To analyze the contamination status of human enteroviruses (HEVs) in untreated municipal sewage and identify viral serotypes based on the municipal sewage network in Guizhou province.

Influent sewage samples were collected from monitoring sites in Guiyang city (Nanming district), Zunyi city (Xinpu new district), Liupanshui city (Zhongshan district), and Tongren city (Bijiang district) in Guizhou province from November 2024 to January 2025. Ten virus-enriched sewage samples were processed by a combined anion-exchange membrane adsorption-elution and ultrasound-assisted elution method. The concentrated viral particles were then inoculated into human rhabdomyosarcoma (RD) cells and mouse L20B cells expressing the human poliovirus receptor. RNA was extracted from virus-positive isolates obtained through cell culture, followed by reverse-transcription polymerase chain reaction (RT-PCR) to amplify the VP1 gene of enteroviruses. Genetic sequencing and phylogenetic analysis were performed to characterize the obtained viral strains.

A total of 26 poliovirus (PV) vaccine-related strains and 11 non-polio enterovirus (NPEV) strains were isolated from the 10 sewage samples. Of the PV strains, 10 were of serotype I and 16 were of serotype Ⅲ. All the 26 PV vaccine-related strains exhibited fewer than 10 nucleotide variations in the VP1 region compared to the Sabin reference strains. The NPEV strains included seven echovirus 11 (E11) strains, one echovirus 6 (E6) strain, and one strain each of coxsackieviruses B2 (CVB2), B3 (CVB3), and B5 (CVB5). Phylogenetic analysis revealed that the seven E11 strains belonged to the genetic subcluster D5.

HEVs were detected in sewage samples from the municipal sewage system of Guizhou province, while no wild poliovirus or vaccine-derived poliovirus was identified. Viral surveillance data confirm the potential environmental contamination by HEVs and could inform the development of wastewater management policy standards.

To construct a healthy village monitoring index system in Zhejiang province and provide scientific reference for the competent departments to monitor the progress in healthy village construction.

From May to September 2024, one healthy village was randomly selected from each of the 11 prefecture-level cities in Zhejiang province for on-site research to assess the current status of healthy village construction, and a pool of indexes for monitoring healthy village in Zhejiang province was established by combining the analysis of the related policies and literature and the results of expert discussion. From October to December 2024, the Delphi method was employed to carry out two rounds of consultation with 20 experts in related fields to determine the monitoring index system. The analytic hierarchy process (AHP) was adopted to complete the weighting design of the index system.

The first and second rounds of Delphi expert consultation showed the positive coefficients of experts being 86.96% and 100%, the proportion of experts giving opinions being 70% and 20%, and the coefficients of expert authority being 0.848 and 0.878, the Kendall’s harmony coefficients of index importance being 0.386 and 0.419, and the Kendall’s harmony coefficients of index operability being 0.350 and 0.369 (all P < 0.05). The consistency ratio (CR) of the AHP judgment matrix was less than 0.1. Finally, a healthy village monitoring index system of Zhejiang province was formed, consisting of 6 first-level indicators, 17 second-level indicators, and 55 third-level indicators, which showed the weights of 0.073 8 to 0.253 5, 0.022 0 to 0.126 8, and 0.001 5 to 0.084 5, respectively.

The healthy village monitoring index system in Zhejiang province that is constructed in this study is in line with the characteristics of healthy village construction in Zhejiang province and can provide reference for the competent authorities to carry out the monitoring of construction progress.

To explore the impact of health resource allocation and health security on the choice of elderly care services among China's elderly population, and to provide insights for promoting healthy aging.

The panel data of 2 444 elderly people aged over 65 years old were selected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2011, 2014, and 2018. A mixed-effects logit regression model (MLR) with random effects was used to analyze the impact of health resource allocation and health security on the choice of elderly care services. Age heterogeneity was examined through subgroup analysis based on age and residence type. The robustness of the results was tested by comparing different link functions (logit and probit) using generalized estimating equations (GEE), which were chosen to account for potential model misspecification and to ensure the reliability of the results.

Health resource availability (β = 1.587, P < 0.05), health resource accessibility (β = 0.790, P < 0.05), and health security (β = 0.380, P < 0.05) were significantly associated with increased odds of the elderly choosing institutional care. Specifically, after exponentiating the beta coefficients, for each 1-grade increase in health resource availability, health resource accessibility, and health security, the odds of the elderly choosing institutional care increased by a factor of 4.89, 2.20, and 1.46, respectively (all P < 0.05). Heterogeneity analysis results indicate that both the availability (β = 1.729, P < 0.05) and accessibility (β = 0.832, P < 0.05) of health resources have a significant impact on the choice of elderly care services for the oldest elderly (≥ 80 years); the impact of health security on the choice of elderly care services for both the young elderly (β = 0.392) and the oldest elderly (β = 0.363) is significant (both P < 0.05); the availability of health resources (β = 1.433), accessibility of health resources (β = 0.619), and health security (β = 0.326) have a significant impact on the choice of elderly care services for the urban elderly population (all P < 0.05); availability of health resources (β = 1.850), accessibility of health resources (β = 1.084), and health security (β = 0.340) have a significant impact on the choice of elderly care services for the rural elderly population (all P < 0.05).

The allocation of health resources and health security significantly influence the choice of elderly care services. The allocation of health resources affects different age groups and residential types of the elderly population differently, while the impact of health security varies across residential types.

To construct a cross-regional transmission risk assessment model for respiratory infectious diseases, providing a theoretical basis, practical experience, and technical support for evaluating the risk of cross-regional transmission.

Data related to the COVID-19 epidemic in China from January 2020 to December 2022, officially released by the National Health Commission, Baidu Migration, and provincial statistical bureaus, were collected. Nine epidemic events were selected: the 2020 Wuhan, Hubei province epidemic; the 2021 Shijiazhuang, Hebei province epidemic; the 2021 Xi'an, Shaanxi province epidemic; the 2022 Shanghai epidemic; the 2022 Beihai, Guangxi Zhuang Autonomous Region epidemic; the 2022 Sanya, Hainan province epidemic; the 2022 Hohhot, Inner Mongolia Autonomous Region epidemic; the 2022 Zhengzhou, Henan province epidemic; and the 2022 Shijiazhuang, Hebei province epidemic. Principal component analysis (PCA) was used to construct a comprehensive input risk index formula for urban epidemics to quantitatively assess the comprehensive cross-regional epidemic input risk. The principal components with higher contribution rates were used as feature vectors for a support vector machine (SVM) model, with the actual intercity epidemic transmission status as the target variable. The SVM was used for model construction and prediction, and the Shapley Additive exPlanations (SHAP) method was used for model interpretability analysis.

Five factors were extracted by PCA: local socioeconomic activity factor (F₁), epidemic source socioeconomic activity factor (F₂), urban policy implementation factor (F₃), urban population inflow and geographical distance-related factor (F₄), and urban epidemic transmission index factor (F₅), with a cumulative variance contribution rate of 82.32%. Based on the principal component score coefficients and variance contribution rates, the formula for the comprehensive input risk index score was: F=0.2178×F₁+0.1841×F₂+0.1556×F₃+0.1419×F₄+0.1238×F₅. The SVM model achieved a prediction accuracy of 84.88%, precision of 75.00%, recall of 57.14%, and an F1-score of 64.86%. SHAP analysis showed that the SHAP values of F₁, F₂, F₃, F₄, and F₅ were 0.15, 0.09, 0.08, 0.08, and 0.12, respectively, contributing 29.23%, 16.72%, 15.26%, 16.09%, and 22.70% to the assessment of transmission risk.

The cross-regional transmission risk assessment model for respiratory infectious diseases constructed in this study, based on COVID-19 epidemic data, demonstrates good applicability and accuracy in quantifying the risk of cross-regional importation and predicting transmission, providing theoretical support and practical reference for the scientific formulation of respiratory infectious disease prevention and control strategies.

To analyze the trends in hepatitis A (HA) and hepatitis B (HB) incidence in China and provide evidence for scientific prevention and control.

Data on HA and HB incidence from 2004 to 2020 were collected from the Public Health Science Data Center for 31 provinces (autonomous regions and municipalities) in China′s mainland . Joinpoint regression and Bayesian Age-Period-Cohort (BAPC) models were used to analyze the overall trends, age, period, and birth cohort effects of HA and HB.

The overall incidence of HA showed a decreasing trend from 2004 to 2020 (AAPC= –11.23%, 95%CI: –13.32% to –9.09%), with decreasing trends observed in both 2004–2012 (EAPC= –15.47%, 95%CI: –18.57% to –12.24%) and 2012–2020 (EAPC= –6.79%, 95%CI: –10.21% to –3.23%). The overall incidence of HB showed no significant trend from 2004 to 2020 (AAPC= –0.43%, 95%CI: –2.95%–2.17%). From 2004 to 2020, the highest HA incidence rates were observed in the 5–9 (71 223 cases, 5.34/100 000), 0–4 (53 493 cases, 3.92/100 000), and 10-14 (48 481 cases, 3.49/100 000) age groups. The age group with the highest HA incidence shifted from younger age groups (≤14 years) in 2004 to older age groups (≥75 years) after 2017. From 2004 to 2020, the highest HB incidence rates were observed in the 25–29 (1 981 536 cases, 114.46/100 000), 30–34 (1 878 450 cases, 110.13/100 000), and 50–54 (1 500 335 cases, 99.61/100 000) age groups. The age group with the highest HB incidence shifted from the 15–24 age group in 2004 to the 50–59 age group after 2016. The birth cohort risk of HA showed an inverted "V" shape, with a decreasing trend in those born after 2000 (P<0.05). The birth cohort risk of HB also showed an inverted "V" shape, with a decreasing trend in those born after 1995 (P<0.05).

After the inclusion of HA and HB vaccines in the Expanded Program on Immunization (EPI) in China, the incidence rates in the target populations have decreased significantly. From 2004 to 2020, significant changes were observed in the high-risk populations for both HA and HB, with a trend towards higher age groups.

To analyze the content, characteristics, and public engagement of popular health information related to cervical cancer prevention and control on Chinese social media, and to explore the key factors influencing information dissemination and interaction, providing a basis for optimizing health communication strategies.

From Sina Weibo, a total of 591 popular posts related to cervical cancer prevention and control were selected, covering the period from January 1, 2022, to February 1, 2023. A combination of manual and computer-assisted coding methods was used to analyze the information content, dissemination patterns, public engagement, and emotional tendencies. Multivariate analysis of covariance (MANCOVA) and analysis of variance (ANOVA) were employed to explore the relationships between variables.

Authoritative media dominated the dissemination of cervical cancer prevention and control information (56.85%), and the proportion of factual information was high (91.4%). Discussions related to the human papillomavirus (HPV) vaccine (43.15%) were significantly more prevalent than those related to cervical cancer screening (8.63%), and the emphasis on male responsibility was insufficient (2.2%). The mean Weibo diffusion structure was close to 1 (M = 1.69, SD = 0.64), indicating that information dissemination exhibited a "one-to-many" broadcast structure rather than a "many-to-many" viral diffusion pattern. The source, topic, veracity, and gender orientation of the information significantly influenced some indicators of public engagement. The source significantly affected the diffusion scale (P = 0.047) and diffusion structure (P = 0.004), with media having a wider reach and tending towards viral dissemination. The topic significantly affected the diffusion scale (P = 0.008) and diffusion structure (P < 0.001), with topics related to vaccine controversies less likely to exhibit viral diffusion patterns. The veracity of information significantly affected the diffusion scale (P = 0.004), with false information having a wider reach. Gender orientation significantly affected the diffusion scale (P = 0.003) and the number of likes (P = 0.035), with male-oriented content being more likely to be reposted and liked. Furthermore, the source (P < 0.036), topic (P < 0.001), veracity (P < 0.001), and sentiment (P < 0.001) of the original Weibo post significantly predicted public sentiment, with vaccine controversies and negative sentiment tending to evoke negative emotions.

Authoritative media play a leading role in the dissemination of cervical cancer prevention and control information, but there is an imbalance in the ratio of discussions about HPV vaccination and screening, and insufficient emphasis on male responsibility. Information dissemination is mainly characterized by a broadcast structure, and the source, topic, veracity, and gender orientation of information are key factors influencing public engagement and sentiment.

To evaluate the clinical value of intravenous anesthesia with Esketamine in children undergoing surgery.

A total of 1 296 children undergoing surgery between January 1, 2020 and January 1, 2024 were selected by convenient sampling from two tertiary hospitals in Jinan, China. Participants were allocated into three groups: Esketamine (E) group (n = 447), Propofol (P) group (n = 411), and Sevoflurane (S) group (n = 438). Baseline characteristics, anesthetic efficacy (including anesthesia induction time, emergence time, emergence agitation, duration of emergence agitation, and crying), and adverse reactions were compared among groups.

The three groups were well-balanced in baseline characteristics, with mean age of (6.9 ± 2.8) years and mean body weight of (21.35 ± 8.24) kg. Significant differences were observed in anesthesia induction time [(45.73 ± 9.59) s, (50.36 ± 10.28) s, and (35.53 ± 8.76) s in E, P, and S groups respectively; F = 114.05, P < 0.001] and emergence time [(21.27 ± 4.63) min, (25.34 ± 5.18) min, and (15.42 ± 4.85) min; F = 134.65, P < 0.001]. The incidences of emergence agitation (χ² = 10.09) and crying (χ² = 13.42) showed differences among groups (P < 0.05). Regarding safety profiles, significant intergroup differences were observed in incidences of hypotension (χ² = 15.85), excessive sedation (χ² = 12.65), respiratory depression (χ² = 19.83), and pain (χ² = 9.83) (all P < 0.05).

Esketamine induces effective anesthesia with mild adverse effects in children undergoing surgery.

To establish a biosafety supervision evaluation index system for pathogenic microorganism laboratories, assess the implementation and effectiveness of laboratory biosafety supervision by municipal/district-level health administrative departments, and provide references for innovating regulatory evaluation methods, identifying weaknesses in administrative management, and optimizing laboratory biosafety supervision.

After constructing the primary evaluation index system, Delphi qualitative interview were conducted among 20 authoritative experts and scholars engaged in laboratory biosafety to screen the indicators from November 2024 to January 2025. The weights of the selected indicators were calculated using hierarchical analysis.For the two rounds of expert consultation, the response rates were 100% with authority coefficients of 0.940 and 0.913, respectively. The Kendall harmony coefficient for the first round was 0.431, with statistical testing confirming consistency among expert scores (P < 0.01), indicating reliable selected indicators within the system.

The final index system comprised 3 first-level indicators (regulatory system, regulatory process, and regulatory outcome, with weights of 0.547 3, 0.297 8, and 0.155 0, respectively), 9 second-level indicators (with organizational team, institutional development, and funding situation having the highest weights at 0.249 7, 0.186 3, and 0.111 2, respectively), and 30 third-level indicators (with the biosafety expert group having the highest weight at 0.101 2, followed by personnel function coverage and overall safety management system, both weighted at 0.089 9).

This study established an evaluation index system for biosafety supervision in pathogenic microorganism laboratories based on the SPO model, addressing a critical gap in administrative department assessment tools. The developed index system enables comprehensive and accurate evaluation of laboratory biosafety supervision through systematic and operational indicators. When applied across the four key stages of planning, implementation, inspection, and feedback, this system promotes a shift from reactive responses to proactive prevention and control measures, ultimately enhancing laboratory biosafety.