Publication date: Jun 27, 2025
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. 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. 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. 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.
| Concepts | Keywords |
|---|---|
| China | COVID-19 non-pharmaceutical interventions |
| December | Epidemiologic characterization |
| Pandemic | Scarlet fever |
| Pharmaceutical | Surveillance |
Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | COVID-19 |
| disease | MESH | scarlet fever |
| disease | MESH | Infectious Disease |
| pathway | REACTOME | Infectious disease |
| disease | MESH | morbidity |