Dengue is the fastest-rising mosquito-borne disease in China, with its prevalence rapidly expanding northward in recent years.

To analyze the disease burden, spatiotemporal patterns, and determinants of Dengue in China from 2004 to 2023.

Data from the Global Burden of Disease Study 2024, Chinese Public Health Science Data Center, China Health Statistics Yearbook (2022), National Statistics, and weather databases were utilized. Estimated annual percentage change (EAPC) for incidence and mortality were calculated. Spatiotemporal distribution and trends were described. After addressing multicollinearity and spatial autocorrelation, a geographically and temporally weighted regression (GTWR) model was employed to analyze provincial regional heterogeneity by incorporating influencing factors from four dimensions—economy, transportation, healthcare, and natural environment from 2018 to 2020.

From 2004 to 2023, the age-standardized incidence rate (EAPC=5.51%) increased, while age-standardized mortality (EAPC=-5.16%) declined. Dengue fever incidence in most provinces and cities of China showed an increasing trend from 2004 to 2020, with the peak occurring in September. The GTWR model demonstrated strong explanatory power (R²=0.739, Adjusted R²=0.719, AIC=340.492). Based on the spatiotemporal distribution of fitted coefficients, per capita disposable income and passenger turnover showed negative correlations with dengue incidence across provinces. International tourist arrivals and average temperature exhibited positive nationwide correlations. Health personnel per 1 000 population correlated positively only in eastern developed provinces. Average precipitation correlated positively north of the Qinling-Huaihe Line but negatively south of it.

The incidence of dengue fever in most provinces and cities of our country has been on the rise from 2004 to 2020, with the peak incidence in September. The per capita disposable income of all residents, the turnover of tourists, the number of international tourists received, the number of health technicians per thousand people, the average temperature and the average precipitation all have significant influences on the incidence of dengue fever in China. However, there is a strong regional heterogeneity. Therefore, targeted prevention and control measures should be formulated according to the specific conditions of each place.

登革热是我国蚊传疾病中发病率上升较快的媒介传染病之一，且流行范围逐渐向北部地区蔓延。

分析2004—2023年中国登革热的疾病负担、时空分布特征及其影响因素。

利用2025年全球疾病负担（GBD）数据库、中国公共卫生科学数据中心、《中国卫生健康统计年鉴（2022）》、国家数据及天气后报网数据，分析中国登革热发病及死亡估计年度变化百分比（EAPC），描述性分析登革热发病率的时间地域分布及流行趋势，最后通过多重共线性及空间自相关检验后，利用时空地理加权回归（GTWR）模型结合2018—2020年经济、交通、医疗卫生及自然4个维度的影响因素进行省级地域异质性分析。

2004—2023年中国登革热年龄标化发病率呈上升趋势（EAPC=5.51%），年龄标化死亡率呈下降趋势（EAPC=-5.16%）。我国大部分省市登革热发病率在2004—2020年呈上升趋势，发病高峰为9月份。依据2018—2020年中国登革热发病率数据构建的GTWR模型，R²=0.739，Adjusted R²=0.719，AIC=340.492，能够较好地解释自变量对登革热发病的影响。各变量拟合系数时空分布图显示,全体居民人均可支配收入、旅客周转量在各省（自治区、直辖市）与登革热发病率呈负相关关系，接待国际游客量及平均气温在各省（自治区、直辖市）与登革热发病率呈正相关关系，每千人口卫生技术人员数仅在东部经济发达地区与登革热发病率呈正相关关系，平均降水量在我国秦岭-淮河以北主要与登革热发病率呈正相关关系，在秦岭-淮河以南主要与登革热发病率呈负相关关系。

我国大部分省市登革热发病率在2004—2020年呈上升趋势，发病高峰为9月份。全体居民人均可支配收入、旅客周转量、接待国际游客量、每千人口卫生技术人员数、平均气温及平均降水量均对我国登革热的发病具有显著影响，但存在较强的地域异质性，因此应针对各地的具体情况制定针对性的防控措施。