Li Jiahui, Yu Wenxin, Wang Yanwei, Zhang Ruixue, Zhang Wenzeng. Epidemiological characteristics of febrile respiratory illness epidemics and influencing factors in a district of Beijing, 2010−2023[J]. Disease Surveillance. DOI: 10.3784/jbjc.202405240304
Citation: Li Jiahui, Yu Wenxin, Wang Yanwei, Zhang Ruixue, Zhang Wenzeng. Epidemiological characteristics of febrile respiratory illness epidemics and influencing factors in a district of Beijing, 2010−2023[J]. Disease Surveillance. DOI: 10.3784/jbjc.202405240304

Epidemiological characteristics of febrile respiratory illness epidemics and influencing factors in a district of Beijing, 2010−2023

  • Objective To analyze the epidemiological characteristics of outbreaks of febrile respiratory illness in a district of Beijing from 2010 to 2023, identify the influencing factors of epidemic intensity and duration, and provide evidence for the prevention and control of febrile respiratory illness.
    Methods The incidence data of epidemics of febrile respiratory illness in the district from 2010 to 2023 were collected for a descriptive epidemiological analysis, and χ2 test and the multiple logistic regression model was used to analyze the influencing factors for epidemic intensity and duration.
    Results From 2010 to 2023, a total of 554 epidemics of febrile respiratory illness were reported in the district, with an average attack rate of 21.71%. The median duration of the epidemic was 4 days, and the median size of the epidemic was 8 cases. The annual incidence peak of the epidemic was during November - April, with a total of 501 outbreaks (90.43%) being reported. The attack rate was higher in urban area than in rural area (χ2=169.801, P<0.001). The epidemics mainly occurred in primary or secondary schools and kindergartens (544 outbreaks, 98.19%). The causative pathogens were mainly influenza viruses, accounting for 76.65% (384/501), followed by adenoviruses, accounting for 2.20% (11/501). In the influenza virus-caused epidemics, the attack rate in students who received influenza vaccination was lower than that in those who received no influenza vaccination (χ2=296.350, P<0.001). The multiple logistic regression analysis revealed that private school (OR=5.06, 95%CI: 1.79− 14.27), school suspension for >4 days (OR=3.92, 95%CI: 1.04−14.74), epidemic response for 2−3 days (OR=2.91, 95%CI: 1.99−4.26), epidemic response for4 days (OR=4.79, 95%CI: 2.18−10.54), and influenza B virus/Victoria lineage (OR=3.76, 95%CI: 1.60−8.82) were the influencing factors for the intensity of the epidemics. School suspension for >4 days (OR=47.12, 95%CI: 14.36−154.55), epidemic response for 2−3 days (OR=2.14, 95%CI: 1.44−3.18), epidemic response ≥4 days (OR=20.16, 95%CI: 6.85−59.33), pathogen being included in the current seasonal influenza vaccine composition (OR=0.35, 95%CI: 0.13−0.96), influenza B virus/Victoria lineage (OR=5.25, 95%CI: 2.31−11.91), B/Yamagata lineage (OR=5.54, 95%CI: 1.76−17.45), adenovirus (OR=6.72, 95%CI: 1.66−27.23), and others (mycoplasma pneumoniae, human metapneumovirus, respiratory syncytial virus and rhinovirus) (OR=4.41, 95%CI: 1.19−16.28) were the influencing factors for the duration of the epidemics.
    Conclusion The seasonality of the epidemics of febrile respiratory illness was obvious in the district of Beijing from 2010 to 2023, with higher attack rate in urban area than in rural area. Schools and kindergartens were the high-risk settings, and influenza virus was the most common pathogen. To mitigate the impact and reduce the duration of the epidemics, it is suggested to further strengthen school health management, improve influenza vaccination coverage in students, and conduct timely reporting of the epidemics and standardized epidemic prevention and control.
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