicron due to its high transmissibility and fast spatial expansion. A key limitation is that the model was validated against city-level first arrival times rather than full epidemic dynamics, and was parameterised using mobility data from China's "dynamic zero-COVID" period, which may limit direct quantitative generalisability to other settings. CONCLUSIONS:Spatial transmission risk reflects an interaction between pathogen-specific transmissibility and the hierarchical organisation of China's urban mobility system. These findings indicate that surveillance and response strategies effective for less transmissible pathogens may be insufficient for highly transmissible variants. Mobility-informed, tier-specific risk assessment may help inform early warning and support more adaptive public health responses. Because the framework relies on routinely available mobility data and minimal pathogen-specific inputs, it may provide a scalable approach for epidemic preparedness, including potential future emerging respiratory threats (Disease X).

Influenza-like illness (ILI) and severe acute respiratory infection (SARI) remain significant public health burdens, particularly among older adults and in resource-limited settings. However, long-term epidemiologic trends across different pandemic phases remain poorly understood, especially for vulnerable populations. Surveillance and hospital records collected between 2017 and 2024 from two sentinel hospitals in Shanghai, China, were analyzed. Interrupted time-series (ITS) models were used to evaluate temporal changes in ILI and SARI incidence. Large-scale data processing techniques were applied to extract structured information from unstructured medical records, enabling comprehensive analysis of clinical characteristics and outcomes. Both ILI and SARI cases declined sharply during the COVID-19 pandemic but rebounded thereafter. Older adults (≥60 years) experienced disproportionately greater increases in these cases, along with higher risks of ILI-to-SARI progression and ICU admission. Although clinical recovery rates improved in the post-pandemic period, the demand for oxygen therapy and hospital-based care remained elevated. These findings highlight the long-term impact of the COVID-19 pandemic on respiratory infection dynamics and underscore the need for targeted interventions for older adults. Despite highest susceptibility and baseline risk for severe illness, older adults demonstrated improved post-pandemic clinical outcomes due to enhanced clinical prioritization. Strengthening vaccination programs, improving health education, and enhancing resource preparedness are crucial to reduce the post-pandemic disease burden, particularly in settings with limited healthcare capacity. These findings provide important evidence to strengthen post-pandemic respiratory surveillance and improve protection strategies for older adults in China.

Quantifying transmission distance helps to understand infectious disease spread patterns, but few studies have assessed this for (re-)emerging respiratory infectious diseases. The COVID-19 pandemic's extensive surveillance and high-quality data in China offer a strong model for studying the spread pattern of respiratory infections. We collected COVID-19 outbreak data from June 2020 to December 2022 in mainland China to estimate transmission distances, examine the association between urban characteristics and transmission distance, and explore its implications in outbreak response. The mean transmission distance of all outbreaks was 18.94 km. This distance varied by SARS-CoV-2 variants, with wild-type outbreaks showing shortest transmission distance (3.08 km) and Omicron outbreaks showing longest transmission distance (20.17 km). Transmission distance was positively associated with city size and total length of roads. Potential transmission areas identified as areas within transmission distance of the first 100 cases contained 63.84–99.61% of cases. Providing testing services to residents in these areas helped to control the outbreak. Our results suggest that transmission distances can help predict where emerging respiratory infectious diseases may spread next spatially and guide the implementation of targeted interventions.

Patient complaints are crucial for improving the service quality of hospitals and healthcare professionals as well as enhancing patient satisfaction. The 12320 and 12345 hotlines in Shanghai are key platforms for receiving public health complaints. Understanding the temporal and spatial changes in the growth rate of patient complaints in Shanghai is essential for resource allocation and service quality improvement. This retrospective study investigated the spatial distribution characteristics of the growth rate of patient complaints in Shanghai’s sub-districts from 2015 to 2022, involving a total of 326,147 patient complaint cases. We used ArcGIS 10.2 to analyze the annual trends in complaint volume, perform spatial autocorrelation analysis, hot-spot analysis (Getis-Ord Gi*), and content analysis based on the Healthcare Complaint Analysis Tool (HCTA). The volume of patient complaints showed a continuous upward trend from 2015 to 2022. The Moran’s Index for the two periods of 2015–2019 and 2015–2022 was 0.020 (P = 0.036) and 0.045 (P = 0.001), respectively. Patient complaints exhibited strong spatial clustering effects in certain street areas, particularly in the western suburbs, where the growth rate of complaints was more severe than in central urban areas. The top three types of complaints in focus areas in 2022 were environment, safety, and institutional processes, accounting for 45.93

[Objective]To analyze the hygienic status of tableware cleaning and disinfection in 41 catering facilities of Shanghai in 2020,to identify its influencing factors,so as to propose evidence-based improvements for future scientific supervision.[Methods]A field survey was conducted on the cleaning and disinfection methods of tableware in 41 catering establishments in Shanghai.A total of 180 tableware samples were collected and tested for four indicators,including free residual chlorine,anionic synthetic detergent residues,coliforms,and total number of bacterial colonies.The results were classified and statistically analyzed based on the type of catering establishment,tableware material,tableware function,and cleaning and disinfection methods.[Results]The tableware passed the tests for coliforms and free residual chlorine.The qualification rate for anionic synthetic detergent residues was 48.89%(88/180),with an average of 0.02 mg per 100 cm2 and a maximum of 0.25 mg per 100 cm2(This unit complied with the requirements of national standardard:GB 14934-2016).Based on the type of catering enterprises,large restaurants had the lowest qualification rate for anionic synthetic detergent residues in tableware at 46.15%.In terms of the function of tableware,chopsticks had the lowest qualification rate for anionic synthetic detergent residues at 26.32%.The detection rate of total number of bacterial colonies in tableware was 42.22%(76/180),with an average of 0.5 log10(CFU·mL-1)and a maximum of 3.4 log10(CFU·mL-1).Among them,medium-sized restaurants had the highest detection rate of total number of bacterial colonies in tableware at 47.73%(21/44).[Conclusion]The qualification rate of anionic synthetic detergent residues in tableware is relatively low.It is recommended to strengthen research on the occurrence patterns of unqualified tableware and establish early warning values for the qualification rate of anionic synthetic detergent residues,enhance law enforcement inspections on relevant catering establishments,guide enterprises to fulfill their main responsibilities,and improve the quality and safety of tableware.

Background: Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, with growing evidence linking risk to lifestyle and dietary factors. However, nutrition-related exposures have rarely been integrated into existing CRC risk prediction models. This study aimed to develop and validate a lifestyle-based 10-year CRC risk prediction model using longitudinal data from a large-scale population-based screening cohort to facilitate early risk stratification and personalized screening strategies. Methods: Data were obtained from 21,358 individuals participating in a CRC screening program in Shanghai, China, with over 10 years of active follow-up until 30 June 2021. Of these participants, 16,782 aged ≥40 years were used for model development, and 4576 for external validation. Predictors were selected using random survival forest (RSF) and elastic net methods, and the final model was developed using Cox regression. Machine learning approaches (RSF and XGBoost) were additionally applied for performance comparison. Model performance was evaluated through discrimination, calibration, and decision curve analysis (DCA). Results: The final model incorporated twelve predictors: age, gender, family history of CRC, diabetes, fecal immunochemical test (FIT) results, and seven lifestyle-related factors (smoking, alcohol use, body shape, red meat intake, fried food intake, pickled food intake, and fruit and vegetable intake). Compared to the baseline demographic-only model (C-index = 0.622; 95% CI: 0.589-0.657), the addition of FIT improved discrimination, and further inclusion of dietary and lifestyle variables significantly enhanced the model's predictive accuracy (C-index = 0.718; 95% CI: 0.682-0.762; ΔC-index = 0.096, p = 0.003). Conclusions: Incorporating dietary and lifestyle variables improved CRC risk stratification. These findings highlight the value of dietary factors in informing personalized screening decisions and providing an evidence-based foundation for targeted preventive interventions.

Background:Since varicella is already known to be a globally distributed disease, the focus should be more on its transmissibility or disease burden. The incidence of varicella is affected by natural and socio-economic factors. However, it is unclear how these factors synergetically impact the dynamics of varicella transmission and control. Methods:We conducted a retrospective analysis of varicella cases in children aged 0-17 years from 2013 to 2022 in Jiading District, Shanghai, China. First, we evaluated demographic characteristics, epidemiological trends of varicella. And then, we explored the impact of two-dose varicella vaccine (VarV) program on varicella incidence using interrupted time-series analyses, and assessed the influence of natural and socio-economic factors using principal component analysis and multivariate regression. Spatial analysis was conducted to compare varicella epidemiology. Results:Our analysis includes 6,482 reported varicella cases, with a higher incidence observed among males (58.67%). Regional differences were noted, with the highest incidence in the western region and the lowest in the central region. Before the implementation of the two-dose VarV program, varicella incidence increased by 0.28 cases per 100,000 per month. Following the two-dose VarV program's introduction, the incidence rate decreased by 0.49 cases per 100,000 per month, with an impressive 79.10% reduction in the annual average incidence among children aged 4-6 years. By analyzing the impact of demographic characteristics, healthcare capacity, economic level, air pollutants, and meteorological factors on the incidence of varicella, we found that the child population ratio and VarV program were most strongly associated with varicella incidence. Conclusion:The study underscores the importance of sustained monitoring of child population ratio and VarV program to reduce varicella transmission and protect vulnerable groups.

BACKGROUND:It is evident that respiratory viruses exhibit a discernible spatial and temporal transmission pattern, and severe acute respiratory syndrome (SARS-CoV-2) has profoundly altered the dynamics of these pathogens. The viral interference has led to greater complexity in the surveillance. This study aims to examine the spatiotemporal transmission patterns of respiratory viruses in the post-pandemic era and assess the impact of virus interactions on virus outbreaks. METHODS:A multi-pathogen surveillance program was conducted in Taizhou, Zhejiang Province, commencing in 2021. The study utilized spatial-temporal modeling to analyze four respiratory viruses, namely SARS-CoV-2, influenza, human rhinovirus (HRV) and respiratory syncytial virus (RSV), with the objective of identifying interaction patterns and their lagged effects. RESULTS:Each virus is influenced to varying degrees by economic and traffic-related factors. Even after adjusting for spatiotemporal variables and baseline factors, significant interactions were observed between different viruses. These interactions were not always bidirectional and demonstrated specific patterns and lag times. RSV outbreaks are influenced by HRV, but the converse is not true. The effect of SARS-CoV-2 on influenza manifested 12 weeks later, whereas influenza affected SARS-CoV-2 with only 1-week lag. Potential competitive relationships between viruses were also evident in their spatial distribution, such as the nearly opposite high- and low-prevalence areas of influenza and HRV. Furthermore, the coexistence of multiple pathogens resulted in substantial alterations to virus diffusion patterns and epidemic duration. CONCLUSIONS:This study integrates multi-pathogen surveillance with spatiotemporal modeling, confirming that the viral interference relationships derived from population-level incidence data are consistent with experimental findings, thereby revealing potential interactions between SARS-CoV-2 and other viruses. Our findings confirm that SARS-CoV-2 has altered transmission patterns of respiratory viruses and highlight the critical role of viral interactions in shaping epidemic dynamics.

IntroductionInfectious diarrhea, as one of the oldest infectious diseases, has been fought against by people for hundreds of years. From changing lifestyle habits to developing new drugs, people have been tirelessly searching for ways to reduce the burden of diarrhea. This study evaluated the impact of cockroach control intervention on infectious diarrhea from the perspective of public health and explored influencing factors, providing practical suggestions for implementation in various regions.Methods2,471 positive cases of diarrhea and 14,788 outpatient visits were included for analysis. Using the annual cockroach control intervention as the interruption time point, we observed the number of cases and visits for 12 months before and after, established interruption time series to evaluate the impact of cockroach control intervention on diarrhea in the population, and used hypothesis test to determine potential influencing factors.ResultsConducting an annual cockroach control intervention in Shanghai Songjiang District help reduce the number of diarrhea cases by 23.58% and the number of outpatient visits by 10.12% in the following year on average from 2020 to 2022. The temperature during the intervention in June 2022 showed a significant increase compared to 2020 and 2021; The effectiveness of cockroach control interventions was almost entirely reflected in Blattella germanica, while Periplaneta Americana were not affected.ConclusionUnder the combination of local natural conditions and comprehensive prevention measures, regular cockroach control interventions have a promising supporting effect on reducing the disease burden of diarrhea in the population and a certain effect on reducing the symptom burden. However, the intervention effect is affected by numerous factors such as temperature and cockroach species. If local baseline data can be consulted before intervention to select targeted intervention time and prevention methods, it is easier to achieve ideal results.

Background and objective Lung cancer is one of the malignant cancers with the highest incidence rate, and it is important to identify the factors contributing to lung cancer carcinogenesis for prevention. Lifestyle and genetic factors play important roles in cancer development, however the impact of dietary factors, such as soy product intake, on lung cancer risk remains inadequately understood. This study aims to explore the associations between soy product intake, genetic risk, and lung cancer incidence, and validate the consistent effects of soy product intake in European populations, thereby providing new insights for lung cancer prevention. Methods Utilizing the Shanghai Suburban Adult Cohort and Biobank (SSACB) (n=66,311), Cox proportional hazards model was adopted to assess the association between soy product intake and lung cancer incidents, followed by subgroup analyses stratified by gender, smoking status, and pathological types of lung cancer. The UK Biobank (UKB) was used for validation of the effect of soy product intake on lung cancer. To investigate the association between genetic factors and lung cancer, in addition to previously reported loci, we incorporated newly identified loci from two independent studies in Southeast China: a nested case-control population from the SSACB cohort (433 cases/650 controls) and a case-control study from the Shanghai Cancer Center-Taizhou cohort (1359 cases/1359 controls). Meta-analysis and Linkage disequilibrium clumping (LD clumping) of the association results identified 23 loci for polygenic risk score (PRS) construction. Subsequently, conditional Logistic regression model was used to assess the association between genetic risk and lung cancer. Results In SSACB cohort, after adjusting for age, gender, smoking, chronic bronchitis, body mass index (BMI), vegetable intake and red meat intake, sufficient soy product intake was significantly associated with a reduced risk of lung cancer [hazard ratio (HR)=0.60, 95%CI: 0.47-0.77, Padj=6.69E-05], an effect that was consistent in males and females, smokers and non-smokers. In UKB, although the association did not reach statistical significance, a protective trend against lung cancer was also observed (HR=0.76, 95%CI: 0.55-1.06, Padj=0.10). In the nested case-control population within SSACB, a PRS score generated in the Chinese population was significantly correlated with lung cancer risk. After adjustment of age, gender, smoking, chronic bronchitis, and soy product intake, the high-PRS group had a 1.88 times higher risk of lung cancer compared to the low-PRS group (Padj=1.84E-03). Conclusion The prospective cohort study found that adequate intake of soy products was significantly associated with a reduced risk of lung cancer, while a high PRS is a risk factor for lung cancer development. Integrating soy product intake and PRS into traditional epidemiological risk factor prediction will guide personalized lung cancer prevention and high-risk population stratification.

Specific high-risk subgroups of men who have sex with men (MSM) play crucial roles in sexually transmitted infection (STI) transmission. This study investigated temporal trends in sexual behaviors and associated factors among bisexual MSM, active MSM, and active MSM in bisexuality. From 2010 to 2023, MSM were recruited in Zhejiang, China, through multiple strategies, including community popular opinion leader (CPOL) outreach, venue-based sampling (VBS), HIV voluntary counseling and testing (VCT) clinics, and online platforms. MSM who reported anal sex in the past six months and completed a standardized survey were classified into three high-risk subgroups. We used chi-square trend tests and weighted multivariable logistic regression analyses to assess temporal trends and associated factors. Additionally, SHapley Additive exPlanations (SHAPs) were applied to evaluate the relative importance of predictors. Among the 4197 MSM, 2709 were classified as high-risk, with the proportions of the three high-risk subgroups showing gradual declines but remaining above 20

BACKGROUND:COVID-19 pandemics have greatly impacted the epidemiology of seasonal influenza, presenting a challenge for postpandemic prediction and prevention and control of influenza. This study aimed to gain a deeper understanding of future influenza patterns. METHODS:We collected data from eight regions around the world. Using SVIRS model, we identified a clear change during and after the COVID-19 era. Linear regression modelling showed the relationship between influenza, COVID-19 and PHSMs. Finally, we conducted a simulation to assess the impact of implementing simple PHSMs at the end of the COVID-19 outbreak. RESULTS:In all regions except Tokyo, there were off-season influenza outbreaks. The levels of influenza outbreaks were found to be higher than simulated. In California, the peak was 8.5 times higher than the simulated value (95% CI: 1.00, 8.65). In every region, the peaks of influenza outbreaks closely followed those of the COVID-19 pandemic. The results of linear regression indicated that the influenza outbreaks were significantly correlated with that of COVID-19 and existing seasonality (P-value < 0.05). Finally, we conducted a simulation to assess the impact of implementing PHSMs at the end of the COVID-19 outbreak. Reducing the reproduction number of influenza to 95% of its original value could result in a 50% decrease in the peak. CONCLUSION:This study highlights the impact of the COVID-19 pandemic on influenza, raises the possibility of incorporating the observed trends in the incidence of COVID-19 into influenza prediction models, and suggests the implementation of collaborative surveillance to mitigate the risk of influenza outbreaks.

The incidence of depression among adolescents has risen significantly over the past decade. Emotional dynamics, including variability, instability, and inertia of positive affect (PA) and negative affect (NA), are potential risk factors for depressive psychopathology. However, limited longitudinal evidence exists on how these emotion dynamics relate to depression, particularly in collectivistic cultural contexts, where emotional expression and regulation are shaped by social and familial expectations. This study aimed to investigate the longitudinal associations between emotion dynamics—variability, instability, and inertia of PA and NA—and subsequent depressive symptoms among Chinese adolescents. Data were collected from middle school students in Taizhou, China, between November 2021 and April 2022. Participants completed baseline surveys and experience sampling assessments, reporting their emotional states ten times daily over five consecutive weekdays. Depressive symptoms were assessed using the Children’s Depression Inventory (CDI), while emotional dynamics (variability, instability, and inertia) were derived from the experience sampling data. Logistic regression models were employed to examine whether emotion dynamics predicted depressive symptoms at 1-month and 3-month follow-ups. A total of 448 participants completed all study procedures and were included in the analysis. Emotional variability and instability in PA and NA were longitudinally associated with depressive symptoms at both 1-month and 3-month follow-ups. After controlling for mean affect levels, PA variability and instability, but not NA, were uniquely linked to depressive symptoms. Emotional inertia showed no significant association with subsequent depressive symptoms. Emotional variability and instability in PA and NA also predicted the development of new symptoms in adolescents without baseline depression (n = 372). Emotional variability and instability of PA and NA were longitudinally associated with changes in depressive symptoms and the development of new symptoms among adolescents. These emotion dynamics provide insights into real-world emotional processing and offer important targets for adolescent depression interventions.

Background: COVID-19 threatened global health, however little is known about the long-term courses of loneliness and their effect on mental health in adolescents. This study aimed to explore the trajectories of loneliness among adolescents in Taizhou, Zhejiang Province, China, during the last phase of the pandemic. We also aimed to identify risk factors in each loneliness course and the impact of loneliness on emotional problems, peer problems, hyperactivity and conduct problems. Methods: The study employed multistage cluster sampling to collect four waves of data from 2347 Chinese adolescents (average baseline age of 14.7 years) covering a period of 20 months (October 2021 - May 2023). The UCLA 3-Item Loneliness Scale and the Strengths and Difficulties Questionnaire were utilized to assess loneliness and mental health problems, respectively. Growth mixture modelling was employed to identify latent classes of loneliness trajectories. Associated risk factors were investigated using multinomial logistic regression model. Mixed-effects logistic regression models were constructed to examine the long-term impact of loneliness classes on mental health outcomes. Results: The overall percentage of loneliness increased from 22.9% at baseline to 32.2% at the fourth wave in our sample. Three classes of loneliness were identified: Decreasing Low Loneliness (58.71%), Increasing Medium Loneliness (36.52%), and Increasing High Loneliness (4.77%). Risk factors for poorer loneliness trajectories included lack of physical exercise habits, poorer mental health literacy, medium or low perceived social support, having study difficulties, being female, higher grades, and lower economic status. Loneliness classes were associated with the severity and variability of emotional problems, peer problems, hyperactivity and conduct problems (ORs for the highest loneliness class: 10.24, 4.21, 3.87, 2.68, respectively). Individuals in the higher loneliness classes experienced a significant increase in these mental health problems over time (p < 0.05 for interactions between loneliness classes and time). Conclusion: During the last phase of the pandemic, a large proportion of adolescents in our study endured medium to high levels of loneliness with no signs of improvement. Both unfavorable loneliness trajectories adversely affected internalizing and externalizing problems and displayed an upward trend in these difficulties. Results highlight the importance of tackling loneliness and improving mental health in adolescents.

The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has been becoming one of the most important public health issues worldwide. Previous studies have shown the importance of weather variables and air pollution in the transmission or prognosis of infectious diseases, including, but not limited to, influenza and severe acute respiratory syndrome (SARS). In the early stage of the COVID-19 epidemic, there was intense debate and inconsistent results on whether environmental factors were associated with the spread and prognosis of COVID-19. Therefore, our team conducted a series studies to explore the associations between atmospheric parameters (temperature, humidity, UV radiation, particulate matters and nitrogen dioxygen) and the COVID-19 (transmission ability and prognosis) at the early stage of the COVID-19 epidemic with data in early 2020 in China and worldwide. Our results showed that meteorological conditions (temperature, humidity and UV radiation) had no significant associations with cumulative incidence rate or R0 of COVID-19 based on data from 224 Chinese cities, or based on data of 202 locations of 8 countries before March 9, 2020, suggesting that the spread ability of COVID-19 among public population would not significantly change with increasing temperature or UV radiation or changes of humidity. Moreover, we found that particulate matter pollution significantly associated with case fatality rate (CFR) of COVID-19 in 49 Chinese cities based on data before April 12, 2020, indicating that air pollution might exacerbate negative prognosis of COVID-19. Our studies provided an environmental perspective for the prevention and treatment of COVID-19.

22 The Coronavirus Disease 2019 (COVID-19) has been spreading rapidly to other provinces and 23 neighboring countries. Two mathematical SEIR models have been developed to simulate the current 24 epidemic situation in China. The basic reproductive number R 0 declined from 5.75 to 1.69 in Wuhan 25 and 6.22 to 1.67 in entire China from 19 January to 16 February 2020. Wuhan is estimated to have 26 reached a peak in the number of confirmed cases on 6 February 2020. The results also show that the 27 peak of new asymptomatic cases per day, new symptomatic infections and COVID-19 inpatients in 28 Wuhan occurred on February 6, February 3 and February 14. The number of confirmed cases would 29 decrease to less than 10 on March 27 in Wuhan and March 19 in the other parts of China. Five cities 30 with top risk index in China (except for Wuhan) are: Huanggang, Xiaogan, Jingzhou, Chongqing, and 31 Xiangyang city. We should take more strict isolation measures to end the epidemic ahead of time.