International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2025
Effect of nonpharmaceutical interventions on the epidemic trends of scarlet fever in China: a population-based surveillance and modelling study.
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Zhang Xiaojuan, You Yuanhai, Liu Jie, Sun Lu, Zhou Haijian, Zhang Xingxing, Zhang Bike
Аннотация
BACKGROUND: This study analyzed the epidemiological patterns of scarlet fever, and any changes therein, before, during, and after the COVID-19 pandemic in China and provided new perspectives for optimizing prevention and control strategies.
METHODS: Data for clinically diagnosed and laboratory-confirmed cases between January 1, 2005, and December 31, 2024, were collected from the National Notifiable Infectious Disease Surveillance System. Descriptive analysis was used to summarize the characteristics in pre-COVID-19 (2005-2019), during COVID-19 (2020-2022), and post-COVID-19 (2023-2024) periods. Dynamic changes in distribution pattern were explored through spatial autocorrelation analysis. A seasonal autoregressive integrated moving average (SARIMA) model was constructed to evaluate impact of non-pharmaceutical interventions (NPIs) on disease.
FINDINGS: During 2005-2024, 876,680 cases were reported (crude annual incidence: 3.22/100 000). The annual morbidity rates for three periods were 3.56, 1.58, and 3.25/100 000. Significant differences were observed among the periods (P < 0.001). The actual cases during COVID-19 period decreased by 78.43% compared to the SARIMA model predictions. Significant geography-based clustering of cases was identified.
INTERPRETATION: It demonstrated exceptional impacts of NPIs on the epidemic trends and high-risk regions of scarlet fever in China. Hence, tight surveillance programs are needed to protect populations against future pandemics.
METHODS: Data for clinically diagnosed and laboratory-confirmed cases between January 1, 2005, and December 31, 2024, were collected from the National Notifiable Infectious Disease Surveillance System. Descriptive analysis was used to summarize the characteristics in pre-COVID-19 (2005-2019), during COVID-19 (2020-2022), and post-COVID-19 (2023-2024) periods. Dynamic changes in distribution pattern were explored through spatial autocorrelation analysis. A seasonal autoregressive integrated moving average (SARIMA) model was constructed to evaluate impact of non-pharmaceutical interventions (NPIs) on disease.
FINDINGS: During 2005-2024, 876,680 cases were reported (crude annual incidence: 3.22/100 000). The annual morbidity rates for three periods were 3.56, 1.58, and 3.25/100 000. Significant differences were observed among the periods (P < 0.001). The actual cases during COVID-19 period decreased by 78.43% compared to the SARIMA model predictions. Significant geography-based clustering of cases was identified.
INTERPRETATION: It demonstrated exceptional impacts of NPIs on the epidemic trends and high-risk regions of scarlet fever in China. Hence, tight surveillance programs are needed to protect populations against future pandemics.