El Niño Southern Oscillation and vegetation dynamics as predictors of dengue fever cases in Costa Rica.
El Niño Southern Oscillation and vegetation dynamics as predictors of dengue fever cases in Costa Rica.
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DOI：
10.1088/1748-9326/4/1/014011
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发表时间：
2009-03-04
期刊：
影响因子：
--
通讯作者：
Beier JC
中科院分区：
文献类型：
--
作者：
Fuller DO;Troyo A;Beier JC
登革热（DF）和登革出血热（DHF）是整个拉丁美洲和加勒比地区日益严重的健康问题。本研究的重点是哥斯达黎加，该国在2003年至2007年经历了10万多例登革热/登革出血热病例。利用与El Niño南方涛动（ENSO）相关的海面温度异常数据和Terra卫星中分辨率成像光谱仪（MODIS）获得的两个植被指数，模拟了气候和植被动态对哥斯达黎加DF/DHF病例的影响。计算相互关系以评估自变量与DF/DHF病例之间关系的正滞后效应和负滞后效应。该模型利用正弦波和非线性最小二乘来拟合病例数据，当自变量随时间向后移动时，能够解释每周DF/DHF病例中83%的方差。当自变量随时间向前移动时，与预测方法一致，该模型解释了64%的方差。重要的是，当纳入5个ENSO指数和2个植被指数时，该模型再现了2005年的一次登革热/登革出血热大流行。模型中无法解释的差异可能是由于群体免疫和病媒控制措施，尽管通常缺乏有关疾病系统这些方面的信息。我们的分析表明，该模型可用于早在40周前预测登革热/登革出血热暴发，还可提供有关未来流行程度的宝贵信息。目前的形式可用于通报国家病媒控制规划和有关控制措施的政策；这是为该国开发的第一个基于气候的登革热模型，并有可能推广到已观察到登革热/登革出血热发病率和传播急剧增加的更广泛的拉丁美洲和加勒比地区。
Dengue fever (DF) and dengue hemorrhagic fever (DHF) are growing health concerns throughout Latin America and the Caribbean. This study focuses on Costa Rica, which experienced over 100 000 cases of DF/DHF from 2003 to 2007. We utilized data on sea-surface temperature anomalies related to the El Niño Southern Oscillation (ENSO) and two vegetation indices derived from the Moderate Resolution Imaging Spectrometer (MODIS) from the Terra satellite to model the influence of climate and vegetation dynamics on DF/DHF cases in Costa Rica. Cross-correlations were calculated to evaluate both positive and negative lag effects on the relationships between independent variables and DF/DHF cases. The model, which utilizes a sinusoid and non-linear least squares to fit case data, was able to explain 83% of the variance in weekly DF/DHF cases when independent variables were shifted backwards in time. When the independent variables were shifted forward in time, consistently with a forecasting approach, the model explained 64% of the variance. Importantly, when five ENSO and two vegetation indices were included, the model reproduced a major DF/DHF epidemic of 2005. The unexplained variance in the model may be due to herd immunity and vector control measures, although information regarding these aspects of the disease system are generally lacking. Our analysis suggests that the model may be used to predict DF/DHF outbreaks as early as 40 weeks in advance and may also provide valuable information on the magnitude of future epidemics. In its current form it may be used to inform national vector control programs and policies regarding control measures; it is the first climate-based dengue model developed for this country and is potentially scalable to the broader region of Latin America and the Caribbean where dramatic increases in DF/DHF incidence and spread have been observed.
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影响因子：
15.8
作者：
Cazelles B;Chavez M;McMichael AJ;Hales S
通讯作者：
Hales S
影响因子：
2.1
作者：
Cheng, SQ;Kalkstein, LS;Nnaji, A
通讯作者：
Nnaji, A
DOI：
10.3390/s8042136
发表时间：
2008-03-28
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Glenn EP;Huete AR;Nagler PL;Nelson SG
通讯作者：
Nelson SG
影响因子：
2.1
作者：
FOCKS, DA;HAILE, DG;MOUNT, GA
通讯作者：
MOUNT, GA
DOI：
10.1016/j.cimid.2004.03.013
发表时间：
2004-09-01
影响因子：
2
作者：
Gubler, DJ
通讯作者：
Gubler, DJ