To construct a scenario expression model reflecting the objective state of unconventional healthcare-associated infection outbreak events, providing a basis for hospital decision-makers to formulate targeted prevention and control strategies.

On the basis of the "triangular" framework of public safety and the theory of disaster science, the components of scenarios of unconventional healthcare-associated infection outbreak events were classified, and the theoretical method of knowledge elements was used to structurally express each component.

The scenario components of unconventional healthcare-associated infection outbreak events were classified into disaster-causing factors (DF), disaster-bearing body (DB), disaster-prone environment (DE), and emergency activities (EA). The spatial and temporal expression models of unconventional healthcare-associated infection outbreak events were constructed according to the binary form of knowledge elements, and some scenarios of the events were expressed as examples. Finally, the five-dimensional scenario expression model of unconventional healthcare-associated infection outbreak events was proposed, consisting of component (K), denotation (N), feature (P), value (D), and time (T) dimensions.

The cross-domain application of the method of knowledge elements provides an innovative model demonstration for unconventional healthcare-associated infection outbreak events, which is of great significance for improving the preparedness for healthcare-associated infection emergencies.

To understand the epidemiological trends of SARS-CoV-2 Omicron variants and evolutionary variations of the spike protein in Quzhou city of Zhejiang province from 2023 to 2024.

Respiratory specimens (including nasopharyngeal swabs and sputum specimens) were collected from COVID-19 cases at sentinel surveillance sites for SARS-CoV-2 variants and influenza in Quzhou between January 2023 and September 2024. The whole genome sequences of SARS-CoV-2 from 267 cases were obtained by nanopore sequencing. The genotypes and amino acid variations were analyzed through Pangolin v4.3 and Nextclade v3.13.1 platforms. Heatmaps of amino acid mutations in the key domains of the spike protein were generated by TBtools-Ⅱ v2.222, while the impact of amino acid mutations on viral adaptability was assessed by the VarEPS system.

All the 246 sequences were Omicron variants of SARS-CoV-2, showing the turnover of BA.5-XBB-BA.2 lineages. These variants were classified into ten sub-lineages, with JN.1 and its sub-lineages showing the highest prevalence (42.28%, 104/246). This classification was consistent with the results of the phylogenetic analysis. The distribution of SARS-CoV-2 genotypes across different age groups showed differences (P < 0.001). Amino acid mutation analysis revealed frequent mutations in the spike protein, with the number of mutation sites gradually increasing over time and involving substitutions, insertions, and deletions. JN.1, XDV.1, and their sub-lineages exhibited higher mutation frequency in the spike protein, accumulating novel mutations (K356T, R403K, N450D, N481K, E544K, A570V, P621S, etc.) in key domains. Functional assessments indicated that multiple spike protein mutations (R346T, S371F, S373P, T376A, D405N, R408S, K417N, G446S, F456L, Y505H, etc.) may reduce the binding stability between the spike protein with neutralizing antibodies.

The Omicron variants were the predominant circulating variants in Quzhou during 2023–2024, exhibiting diverse genotypes. Monitoring and analyzing amino acid mutations in the spike protein facilitate timely understanding of the evolutionary characteristics of SARS-CoV-2, providing a theoretical basis for risk assessment of COVID-19 variant prevalence and the implementation of epidemic prevention and control measures.

To explore the application value of regional health information platform data in reducing garbage code rates and improving data quality at the source.

We analyzed 8 717 death records of registered residents in Putuo district, Shanghai from March 1, 2023 to February 29, 2024. Using the GBD-2019 ICD-10, we extracted cases with the underlying cause of death being classified as a garbage code and examined their baseline characteristics. Using the regional health information platform, we supplemented medical records for cases with garbage-coded underlying causes of death. Two trained mortality coders then revised the underlying causes to evaluate data quality improvement.

The garbage code rates were higher for underlying causes of deaths among individuals < 60 years (14.14%), cases documented in resident death inference certificates (12.74%), and deaths occurring at locations categorized as dead on arrival (23.81%), at home (13.43%), and others (13.04%). On the basis of the regional health information platform, the successful matching rate for medical records with garbage-coded underlying causes was 55.32%, and the effective correction rate for underlying causes reached 50.00%. After correction, the overall garbage code rate decreased from 7.01% to 5.28% (χ² = 22.683, P < 0.001). Notably, significant reductions were observed in the garbage code rates for individuals ≥ 60 years, cases recorded in both official death certificates and death inference certificates, and deaths occurring in hospital wards, at home, and in nursing homes (all P < 0.05). Regarding garbage code classification, prior to correction, the coding rates for Level I (severe impact) to Level Ⅳ (limited impact) were 1.96%, 2.90%, 1.28%, and 0.86%, respectively (χ² = 336.015, P < 0.001), with Level Ⅱ (major impact) codes predominating at 41.41% of cases. Post-correction, the coding rates for Level I to Level Ⅲ reduced (all P < 0.05), with 26.48% of Level Ⅱ codes and 29.46% of Level Ⅲ codes reclassified as non-garbage codes. High-frequency Level Ⅱ codes such as hypertension and hypertensive encephalopathy, as well as Level Ⅲ codes including other diseases of the lung and other specified respiratory conditions exhibited decreases (χ² = 15.599, P < 0.001; χ² = 4.838, P = 0.028).

The regional health information platform effectively targets major mortality reporting sources and significantly reduces garbage code rates, thus substantially improving the overall data quality in mortality statistics.

To understand the status of antibiotic contamination in drinking water in Ma′anshan city, Anhui province and assess the ecological and human health risks of antibiotics, thus providing a scientific basis for drinking water management and antibiotic contamination control.

In 2024, 36 drinking water samples were collected. Solid-phase extraction-high performance liquid chromatography-tandem mass spectrometry was employed to measure the concentrations of 13 antibiotics of 4 categories in source water, finished water, and tap water. Ecological and health risks were assessed for the detected antibiotics.

A total of 7 antibiotics of 3 categories were detected, with the detection rates ranging from 0.00% to 75.00% and concentrations ranging from ND (not detected) to 43.70 ng/L. The antibiotic with the highest concentration was enrofloxacin (43.70 ng/L). The water treatment process demonstrated good removal efficiency for antibiotics, with a removal rate of 89.97%. Specifically, sulfamethoxazole, sulfachloropyridazine, and clarithromycin were completely removed (100.00%). In source water, sulfachloropyridazine and clarithromycin showed no ecological risk to three aquatic organisms, while sulfamethoxazole and enrofloxacin showed no ecological risk to invertebrates and fish but exhibited low-level ecological risk to algae. Under the premise of using the most sensitive species, algae, as an indicator, the combined toxicity of antibiotics posed a moderate ecological risk. Among the detected antibiotics, clarithromycin had the highest health risk quotient (RQ_H), which, however, was less than 1×10⁻², indicating negligible health risks to people of all age groups. The combined effect of antibiotics showed the RQ_sum < 1×10⁻², presenting an increasing-decreasing-increasing trend.

Antibiotic contamination in the drinking water in Ma′anshan is primarily dominated by enrofloxacin. The combined effect of antibiotics poses a moderate ecological risk.

To understand the detection rates of different pneumonia pathogens in children < 5 years in China′s mainland from 2014 to 2023 and provide a basis for the development of preventive and control measures related to childhood pneumonia in China.

We searched China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP, SinoMed, PubMed, Embase, and Web of Science with the time interval from January 1, 2014 to October 10, 2024 for the articles about the detection of different pneumonia pathogens in children < 5 years in China′s mainland. Stata 18.0 was used for meta-analysis of the included articles.

A total of 65 articles (55 in Chinese and 10 in English) involving 197 146 patients were included. The meta-analysis revealed that from 2014 to 2023 in China′s mainland, the overall detection rate of bacterial pathogens causing pneumonia in children < 5 years was 50.9% (95%CI: 41.8%–60.0%), with Streptococcus pneumoniae having the highest detection rate of 14.8% (95%CI: 12.4%–17.1%). The overall detection rate of viral pathogens was 47.8% (95%CI: 37.8%–57.8%), with respiratory syncytial virus (RSV) having the highest detection rate of 21.8% (95%CI: 18.3%–25.2%). The overall detection rate of Mycoplasma and Chlamydia was 18.0% (95%CI: 14.9%–21.1%), with Mycoplasma having the highest detection rate of 16.5% (95%CI: 13.3%–19.7%). Subgroup analysis revealed that the detection rates of bacterial pathogens among children in the < 1-year group, 1–< 3-year group, 3–< 5-year group, and ungrouped < 5-year children were 49.2%, 49.4%, 75.0%, and 43.6%, respectively. In eastern and central-western China, the detection rates of bacterial pathogens in children < 5 years were 38.9% and 54.6%, respectively. During 2014–2019 and 2020–2023, the detection rates of bacterial pathogens in children < 5 years were 53.7% and 31.5%, respectively. The detection rates of bacterial pathogens varied across different ages, regions, and time periods (all P < 0.001). The detection rates of viral pathogens among children in the < 1-year group, 1–< 3-year group, 3–< 5-year group, and ungrouped < 5-year children were 53.5%, 48.3%, 62.0%, and 38.7%, respectively. In eastern and central-western China, the detection rates of viral pathogens in children < 5 years were 47.0% and 42.8%, respectively. During 2014–2019 and 2020–2023, the detection rates of viral pathogens in children < 5 years were 47.1% and 51.2%, respectively. The detection rates of viral pathogens varied across different ages, regions, and time periods (all P < 0.001). The detection rates of Mycoplasma and Chlamydia among children in the < 1-year group, 1–< 3-year group, 3–< 5-year group, and ungrouped < 5-year children were 10.1%, 25.1%, 27.6%, and 20.7%, respectively. In eastern and central-western China, the detection rates of Mycoplasma and Chlamydia in children < 5 years were 18.2% and 16.5%, respectively. During 2014–2019 and 2020–2023, the detection rates of Mycoplasma and Chlamydia in children < 5 years were 18.7% and 19.3%, respectively. The detection rates of Mycoplasma and Chlamydia varied across different ages, regions, and time periods (all P < 0.001).

From 2014 to 2023 in China′s mainland, bacterial pathogens causing pneumonia showed the highest detection rates among children < 5 years, with S. pneumoniae being the predominant bacterial pathogen. Children in the 3–< 5-year group showed elevated detection rates across all pathogen types. Regional and temporal variations were significant: bacterial infections dominated in central-western China and during 2014–2019, whereas eastern China and the 2020–2023 period were characterized by higher rates of viral infections and Mycoplasma and Chlamydia infections.

To understand the influenza (flu) vaccination status and willingness and influencing factors among students in primary and secondary schools with flu outbreaks in Sichuan province and provide reference for formulating flu vaccination strategies.

This study was conducted in 7 primary and secondary schools where flu outbreaks occurred from February to April 2023 in Sichuan province. A total of 5 373 primary and secondary school students in classes with ≥ 2 confirmed cases of flu were selected by convenient sampling method for a questionnaire survey. To reveal the flu vaccination status in the 2020–2023 flu season and the willingness to receive flu vaccination in the 2023–2024 flu season, we employed multivariate unconditional logistic regression to analyze the influencing factors of flu vaccination willingness.

Among the 4 718 primary and secondary school students included in the analysis, 1 320 (28.0%) received flu vaccination in any season during the 2020–2023 flu season. Among them, the flu vaccination rates in the 2020–2021, 2021–2022, and 2022–2023 flu seasons were 10.4% (491/4 718), 14.0% (658/4 718), and 16.6% (785/4 718), respectively. The flu vaccination rates varied in different flu seasons (χ² = 77.076, P < 0.001). The primary motivations for parental consent to flu vaccination included awareness of vaccine benefits leading to a desire for comprehensive protection (60.5%), concern about severe influenza outbreaks and infection risk (12.9%), and school teacher recommendations (9.9%). Conversely, the main reasons for vaccine hesitancy were lack of knowledge about vaccine availability or annual vaccination requirements (33.5%), concerns about potential adverse reactions (21.2%), and perceived risk of post-vaccination infection (10.8%). During the 2023–2024 flu season, 4 113 (87.2%) students expressed willingness to receive flu vaccination. Multivariate logistic regression analysis identified that primary and secondary school students residing in City A and City B, receiving flu vaccination during the 2020–2023 flu season, being aware of annual vaccination requirements, believing in vaccination’s protective efficacy against infection, and concerning about potential transmission from infected classmates and friends demonstrated higher vaccination willingness. Conversely, students aged ≥ 16 years, secondary school attendees, residents of City B, and those concerned about adverse reactions showed lower vaccination willingness.

The flu vaccination coverage among students in primary and secondary schools affected by flu outbreaks in Sichuan province remained suboptima during the 2020–2023 flu seasons. However, vaccination willingness was higher in the 2023–2024 flu season. Key determinants of vaccination willingness included age and city of residence, vaccination history in the 2020–2023 flu seasons, awareness of annual vaccination requirements, perceived efficacy in reducing infection risk, concerns about adverse reactions, and apprehension regarding disease transmission from peers.

To explore the association between temperature and incidence of influenza-like illness (ILI) in Huai′an city, Jiangsu province and provide a scientific basis for the prevention and control of ILI.

The ILI surveillance data of two national influenza surveillance sentinel hospitals and meteorological data in Huai′an from January 1, 2015 to December 31, 2022 were collected from the Chinese Influenza Surveillance Information System and China Meteorological Data Service Center, respectively. The associations between the weekly incidence of ILI and meteorological factors were tested by Spearman correlation analysis. The distributed lag non-linear model (DLNM) was utilized to analyze the association between the average temperature and ILI incidence among residents in Huai′an. The confounding factors such as long-term trends and holiday effects were controlled to analyze the lag effect of average temperature on the incidence of ILI.

In the influenza surveillance sentinel hospitals in Huai′an from 2015 to 2022, the weekly average incidence of ILI was (527.88 ± 444.83) cases. Spearman correlation analysis indicated that weekly average temperature and weekly average air pressure were negatively associated with weekly average incidence (r = −0.24 and 0.19, respectively, both P < 0.001). The results of the DLNM demonstrated that at a lag of 0 week, the heat effect (30 °C) would increase the risk of ILI in the 5–14 (RR = 2.02, 95%CI: 1.03–3.98), 15–24 (RR = 2.25, 95%CI: 1.17–4.32), 25–59 (RR = 2.08, 95%CI: 1.13–3.83), and ≥ 60 (RR = 3.01, 95%CI: 1.04–8.74) age groups; at a lag of 1 week, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 1.96, 95%CI: 1.35–2.84), 0–4 (RR = 1.39, 95%CI: 1.00–1.94), 5–14 (RR = 1.70, 95%CI: 1.04–2.89), 15–24 (RR = 3.88, 95%CI: 2.30–6.57), 25–59 (RR = 4.02, 95%CI: 2.46–6.57), and ≥60 (RR = 13.02, 95%CI: 5.97–28.42) age groups; at a lag of 2 weeks, the cold effect (1 °C) would increase the risk of ILI in the 25–59 age group (RR = 1.58, 95%CI: 1.01–2.48); at a lag of 0–1 week, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 2.51, 95%CI: 1.83–3.46), 0–4 (RR = 1.61, 95%CI: 1.20–2.14), 5–14 (RR = 2.50, 95%CI: 1.55–3.77), 15–24 (RR = 5.01, 95%CI: 3.19–7.87), 25–59 (RR = 5.25, 95%CI: 3.45–8.00), and ≥ 60 (RR = 17.13, 95%CI: 8.89–32.90) age groups, and the heat effect (30 °C) would increase the risk of ILI in the ≥ 60 age group (RR = 4.68, 95%CI: 1.46–15.01); at a lag of 0–2 weeks, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 3.21, 95%CI: 2.34–4.40), 0–4 (RR = 1.96, 95%CI: 1.47–2.62), 5–14 (RR = 3.07, 95%CI: 2.02–4.67), 15–24 (RR = 5.86, 95%CI: 3.76–9.11), 25–59 (RR = 8.32, 95%CI: 5.60–12.46), and ≥ 60 (RR = 15.87, 95%CI: 8.12–31.03) age groups, and the heat effect (30 °C) would increase the risk of ILI in the 15–24 age group (RR = 2.18, 95%CI: 1.08–4.38); at a lag of 0–3 weeks, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 2.10, 95%CI: 1.54–2.88), 0–4 (RR = 1.90, 95%CI: 1.44–2.51), 5–14 (RR = 2.16, 95%CI: 1.43–2.37), 15–24 (RR = 2.42, 95%CI: 1.51–3.86), 25–59 (RR = 3.43, 95%CI: 2.45–5.25), and ≥ 60 (RR = 6.18, 95%CI: 3.07–12.44) age groups.

Temperature affects the risk of ILI in different age groups in Huai′an. The cold effect is the main risk factor and has a lag effect, demonstrating a greater effect on ILI in the elderly population, which suggests that more attention should be paid to the elderly in the future.