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Spatiotemporal patterns and 2025 forecasting of other infectious diarrheal diseases in Beijing, China: a 21-year
Jiaxin Feng1,2, Baiwei Liu1,2, Xiaona Wu1,2
1Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research On Emerging Infectious Diseases, Beijing Center for Disease Prevention and Control, No. 16 Hepingli Middle Street, Dongcheng District, Beijing, 100013, China.
Background:
Other Infectious Diarrheal Diseases (OIDD), caused by pathogens excluding Vibrio cholerae, Shigella, Salmonella typhi, and Salmonella paratyphi, remain a significant public health concern in China. Beijing, a megacity with high population density, extensive mobility, and a temperate monsoon climate, is a prototypical example of temperate monsoon megacities globally. Long-term OIDD patterns, spatiotemporal distribution, and future trends in such dense urban settings are poorly understood, and insights from Beijing can provide valuable guidance for similar cities worldwide.
Methods:
We retrieved case data on OIDD reported in Beijing during 2004-2024 from the Chinese Disease Prevention and Control Information System. Descriptive epidemiology, spatial autocorrelation analysis, hotspot analysis, and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model were employed to investigate the temporal, demographic and regional distribution patterns, identify high-risk regions, and forecast the incidence of OIDD for 2025.
Results:
A total of 756,933 OIDD cases were reported over the 21-year period. Incidence exhibited an overall downward trend from 2006 to 2022, followed by a rebound from 2023 to 2024. Seasonal peaks occurred in summer (July-August) and winter (December-January), with a notable shift of the summer peak to April-May in 2023. The under-1 year age group showed the highest average annual incidence rate (3502.75 per 100,000), and males were more affected than females (male-to-female ratio 1.19:1). Spatial analysis revealed significant clustering (Moran's I = 0.18-0.44, P < 0.01), with high-high clusters shifting from central urban districts to suburban areas over time, while persistent low-low clusters were observed in remote districts. The SARIMA (1,1,1) (1,1,1) ₁₂ model accurately predicted monthly cases in 2024 (MAPE = 17.46%) and forecast 32,638 OIDD cases in 2025, following a bimodal seasonal pattern.
Conclusions:
This study depicted the 21‑year spatiotemporal epidemiological characteristics of OIDD in Beijing and validated a predictive SARIMA model for future incidence. OIDD showed a downward trend followed by a recent rebound, obvious bimodal seasonality, a heavy burden among young children, and shifting spatial clusters. These results provide key evidence for targeting suburban areas, young children, and seasonal peaks in prevention strategies.
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