Epidemiological characteristics of common respiratory infectious diseases in children before and during the COVID-19 epidemic

Wang, Bing; Gai, Xiangzhen; Han, Yuling; Li, Yanqin; Zhang, Yun; Sun, Jing; Liu, Miao; Yu, Hao; Peng, Zhibin; Wei, Xiaoling; Chang, Young-Il; Ma, Xiang; Gai, Zhongtao

doi:10.3389/fped.2023.1212658

Cited by 3 publications

References 28 publications

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Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province, China, 2020–2023 post-COVID-19 pandemic

Peng,

Xu,

Tong

et al. 2024

BMC Infect Dis

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Background This study aimed to analyze the epidemic characteristics and influencing factors of school influenza outbreaks in Jiangsu Province, China from 2020 to 2023,following the COVID-19 pandemic, to inform prevention and control strategies. Methods Data on influenza-like illness(ILI) outbreaks from the Chinese Influenza Surveillance Information System and national-level influenza surveillance sentinel hospitals were analyzed. The temporal distribution, school type, virus strains, and outbreak scales were examined using descriptive statistics. Results From 2020 to 2023, 1142 influenza outbreaks occurred in schools, with primary schools(ages 6 to 12) accounting for 71.80%. Most large outbreaks were caused by A(H1N1) and A(H3N2), responsible for 8.99% of total outbreaks. Outbreaks were predominantly reported in the pre-peak periods of B(Victoria) and A(H1N1) circulation, accounting for 86.31% and 92.32% of their respective total outbreaks. No concurrent influenza and COVID-19 outbreaks were observed during the study period. Conclusion Primary and secondary schools are high-risk settings for influenza outbreaks. A(H3N2) shows higher adaptability and is more likely to co-circulate with other subtypes/lineages, especially A(H1N1), leading to larger outbreaks. B(Victoria)-caused outbreaks are more frequent but smaller in scale. School influenza outbreaks are more likely to occur during the early stages of seasonal peaks, particularly for B(Victoria) and A(H1N1). This suggests that influenza outbreaks in schools may play a crucial role in seeding and accelerating the spread of the virus within the broader community.

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Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province, China, 2020–2023 post-COVID-19 pandemic

Peng,

Xu,

Tong

et al. 2024

BMC Infect Dis

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Epidemiological changes of scarlet fever before, during and after the COVID-19 pandemic in Chongqing, China: a 19-year surveillance and prediction study

Wu,

Xiong,

Wang

et al. 2024

BMC Public Health

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Background This study aimed to investigate the epidemiological changes in scarlet fever before, during and after the COVID-19 pandemic (2005–2023) and predict the incidence of the disease in 2024 and 2025 in Chongqing Municipality, Southwest China. Methods Descriptive analysis was used to summarize the characteristics of the scarlet fever epidemic. Spatial autocorrelation analysis was utilized to explore the distribution pattern of the disease, and the seasonal autoregressive integrated moving average (SARIMA) model was constructed to predict its incidence in 2024 and 2025. Results Between 2005 and 2023, 9,593 scarlet fever cases were reported in Chongqing, which resulted in an annual average incidence of 1.6694 per 100,000 people. Children aged 3–7 were the primary victims of this disease, with the highest average incidence found among children aged 6 (5.0002 per 100,000 people). Kindergarten children were the dominant infected population, accounting for as much as 54.32% of cases, followed by students (34.09%). The incidence for the male was 1.51 times greater than that for the female. The monthly distribution of the incidence showed a bimodal pattern, with one peak occurring between April and June and another in November or December. The spatial autocorrelation analysis revealed that scarlet fever cases were markedly clustered; the areas with higher incidence were mainly concentrated in Chongqing’s urban areas and its adjacent districts, and gradually spreading to remote areas after 2020. The incidence of scarlet fever increased by 106.54% and 39.33% in the post-upsurge period (2015–2019) and the dynamic zero-COVID period (2020–2022), respectively, compared to the pre-upsurge period (2005–2014) ( P < 0.001). During the dynamic zero-COVID period, the incidence of scarlet fever decreased by 68.61%, 25.66%, and 10.59% ( P < 0.001) in 2020, 2021, and 2022, respectively, compared to the predicted incidence. In 2023, after the dynamic zero-COVID period, the reported cases decreased to 1.5168 per 100,000 people unexpectedly instead of increasing. The cases of scarlet fever are predicted to increase in 2024 (675 cases) and 2025 (705 cases). Conclusions Children aged 3–7 years are the most affected population, particularly males, and kindergartens and primary schools serving as transmission hotspots. It is predicted that the high incidence of scarlet fever in Chongqing will persist in 2024 and 2025, and the outer districts (counties) beyond urban zone would bear the brunt of the impact. Therefore, imminent public health planning and resource allocation should be focused within those areas. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-024-20116-5.

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Epidemiological Characteristics of Influenza Outbreaks in Schools in Jiangsu Province, China, 2020- 2023 Post-COVID-19 Pandemic

Peng,

Xu,

Huang

et al. 2023

Preprint

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Background To understand the epidemic characteristics and influencing factors of school influenza outbreaks after the COVID-19 pandemic in Jiangsu Province, China from 2020 to 2023, and provide scientific basis for the prevention and control of school influenza. Methods We collected data on influenza-like illness(ILI) outbreaks reported in the Chinese Influenza Surveillance Information System and monitoring data from national-level influenza surveillance sentinel hospitals. Descriptive statistical analysis was conducted on the temporal distribution, school type distribution, virus strain distribution, and epidemic scale of school influenza outbreaks. Results From 2020 to 2023, a total of 833 influenza outbreaks occurred in schools in Jiangsu Province. The most reported school type was primary schools, catering to the age group of 6–12 years, accounting for 70.11% of the total reports. This study included three complete influenza seasons, with the majority of large-scale outbreaks caused by A(H1N1) and A(H3N2), accounting for 9.09% of the total outbreaks caused by them,. Outbreaks occurring in the early stages of the B(Victoria) and A(H1N1) influenza peaks accounted for 86.31% and 97.30%, respectively. The current surveillance data has not yet observed a concurrent outbreak of influenza and COVID-19. Conclusion Primary and secondary schools are high-risk locations for influenza outbreaks. The higher environmental adaptability of A(H3N2) makes it more prone to co-circulate with other subtypes/lineages, especially during concurrent circulation with A(H1N1), increasing the likelihood of large-scale outbreaks. In contrast, outbreaks caused by B (Victoria) show a higher frequency and relatively smaller scale compared to those triggered by influenza A. School influenza outbreaks are more likely to occur in the early stages of seasonal epidemics, indirectly indicating that the occurrence of influenza in schools plays a crucial role in driving the onset and development of influenza within the broader community/population. In the post-COVID-19 pandemic period, it is essential to prioritize influenza monitoring and take measures early to reduce the occurrence of outbreaks.

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Epidemiological characteristics of common respiratory infectious diseases in children before and during the COVID-19 epidemic

Cited by 3 publications

References 28 publications

Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province, China, 2020–2023 post-COVID-19 pandemic

Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province, China, 2020–2023 post-COVID-19 pandemic

Epidemiological changes of scarlet fever before, during and after the COVID-19 pandemic in Chongqing, China: a 19-year surveillance and prediction study

Epidemiological Characteristics of Influenza Outbreaks in Schools in Jiangsu Province, China, 2020- 2023 Post-COVID-19 Pandemic

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