Xiaojuan Zhang, Yuanhai You, Jie Liu, Lu Sun, Haijian Zhou, Xingxing Zhang, Bike Zhang
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A seasonal autoregressive integrated moving average (SARIMA) model was constructed to evaluate impact of non-pharmaceutical interventions (NPIs) on disease.</p><p><strong>Findings: </strong>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.</p><p><strong>Interpretation: </strong>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.</p>","PeriodicalId":14006,"journal":{"name":"International Journal of Infectious Diseases","volume":" ","pages":"107969"},"PeriodicalIF":4.8000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effect of COVID-19 non-pharmaceutical interventions on the epidemic trends of scarlet fever in China: A population-based surveillance and modeling study.\",\"authors\":\"Xiaojuan Zhang, Yuanhai You, Jie Liu, Lu Sun, Haijian Zhou, Xingxing Zhang, Bike Zhang\",\"doi\":\"10.1016/j.ijid.2025.107969\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Findings: </strong>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.</p><p><strong>Interpretation: </strong>It demonstrated exceptional impacts of NPIs on the epidemic trends and high-risk regions of scarlet fever in China. 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Effect of COVID-19 non-pharmaceutical interventions on the epidemic trends of scarlet fever in China: A population-based surveillance and modeling study.
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.
期刊介绍:
International Journal of Infectious Diseases (IJID)
Publisher: International Society for Infectious Diseases
Publication Frequency: Monthly
Type: Peer-reviewed, Open Access
Scope:
Publishes original clinical and laboratory-based research.
Reports clinical trials, reviews, and some case reports.
Focuses on epidemiology, clinical diagnosis, treatment, and control of infectious diseases.
Emphasizes diseases common in under-resourced countries.