赵建国, 何冠豪, 肖建鹏, 祝光湖, 刘涛, 胡建雄, 曾韦霖, 李杏, 任周鹏, 马文军. 气温影响登革热传播的机制及未来气温变化对其传播风险的影响[J]. 环境与职业医学, 2022, 39(3): 309-314. DOI: 10.11836/JEOM21457
引用本文: 赵建国, 何冠豪, 肖建鹏, 祝光湖, 刘涛, 胡建雄, 曾韦霖, 李杏, 任周鹏, 马文军. 气温影响登革热传播的机制及未来气温变化对其传播风险的影响[J]. 环境与职业医学, 2022, 39(3): 309-314. DOI: 10.11836/JEOM21457
ZHAO Jianguo, HE Guanhao, XIAO Jianpeng, ZHU Guanghu, LIU Tao, HU Jianxiong, ZENG Weilin, LI Xing, REN Zhoupeng, MA Wenjun. Mechanism of temperature on dengue fever transmission and impact of future temperature change on its transmission risk[J]. Journal of Environmental and Occupational Medicine, 2022, 39(3): 309-314. DOI: 10.11836/JEOM21457
Citation: ZHAO Jianguo, HE Guanhao, XIAO Jianpeng, ZHU Guanghu, LIU Tao, HU Jianxiong, ZENG Weilin, LI Xing, REN Zhoupeng, MA Wenjun. Mechanism of temperature on dengue fever transmission and impact of future temperature change on its transmission risk[J]. Journal of Environmental and Occupational Medicine, 2022, 39(3): 309-314. DOI: 10.11836/JEOM21457

气温影响登革热传播的机制及未来气温变化对其传播风险的影响

Mechanism of temperature on dengue fever transmission and impact of future temperature change on its transmission risk

  • 摘要: 背景 登革热是由伊蚊传播的急性蚊媒传染病,在全球气候变暖背景下,其流行趋势及防控形势愈加严峻,严重危害人群健康。

    目的 以广州市作为研究点,建立人蚊耦合动力学模型,分析气温影响登革热传播的机制及预估未来不同气候变化情景下登革热的发病风险,为适应气候变化提供参考。

    方法 收集广州市2015年1月1日至2019年12月31日登革热报告病例及气象数据,数据分别从广东省疾病预防控制中心和中国气象科学数据共享服务平台获得。2030s(2031—2040年)、2060s(2061—2070年)、2090s(2091—2099年)三个年代三种代表性浓度路径(RCP2.6、RCP4.5、RCP8.5)情景下所对应的气温数据通过第五次耦合模式比较计划(CMIP5)提供的5个大气环流模式(GCMs)计算得到。通过构建登革热传播动力学(ELPSEI-SEIR)模型分别拟合2015—2019年登革热疫情趋势获得模型参数,分析气温影响登革热传播的机制,然后将2030s、2060s及2090s不同RCP情景下所对应的日平均气温纳入到已建立的动力学模型,预估未来不同气候变化情景下登革热的发病风险。

    结果 2015—2019年广州市共报告登革热4234例,呈逐年上升趋势,其中本地和输入病例分别3741例、493例。回归结果显示,模型较好地拟合了广州市2015—2019年登革热疫情,拟合优度决定系数R2和均方根误差分别是0.82和1.96。气温与蚊媒习性间的“U”型或“倒U”型关系,可以直接影响蚊媒的数量,从而影响登革热的传播。结合未来不同气候变化情景的气温预估数据,发现大部分情景下气温升高均促进登革热传播,且流行期明显宽于基线阶段。具体来说,在RCP2.6和RCP4.5情景下,登革热疫情在2060s达到高峰;在RCP8.5情景下,预估2030s发病数最高但随后呈下降趋势,到2090s明显降低,但每年发病高峰时间明显提前,集中在5—7月。

    结论 气温通过影响蚊媒的习性而影响蚊媒的数量和登革热的传播,未来大部分气候变化情景下登革热疫情呈上升趋势,但RCP8.5情景下,登革热的流行风险可能受到抑制,但流行季节可能提前。

     

    Abstract: Background Dengue fever is a mosquito-borne disease transmitted by Aedes aegypti and Aedes albopictus. Under the background of climate change, there are great challenges in the prevention and control of dengue fever, posing a serious health risk to the population.

    Objective To analyze the mechanism of temperature on dengue fever transmission and estimate the risk of dengue fever under different climate change scenarios by establishing a coupled human-mosquito dynamics model using Guangzhou as a research site, and to provide reference for adaptation to climate change.

    Methods Reported dengue fever cases and meteorological data from January 1, 2015 to December 31, 2019 in Guangzhou were collected from Guangdong Provincial Center for Disease Control and Prevention and China Meteorological Data Service Centre, respectively. The temperature data under three Representative Concentration Pahtyway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2030s (2031–2040), 2060s (2061–2070), and 2090s (2091–2099) were calculated by five general circulation models (GCMs) provided by the fifth phase of the Coupled Model Intercomparison Project. A dengue fever transmission dynamics (ELPSEI-SEIR) model was constructed to analyze the mechanism of temperature affecting dengue fever transmission by fitting the dengue fever epidemic trend from 2015–2019, and then the daily mean temperature under selected RCP scenarios for 2030s, 2060s, and 2090s was incorporated into the established dynamics model to predict the risk of dengue fever under different climate change scenarios in the future.

    Results From January 1, 2015 to December 31, 2019, a total of 4 234 cases of dengue fever were reported in Guangzhou, including 3741 local cases and 493 imported cases. The regression results showed that the model well fitted the dengue fever cases in Guangzhou from 2015 to 2019, and the coefficient of determination R2 to evaluate goodness of fit and the root mean squared error were 0.82 and 1.96, respectively. A U-shaped or inverted U-shaped relationship between temperature and mosquito habits could directly affect the number of mosquitoes and the transmission of dengue fever. We also found that temperature increase in most future scenarios could promote the transmission of dengue fever, and the epidemic period was significantly wider than the baseline stage. The epidemic of dengue fever would peak in the 2060s under the scenarios of RCP2.6 and RCP4.5. The estimated incidence of dengue fever was predicated to be highest in the 2030s and then decrease in the following years under RCP8.5, and in the 2090s, the incidence would decrease significantly, but the incidence peak would be earlier in each year, mainly from May to July.

    Conclusion Temperature can directly affect mosquito population and dengue fever transmission by affecting mosquito habits. The cases of dengue fever will increase under most climate scenarios in the future. However, the epidemic risk of dengue fever may be suppressed, and the epidemic season may be advanced under RCP8.5.

     

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