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.

Objective To understand the distribution of M protein gene (emm) of group A streptococcus (GAS) infections among children in Xicheng District of Beijing. Methods Throat swab samples from scarlet fever and pharyngeal infection cases were collected in sentinel hospitals of Xicheng District, Beijing from 2011 to 2024. GAS strains were isolated and identified, and emm gene was amplified and sequenced by PCR to determine the genotype. The differences in emm genotype between different groups were compared. Results A total of 3 130 throat swab samples were collected, and 400 GAS strains were isolated, with a positive rate of 12.78%. The highest positive rate was 19.93% in 2011. The positive rate of scarlet fever (45.71%) was higher than that of pharyngeal infection (6.14%) (P<0.001). There were 391 emm gene positive strains, and the differences in the positive rate of emm gene among different cases were statistically significant (P<0.001). A total of 7 genotypes and 27 gene subtypes were detected. Among different groups, the emm genotypes were mainly emm12 and emm1. The emm gene subtypes were mainly emm12.00 and emm1.00. Except for some years, the genotypes and their subtypes were dominated by emm12 and emm12.00, and the distribution differences of the two major genotypes and their subtypes were statistically significant from 2011 to 2019 (P<0.001). There were differences in genotypes and subtypes among different age groups (P=0.002). Conclusion The dominant types of emm genes in group A streptococcus infections among children were emm12 and emm1 in Xicheng District of Beijing from 2011 to 2024, and the dominant gene subtypes were emm12.00 and emm1.00. It is necessary to comprehensively strengthen the monitoring of the epidemic situation and genotype, timely grasp the distribution and variation of emm gene.