This study aimed to update the genetic diversity of Rotavirus (RV) infections in children under five years old in Beijing, China. A 5-year active hospital-based surveillance for sporadic acute gastroenteritis (AGE) from January 2018 to December 2022 in the capital of China was performed. A total of 748 fecal samples from AGE patients were collected for followed by RV antigen detection by ELSIA, RNA detection by reverse transcription PCR, G/P genotyping and phylogenetic analyzing. RV antigen was detected in 11.0% of the collected samples, with 54 samples confirmed to be RV RNA positive. G9 and G8 genotypes were identified in 43 (79.6%) and 7 (13.0%) samples, respectively, all of which were allocated to P[8]. The predominant G/P combination was G9P[8] (79.6%), following by G8P[8] (13.0%), G4P[8] (5.6%) and G3P[8] (1.9%). A significant change in G/P-type distribution was observed, with the G9P[8] being predominant from 2018 to 2021, followed by the emergence of an uncommon G8P[8] genotype, which was first reported in 2021 and became predominant in 2022. Blast analysis showed that one G1 isolate had a high similarity of 99.66% on nucleotide acid with RotaTeq vaccine strain with only one amino acid difference L150V. Additionally, one P[8] isolate was clustered into a branch together with RotaTeq vaccine strain G6P[8]. The study reveals that G8P[8] has become the predominant genotype in pediatric outpatients in China for the first time, indicating a significant change in the composition of RV genetic diversity. The importance of RVA genotyping in surveillance is emphasized, as it provides the basis for new vaccine application and future vaccine efficacy evaluation.

Introduction Human sapovirus (HuSaV) is an enteric virus responsible for sporadic cases and outbreaks of acute gastroenteritis (AGE) globally. A seven-year active surveillance study was conducted to investigate the molecular epidemiology of HuSaVs associated with AGE outbreaks in Chaoyang District of Beijing Municipality, China from January 2015 to December 2021. Methods Fecal and anal swab samples were obtained from patients experiencing AGE outbreaks. HuSaVs were identified through reverse transcription polymerase chain reaction (RT-PCR), and partial viral protein 1 (VP1) sequences (approximately 434 base pairs) were utilized for genotyping, single nucleotide polymorphism (SNP) analysis, and phylogenetic examination. Results HuSaVs were identified in 71 AGE outbreaks, demonstrating a detection rate of 10.5%, second only to norovirus. The primary demographic affected by HuSaV were children under the age of 5 in kindergarten settings. Infection rates tended to peak during two distinct periods: May to June and September to December. Upon genotyping, seven distinct genotypes emerged. GII.3 was the most prevalent, accounting for 54.9% of cases, followed by GI.1 (12.7%), GI.2 (9.9%), GII.5 (7.0%), GI.5 (2.8%), GI.6 (1.4%), GII.1 (1.4%), and untyped cases (9.9%). A phylogenetic analysis of GII.3 identified three distinct groups, with 15 notable SNPs observed. Conclusions This study offers a comprehensive analysis of the persistent prevalence of HuSaV outbreaks in Chaoyang District, Beijing Municipality, China. Over time, the diversity of HuSaV subtypes has shifted, and it is now recognized as the second leading viral agent responsible for AGE outbreaks. This highlights the importance of ongoing surveillance in the future.

Background: Delays in seeking care and diagnosis remain major obstacles to tuberculosis (TB) control. However, the dynamic changes and key drivers of the delays, including shifts during and after the COVID-19 pandemic, remain unclear in Beijing. This study aims to comprehensively analyze the status and influencing factors of care-seeking and diagnostic delays among pulmonary tuberculosis (PTB) patients in Chaoyang District, Beijing, to provide evidence for early detection and timely diagnosis. Methods: Data on PTB cases in Chaoyang District, Beijing from 2016 to 2024 were retrospectively collected from the China Disease Prevention and Control Information System. Joinpoint regression was used to analyze temporal trends in care-seeking and diagnostic delays by age and sex. Based on the identified trend patterns, a categorical time-related variable was constructed and then incorporated into logistic regression and random forest models in a complementary manner to comprehensively explore the influencing factors of the two types of delays. Results: Among a total of 7 683 PTB cases included, the median care-seeking time was 3 days (IQR: 0–19) and the median diagnostic time was 5 days (IQR: 0–20), with the delay rates of 29.7% and 30.6%, respectively. Temporal trends showed a decrease in care-seeking delay from 2016 to 2022(APC=-3.340, P = 0.015), followed by an increase from 2022 to 2024 (APC = 30.335, P < 0.001), and an initial increase then decrease in diagnostic delay from 2018 to 2024 (APC =-11.478, P = 0.002). Female, direct visit, with bacteriological results, retreatment, and the 2023–2024 period were associated with higher care-seeking delay, protective factors included first-visit in other local districts (OR = 0.27, 95%CI: 0.23–0.32) and at lower-level facilities (primary-level or below facilities OR = 0.17, 95%CI: 0.11–0.28). For diagnostic delay, comorbidities, combined with other TB, first-visit outside the city (OR = 2.56, 95%CI: 1.53–4.26) and first visit to the non-designated facilities (tertiary hospital OR = 4.77, 95%CI: 3.92–5.79) increased risk, while Han ethnicity, direct visit, with bacteriological results and the 2023–2024 period were associated with a lower risk. Random forest identified first-visit institution, first-visit region, and bacteriological result as the most important predictors for both delays. Conclusions: Care-seeking and diagnostic delay remained relatively low in Chaoyang District, Beijing, but displayed divergent post-2022 trends. Key determinants were captured using combined analytical approach. Priority should be given to scaling up rapid molecular testing in general hospitals and imaging-assisted screening in primary care to improve active case finding and reduce delays.

At present, there is no research that classifies the epidemic intensity of acute gastroenteritis (AGE) caused by Norovirus (NoV) GII combined cases and environmental surveillance data at the same time. With reference to the experience of the epidemiological-level classification of infectious disease and the actual epidemiological status of NoV AGE in Chaoyang District, Beijing, China, the epidemic intensity of NoV GII was divided into five grades with increasing intensity from grade 1 to grade 5, which corresponds to non-epidemic risk, general risk, moderate risk, high risk, and ultra-high risk, respectively. If the synthetic index of two consecutive monitoring weeks in the epidemic season of 2023–2024 exceeds a certain threshold, an early warning for the corresponding epidemic intensity will be issued and recommendations on the corresponding control measures will be given. This study established and quantified the criteria for the epidemic intensity of AGE caused by NoV GII based on case surveillance data and environmental surveillance data. It provides a reference for other methods to carry out relevant studies in the future. However, mathematical models cannot completely replace skilled experience. Therefore, when making decisions with early warning models in practice, it is necessary to refer to the opinions of professional and experienced experts to avoid the bias of the early warning model from affecting strategy judgment.