极端天气对广州登革热的影响:零膨胀负二项空间滞后分析

IF 3.8 2区 医学 Q2 ENVIRONMENTAL SCIENCES
Geohealth Pub Date : 2025-10-01 DOI:10.1029/2025GH001330
Xinqiu Ouyang, Fang Shi, Yang Qiu, Guangran Deng, Shujun Zhang
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引用次数: 0

摘要

气候变化加剧了极端天气,这反过来又影响了传染病的传播。广州作为登革热高发区,缺乏极端天气特征与空间因子相互作用对登革热格局的影响研究。利用零膨胀负二项空间滞后(ZINB-SAR)回归模型,分析了2017 - 2019年广州地区DF的分布,探讨了白天热浪(DHW)、夜间热浪(NHW)和极端降水(EP)对DF的影响。结果显示,登革热病例主要集中在中心城区,流行季节为5 - 11月。ZINB-SAR模型优于负二项回归模型和空间计量模型,所有空间效应系数均显著为正。滞后效应分析显示,在滞后2个月时,每增加一次DHW事件可使DF病例增加10.80% (95% CI: 6.22%-15.59%),而NHW事件可使DF增加2.73% (95% CI: -1.59%-7.23%)。阈值分析表明,DHW强度在0.66 ~ 0.76℃之间由促进DF转变为抑制DF, NHW强度在0.95 ~ 2.28℃之间转变。EP在3个月后表现出最强的影响,使DF病例增加12.05% (95% CI: 9.03%-15.17%),尽管其强度无统计学意义。DF发病率的季节和空间变化明显。综上所述,高热量和极热量的影响主要受事件频率驱动,而非事件强度,而高热量的影响更依赖于事件强度。这些发现突出了广州极端天气与DF之间复杂的时空相互作用,为制定有针对性的气候适应性疾病控制策略提供了重要证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Impact of Extreme Weather on Dengue Fever in Guangzhou, China: A Zero-Inflated Negative Binomial Spatial Lag Analysis

The Impact of Extreme Weather on Dengue Fever in Guangzhou, China: A Zero-Inflated Negative Binomial Spatial Lag Analysis

Climate change intensifies extreme weather, which in turn influences infectious disease transmission. As a dengue fever (DF) hotspot, Guangzhou lacks research on how extreme weather characteristics and spatial factors interact to shape DF patterns. This study analyzed DF distribution in Guangzhou from 2017 to 2019, using a zero-inflated negative binomial spatial lag (ZINB-SAR) regression model to assess the effects of daytime heatwaves (DHW), nighttime heatwaves (NHW) and extreme precipitation (EP) on DF. Results revealed that DF cases were predominantly clustered in central urban areas, with an epidemic season from May to November. The ZINB-SAR model outperformed negative binomial regression and spatial econometric models, with all spatial effect coefficients significantly positive. Analysis of lagged effects showed that each additional DHW event increased DF cases by up to 10.80% (95% CI: 6.22%–15.59%) at a 2-month lag, while NHW events increased DF by 2.73% (95% CI: −1.59%–7.23%). Threshold analysis indicated DHW intensity shifted from promoting to inhibiting DF between 0.66°C and 0.76°C, while NHW intensity transitioned between 0.95°C and 2.28°C. EP demonstrated the strongest effects at a 3-month lag, increasing DF cases by 12.05% (95% CI: 9.03%–15.17%), although its intensity was not statistically significant. Seasonal and spatial variations in DF incidence were evident. In conclusion, DHW and EP impacts were primarily driven by event frequency rather than intensity, whereas NHW effects were more dependent on intensity. These findings highlight the complex spatiotemporal interplay between extreme weather and DF in Guangzhou, providing critical evidence for developing targeted climate-adaptive disease control strategies.

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来源期刊
Geohealth
Geohealth Environmental Science-Pollution
CiteScore
6.80
自引率
6.20%
发文量
124
审稿时长
19 weeks
期刊介绍: GeoHealth will publish original research, reviews, policy discussions, and commentaries that cover the growing science on the interface among the Earth, atmospheric, oceans and environmental sciences, ecology, and the agricultural and health sciences. The journal will cover a wide variety of global and local issues including the impacts of climate change on human, agricultural, and ecosystem health, air and water pollution, environmental persistence of herbicides and pesticides, radiation and health, geomedicine, and the health effects of disasters. Many of these topics and others are of critical importance in the developing world and all require bringing together leading research across multiple disciplines.
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