Association Between Hydrological Conditions and Dengue Fever Incidence in Coastal Southeastern China From 2013 to 2019

• Published in: JAMA network open 2023-01, Vol.6 (1), p.e2249440
• Main Authors: Li, Chuanxi, Wang, Zhendong, Yan, Yu, Qu, Yinan, Hou, Liangyu, Li, Yijie, Chu, Cordia, Woodward, Alistair, Schikowski, Tamara, Saldiva, Paulo Hilário Nascimento, Liu, Qiyong, Zhao, Qi, Ma, Wei
• Format: Article
• Language: English
• Subjects: Bayes Theorem; China - epidemiology; Cities; Cross-Sectional Studies; Dengue - epidemiology; Dengue fever; Environmental Health; Humans; Hydrology; Incidence; Online Only; Original Investigation; Precipitation
• ISSN: 2574-3805; 2574-3805
• DOI: 10.1001/jamanetworkopen.2022.49440

Dengue fever is a climate-sensitive infectious disease. However, its association with local hydrological conditions and the role of city development remain unclear. To quantify the association between hydrological conditions and dengue fever incidence in China and to explore the modification role of city development in this association. This cross-sectional study collected data between January 1, 2013, and December 31, 2019, from 54 cities in 4 coastal provinces in southeast China. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated from ambient temperature and precipitation, with SPEI thresholds of 2 for extreme wet conditions and -2 for extreme dry conditions. The SPEI-dengue fever incidence association was examined over a 6-month lag, and the modification roles of 5 city development dimensions were assessed. Data were analyzed in May 2022. City-level monthly temperature, precipitation, SPEI, and annual city development indicators from 2013 to 2019. The primary outcome was city-level monthly dengue fever incidence. Spatiotemporal bayesian hierarchal models were used to examine the SPEI-dengue fever incidence association over a 6-month lag period. An interaction term between SPEI and each city development indicator was added into the model to assess the modification role of city development. Included in the analysis were 70 006 dengue fever cases reported in 54 cities in 4 provinces in China from 2013 to 2019. Overall, a U-shaped cumulative curve was observed, with wet and dry conditions both associated with increased dengue fever risk. The relative risk [RR] peaked at a 1-month lag for extreme wet conditions (1.27; 95% credible interval [CrI], 1.05-1.53) and at a 6-month lag for extreme dry conditions (1.63; 95% CrI, 1.29-2.05). The RRs of extreme wet and dry conditions were greater in areas with limited economic development, health care resources, and income per capita. Extreme dry conditions were higher and prolonged in areas with more green space per capita (RR, 1.84; 95% CrI, 1.37-2.46). Highly urbanized areas had a higher risk of dengue fever after extreme wet conditions (RR, 1.80; 95% CrI, 1.26-2.56), while less urbanized areas had the highest risk of dengue fever in extreme dry conditions (RR, 1.70; 95% CrI, 1.11-2.60). Results of this study showed that extreme hydrological conditions were associated with increased dengue fever incidence within a 6-month lag period, with different dimensions of city development playing va