Objective To explore the impact of meteorological factors on the incidence of scarlet fever in Xicheng District of Beijing, and to provide a scientific basis for formulating targeted prevention and control measures. Methods Daily scarlet fever incidence data and corresponding meteorological data from 2010 to 2019 in Xicheng District of Beijing were collected. Using year, month, and day of the week as time-stratified variables, a conditional logistic regression model with a time-stratified case-crossover design was employed to analyze the impact of different meteorological factors on the number of scarlet fever cases in Xicheng District, while controlling for long-term trends, seasonality and other confounding factors. Results From 2010 to 2019, a total of 3,195 cases of scarlet fever were reported in Xicheng District, with an average annual incidence rate of 24.17/100 000. The overall trend showed fluctuating decline, during which three incidence peaks occurred, with the highest incidence rate observed in 2011. No severe or fatal cases were reported. The incidence of scarlet fever exhibited a distinct seasonal bimodal distribution, primarily concentrated between April to June and November to January of the following year. The conditional logistic regression results showed that the average relative humidity and average temperature were positively correlated with scarlet fever cases (β=0.0203, β=0.0613, P＜0.001), while the average vapor pressure was negatively correlated with scarlet fever cases (β=-0.1468, P＜0.001). Increases average relative humidity and average temperature were risk factors for scarlet fever incidence (OR=1.0205，95%CI=1.0150 -1.0261；OR=1.0632，95%CI=1.0379 -1.0891). For every 1.00% increase in average relative humidity, the number of scarlet fever cases increased by 2.05% (1.50% –2.61%). Similarly, for every 1^。C rise in average temperature, the number of cases increased by 6.32% (3.79% – 8.91%). In contrast, an increase in average vapor pressure had a protective effect against scarlet fever (OR=0.8635,95%CI=0.8392-0.8885). For every 1 hPa increase in average vapor pressure, the number of scarlet fever cases decreased by 13.65% (11.15%–16.08%). Conclusion The average relative humidity, average temperature and average vapor pressure are the primary meteorological factors influencing the incidence of scarlet fever in Xicheng District of Beijing, and can be utilized as indicators for the prevention, control, surveillance and early warning of scarlet fever.

ObjectiveTo understand the epidemic characteristics of influenza in Beijing from 2023 to 2024, and to provide a scientific basis for the prevention and control of influenza. MethodsData on influenza-like illness (ILI) from secondary level and above hospitals, etiology surveillance data, and influenza clusters outbreaks data from 2023‒2024 were used to analyze the epidemic trend and pathogenic characteristics of influenza. Furthermore, an influenza comprehensive index was used to categorize the epidemic intensity at the severity level. ResultsA total of 2 065 857 ILI cases were reported in 2023‒2024 epidemic season, and the percentage of ILI was 3.67%. The age group of 5‒14 years accounted for the highest proportion of ILI (30.48%). A total of 41 766 throat swabs from ILI were detected, with a positive rate of 17.28%.A (H3N2) (51.86%) and B Victoria (41.93%) were the most prevalent subtypes of influenza virus. Clustered influenza outbreaks occurred mainly in primary schools (57.78%) and middle schools (35.55%), mainly caused by the influenza A (H3N2) subtype (85.93%). According to the influenza comprehensive index (I), the period of influenza activity and above (I>0.5) lasted for a total of 37 weeks, accounting for 71.15% of the entire influenza season. ConclusionCompared with previous years, the epidemic level of influenza in Beijing was increased in 2023‒2024, and the peak time became earlier. The comprehensive index method can objectively evaluate the level of influenza epidemic and provide suggestions for the future prevention and control of influenza in Beijing.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.

Objective:To clarify the M protein ( emm gene) types and drug susceptibility characteristic variations of Group A Streptococcus (GAS) in children in Beijing. Methods:The GAS strains isolated from throat swab samples of children diagnosed with scarlet fever and pharyngeal infection in scarlet fever etiology surveillance sentinel hospitals in 16 districts of Beijing in 2018, 2019 and 2021 were analyzed retrospectively.PCR amplification and sequencing were used for emm genotyping, and the minimum inhibitory concentrations (MIC) of 10 antibiotics were determined by the broth microdilution method.The data were analyzed using χ2 test and Fisher′ s exact method between groups. Results:A total of 557 GAS strains were collected, and 11 emm genotypes ( emm1, emm3, emm4, emm6, emm11, emm12, emm22, emm75, emm89, emm128, and emm212) were detected.Of 557 strains, 238 trains were of emm1 type (42.73%), 271 strains were of emm12 type (48.65%) and 48 strains were of other emm types (8.62%). The detection rates of emm1, emm12 and other emm type genes in 2018, 2019, and 2021 were [37.50% (105/280 strains), 57.14% (160/280 strains), 5.36% (15/280 strains)], [49.05% (129/263 strains), 39.54% (104/263 strains), 11.41% (30/263 strains)], and [28.57% (4/14 strains), 50.00% (7/14 strains), 21.43% (3/14 strains)], respectively.In children infected with emm12 in 2018 and 2019, there were more children under 6 years old than children over 6 years old (62.50% vs.46.88%, 46.36% vs.30.36%) (χ 2=7.182, 6.973; all P<0.05). Drug susceptibility testing results suggested that 225 randomly selected GAS strains were all 100.00% sensitive to 7 antibiotics including Penicillin, Levofloxacin, Meropenem, Linezolid, Cefotaxime, Cefepime and Vancomycin.The rates of resistance to Erythromycin, Tetracycline and Clindamycin were [88.57% (93/105 strains), 87.62% (92/105 strains), 86.67% (91/105 strains)], and [94.34% (100/106 strains), 94.34% (100/106 strains), 87.74% (93/106 strains)] in 2018 and 2019, respectively.The test strains were 100.00% (14/14 strains) resistant to the above 3 antibiotics in 2021.MIC 50 and MIC 90 values of Penicillin in 2018, 2019, and 2021 were (0.03 mg/L, 0.03 mg/L), (0.03 mg/L, 0.06 mg/L), and (0.06 mg/L, 0.06 mg/L), respectively.Among 225 GAS strains, 207 strains had drug resistance and were resistant to more than one drug.Specifically, 94.69% (196/207 strains) were resistant to Erythromycin, Tetracycline and Clindamycin.About 4.35% (9/207 strains) were resistant to both Erythromycin and Clindamycin.A total of 0.97% (2/207 strains) were resistant to Erythromycin and Tetracycline. Conclusions:The emm genotypes of GAS in children in Beijing are diverse in 2018, 2019 and 2021.The dominant genotypes are emm12 and emm1, and emm12 is the main epidemiological type.GAS strains maintain highly resistant to Erythromycin, Clindamycin and Tetracycline, and sensitive to Penicillin and other antibiotics.However, MIC 50 and MIC 90 of Penicillin shows an ascending trend.

Objective:To analyze the relationship between the cycle threshold ( Ct) values of N gene of COVID-19 cases and the secondary attack risk in close contacts, and identify the relationship between respiratory viral load and infectivity in COVID-19 cases. Methods:The COVID-19 cases with records of Ct values of N gene within 0-7 days of onset were selected, and their close contacts were recruited as the subjects of study. We collected the information of close contacts, including name, gender, age, isolation mode, exposure mode and outcome (whether they were infected with SARS-CoV-2 or not) and other variables. Multivariate logistic regression models were used to identify the relationship between Ct values of N gene of COVID-19 cases and secondary attack risk in close contacts. Results:A total of 1 618 close contacts were recruited, in whom 77 were confirmed as symptomatic or asymptomatic COVID-19 patients with overall secondary attack rate of 4.8%. The multivariate logistic regression analysis indicated that eating together ( OR=2.741, P=0.054), living together ( OR=9.721, P<0.001), non-centralized isolation ( OR=18.437, P<0.001) and COVID-19 case's values of N gene within 0-7 days of onset being <20 ( OR=8.998, P=0.004) or 20-25 ( OR=3.547, P=0.032) were significantly associated with higher likelihood of being infected with SARS-CoV-2 in close contacts. Conclusion:The results indicated that positive relationship exists between respiratory viral load and infectivity in COVID-19 cases, suggesting that Ct values of N gene can be used as an early warning indicator for the management of close contacts of COVID-19 cases.

Objective:To analyze epidemiological characteristics of influenza in Beijing during 2015—2020 influenza seasons.Methods:Weekly numbers of cases with influenza-like illness and weekly data of virologic surveillance was used to analyze epidemic trend and characteristics of influenza.Results:From June 26, 2015 to June 28, 2020, influenza-like illness (ILI) was 1.58%. A total of 49868 pharyngeal swab samples were collected from ILI cases, and positive rate of influenza virus nucleic acid was 16.32% by real-time PCR. Of these positive samples, 40.89% (6 474) were A(H3N2), 27.86% (4 410) were A (H3N2), 20.78% (3 290) were B/Victoria lineage, and 10.09%(1597) were B/Yamagata lineage. There were correlation between ILI and positive rate of influenza virus ( r=0.796, P<0.001), and ILI percentage and positive rate were also correlated ( r=0.808, P<0.001). The active duration in 2018—2018, 2018—2019 influenza seasons were longer. Weekly numbers of influenza-like illness cases of 2017—2018, 2018—2019 influenza seasons were higher (49 628 and 71 555), peak value of positive rate in the above seasons was higher (58.51% and 57.08%). Conclusions:The epidemic characteristics of influenza during 2015—2020 years was in accordance with the temperate regions of the northern hemisphere. There were longer active period and higher epidemic level in 2017—2018, 2018—2019 influenza seasons. The dominant influenza virus subtypes varied in the different seasons.

COVID-19 ; China/epidemiology* ; Disease Outbreaks ; Humans ; SARS-CoV-2

Objective To calculate both the epidemic and intensity thresholds for different levels in Beijing and to establish a tiered alert system in the 2018-2019 influenza season as well as to evaluate the performance of calculated thresholds.Method Weekly count of influenza-like illness and percentage of influenza-like illness (ILI％) of the last five influenza seasons were modeled by 'moving epidemic method'(MEM) to calculate the influenza epidemic and intensity thresholds at different levels.A cross-validation procedure was used to evaluate the performance.Indicators of Matthew correlation coefficient,Youden's index,sensitivity and specificity were calculated.Results For weekly count of influenza-like illness,data showed that the epidemic threshold for 2018-2019influenza season was 12 984 and the medium,high and very high intensity thresholds were 22 503,37 589,47 157,respectively.Matthew correlation coefficient of the epidemic threshold was 62％ and youden's index as 60％,sensitivity as 69％,specificity as 91％.Data on weekly ILI％,the epidemic threshold for 2018-2019 influenza season was 1.66％,with medium,high and very high intensity thresholds as 2.46％,3.84％ and 4.66％,respectively.The overall Matthew correlation coefficient of the epidemic threshold was 59％,with 54％ for the Youden's index,sensitivity as 60％ and specificity as 94％.Conclusions MEM produced a good specific signal for detecting the influenza epidemics and the accuracy of the method was acceptable.The early warning performance regarding the application of weekly count on influenza-like illness was slightly better than ILI％.This method could be applied in the practical influenza epidemic alert "work in Beijing".

Objective This study aimed to explore the incidence trends and onset features of scarlet fever during the years of epidemic,from 2006 to 2015,in Beijing.Methods Spatial,temporal and population distributions,prognosis of the reported cases and surveillance data on scarlet fever and other streptococcal infections (including the patients of streptococcal infection,tonsillitis and isthmitis) were analyzed by the descriptive epidemiological methods.Results A total of 27 987 scarlet fever cases were reported from 2006 to 2015,with the incidence rates as 7.04 to 18.53 per 100 000 persons during these years,except for 2011.A total of 6 152 cases were reported in 2011,with the incidence of 31.37 per 100 000 persons,significantly higher than the average levels of the other years.There were more cases reported in rural-urban continuum,in summer and winter,with most of the cases were children in primary schools and infant-institutes.From May to December in 2011,4 332 cases were interviewed three weeks after the disease onset,and their conditions improved or recovered,with no death or complication appeared at the follow-up period.There were 2 725 cases of scarlet fever and 104 013 clinical cases of streptococcal infections reported in 36 surveillance hospitals during the same period.The ratio between numbers of scarlet fever cases and streptococcal infection was 1 ∶ 38.17.The weekly numbers of scarlet fever were remarkably correlated to the streptococcal infections,with a Pearson's correlation coefficient as 0.729 (P＜0.001).Accordingly,we estimated that about 21.4 thousand clinical cases of streptococcal infections that were caused by Group A streptococcus in 2011,in Beijing.Conclusions Incidence of scarlet fever in 2011 was significantly higher than the average levels of other years in Beijing,but characteristics on spatial,temporal and population distributions of scarlet fever remained the same,with good prognosis of the reported cases.A large number of culture-positive Group A streptococcus infections among all the clinical cases of streptococcal infection might have been served as important source on septic infection,of scarlet fever.