[Epidemiological characteristics and spatiotemporal analysis of dengue fever in Guangdong Province in 2014 and 2024].

Objective

To analyze the characteristics of two dengue fever outbreaks in Guangdong Province in 2014 and 2024 to provide reference for dengue fever prevention and control.

Methods

Using subdistrict/town as the smallest spatial unit, descriptive epidemiological methods, spatial autocorrelation analysis, and spatiotemporal scanning were employed to analyze dengue fever cases in Guangdong Province in 2014 and 2024. Data were obtained from the China Information System for Disease Control and Prevention for dengue fever cases reported in Guangdong Province in 2014 and 2024. Spatiotemporal scanning was performed using SaTScan 10.2 software.

Results

The peak incidence of local cases in both 2014 and 2024 occurred from September to October. Seasonal analysis showed strong seasonality for local cases in both years (concentration M values of 0.956 and 0.896, respectively). Circular distribution analysis indicated that the epidemic period in 2024 was prolonged by 20 days compared with 2014 (Rayleigh test, P<0.001). Imported cases showed moderate seasonality in both years (M values of 0.368 and 0.344, respectively; Rayleigh test, P<0.001). Spatial autocorrelation analysis revealed Moran's I values of 0.521 for local cases in 2014 and 0.257 for local cases in 2024, indicating spatial clustering in both years, with stronger clustering observed in 2014. Spatiotemporal scanning identified 2 clusters in 2014, with the primary cluster located in Xinghua Subdistrict, Tianhe District, Guangzhou City (August 28-November 2, RR=189.90, LLR=116 786.01, P<0.001); and 5 clusters in 2024, with the primary cluster located in Shishan Town, Nanhai District, Foshan (August 10-November 23, RR=20.38, LLR=12 313.33, P<0.001).

Conclusion

Both the 2014 and 2024 dengue fever outbreaks in Guangdong Province exhibited spatiotemporal clustering. Compared with 2014, the distribution of dengue cases in 2024 expanded significantly, with a prolonged epidemic peak duration and an increased risk of imported cases from abroad. Moreover, more spatiotemporal clusters were identified.