ASSOCIATION BETWEEN METEOROLOGICAL FACTORS AND DENGUE INCIDENCE IN GUANGDONG, CHINA: A TIME SERIES ANALYSIS USING DISTRIBUTED LAG NONLINEAR MODEL
Keywords:
dengue, temperature, rainfall, vector-borne diseasesAbstract
Climate variability greatly affects dengue prevalence; thus, further understanding of the relationship between weather conditions and dengue outbreaks is needed. We analyzed the association between meteorological factors (temperature and rainfall) and the incidence of dengue infection in Guangdong Province, PR China from 2018 to 2019, using weekly mean dengue cases and meteorological data. The nonlinear and delayed associations between dengue incidence and meteorological factors were assessed using a distributed lag nonlinear model. Overall, 9,447 dengue cases were recorded during the study period. The maximum lag-specific and cumulative percent change of dengue cases was 5.5% (95% confidence interval (CI): 3.1-7.9%; lag 0 week) and 28.3% (95% CI: 14.2-43.9%; lag 22 weeks) respectively per 1 °C increase in temperature, and 1.6% (95% CI: 0.6-2.6%; lag 0 week) and 9.4% (95% CI: 3.6-15.4%; lag 12 weeks) respectively for 1 mm increase in rainfall. The cumulative relative risk (RR) for a weekly mean temperature at 25.5°C over 22 weeks was 1.069 (95% CI: 1.031-1.151) relative to a weekly mean temperature at 22.8°C, and for a weekly mean rainfall over 12 weeks with a peak of 9.0 mm RR was 1.623 (95% CI: 0.91-3.40) relative to a weekly mean rainfall of 5.1 mm. However, the risk decreased significantly when rainfall exceeded 20.0 mm. We found a lag nonlinear relationship between meteorological factors and dengue incidence in Guangdong Province. Our findings can be used to develop climate-based early warning systems and provide insights for improving vector control of dengue outbreaks in Guangdong Province.