Collaboration between meteorology and public health: Predicting the dengue epidemic in Guangzhou, China, by meteorological parameters.
Collaboration between meteorology and public health: Predicting the dengue epidemic in Guangzhou, China, by meteorological parameters.
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气象学与公共卫生之间的合作：通过气象参数预测中国广州的登革热疫情。
DOI：
10.3389/fcimb.2022.881745
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发表时间：
2022
影响因子：
5.7
通讯作者：
中科院分区：
文献类型：
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作者：
登革热已成为全球范围内日益严重的公共卫生威胁，气候条件已被确定为影响登革热传播的重要因素，因此本研究旨在通过气象方法建立登革热流行预测模型。登革热病例资料和气象资料分别来自广东省疾病预防控制中心和广东省气象局。我们使用时空分析来表征登革热流行。采用斯皮尔曼相关分析法分析滞后气象因子与登革热病例的相关性，确定不同气象因子的最大滞后相关系数。然后，利用广义加性模型分析滞后气象因素对本地登革热病例的非线性影响，并预测不同天气条件下本地登革热病例数。我们描述了登革热病例的时空分布特征，发现散发的单个或少量输入性病例对周围登革热疫情的影响很小。我们进一步建立了综合考虑滞后42天气象因素对本地登革热病例影响的预测模型，结果表明，该预测模型的预测效果为98.8%，并得到了广州2005年至2016年登革热实际发病率的验证。建立的登革热流行预测模型具有较好的预测效果，可根据当地气象条件进行修正，在全球登革热流行区应用。应高度重视集中患者的场所，以控制登革热流行。
Dengue has become an increasing public health threat around the world, and climate conditions have been identified as important factors affecting the transmission of dengue, so this study was aimed to establish a prediction model of dengue epidemic by meteorological methods. The dengue case information and meteorological data were collected from Guangdong Provincial Center for Disease Prevention and Control and Guangdong Meteorological Bureau, respectively. We used spatio-temporal analysis to characterize dengue epidemics. Spearman correlation analysis was used to analyze the correlation between lagged meteorological factors and dengue fever cases and determine the maximum lagged correlation coefficient of different meteorological factors. Then, Generalized Additive Models were used to analyze the non-linear influence of lagged meteorological factors on local dengue cases and to predict the number of local dengue cases under different weather conditions. We described the temporal and spatial distribution characteristics of dengue fever cases and found that sporadic single or a small number of imported cases had a very slight influence on the dengue epidemic around. We further created a forecast model based on the comprehensive consideration of influence of lagged 42-day meteorological factors on local dengue cases, and the results showed that the forecast model has a forecast effect of 98.8%, which was verified by the actual incidence of dengue from 2005 to 2016 in Guangzhou. A forecast model for dengue epidemic was established with good forecast effects and may have a potential application in global dengue endemic areas after modification according to local meteorological conditions. High attention should be paid on sites with concentrated patients for the control of a dengue epidemic.
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影响因子：
--
作者：
Couret J;Benedict MQ
通讯作者：
Benedict MQ
影响因子：
3.7
作者：
Jain, Raghvendra;Sontisirikit, Sra;Prendinger, Helmut
通讯作者：
Prendinger, Helmut
影响因子：
7.7
作者：
Lowe, Rachel;Coelho, Caio A. S.;Rodo, Xavier
通讯作者：
Rodo, Xavier
2005-2017年中国县级登革热疫情时空格局及影响因素
影响因子：
8.4
作者：
Liu, Keke;Sun, Jimin;Liu, Qiyong
通讯作者：
Liu, Qiyong
DOI：
10.3390/ijerph17176339
发表时间：
2020-08-31
影响因子：
--
作者：
Ateba FF;Febrero-Bande M;Sagara I;Sogoba N;Touré M;Sanogo D;Diarra A;Magdalene Ngitah A;Winch PJ;Shaffer JG;Krogstad DJ;Marker HC;Gaudart J;Doumbia S
通讯作者：
Doumbia S