Journal of Public Health and Preventive Medicine 2026;37(4):16-20

doi:10.3969/j.issn.1006-2483.2026.04.004

Correlation and lag effect between meteorological factors and scarlet fever incidence based on distributed lag nonlinear model

Di QIN 1 ; Li ZHANG 2 ; Xiaokan WEI 1 ; Xiugang GUAN 1 ; Yanhui CHU 1

Affiliations

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Keywords

Scarlet fever; Meteorological factors; Distributed lag non-linear model

Country

China

Language

Chinese

Abstract

Objective To explore the correlation and lag effect between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, and to provide a theoretical basis for the surveillance, early warning,and scientific prevention and control of scarlet fever. Methods Based on the daily scarlet fever incidence data and concurrent meteorological data in Xicheng District, Beijing from 2010 to 2019, the distributed lag non-linear model (DLNM) was used to analyze the impact of meteorological factors on the incidence of scarlet fever. Results The risk of scarlet fever was the highest when the daily average temperature was 34.2℃ with a lag of 0 days (RR=1.175, 95% CI:1.006-1.372). The risk was the second highest when the daily average temperature was 2.2℃ with a lag of 12 days (RR=1.123, 95% CI:1.044 -1.209). The cumulative relative risk of scarlet fever was statistically significant when the daily average temperature ranged from 27.2℃ to 34.2℃, with the highest cumulative relative risk at 34.2℃ (RR=1.906, 95%CI:1.215-2.989). When the daily average relative humidity was 19.5% with a lag of 6 days, the risk of scarlet fever incidence was the highest (RR=1.022, 95% CI: 1.005-1.040). The cumulative relative risk was statistically significant when the daily average relative humidity ranged from 24.7% to 40.2%, with the highest cumulative relative risk at 27.3% (RR=1.170, 95% CI: 1.020-1.343). The risk of scarlet fever was the highest when the daily average vapor pressure was 1.2 hPa with a lag of 5 days (RR=1.029, 95%CI:1.008-1.050). The cumulative relative risk of scarlet fever was statistically significant when the daily average vapor pressure was 1.2-7.4 hPa, and the highest cumulative risk was when the daily average vapor pressure was 1.2 hPa (RR=1.362, 95% CI:1.022-1.815). Conclusion There is a nonlinear relationship between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, with a certain lag effect. Daily average temperature (27.2-34.2℃), daily average relative humidity (28.6~36.3%) and daily average vapor pressure (1.2-7.4 hPa) increase the risk of scarlet fever. These factors can be used as indicators for the prevention, control, surveillance, and early warning of scarlet fever.