2015
DOI: 10.1186/s12936-015-0630-6
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Malaria incidence from 2005–2013 and its associations with meteorological factors in Guangdong, China

Abstract: BackgroundThe temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population’s susceptibility in Guangdong, China.MethodsThe Granger causality Wald test and Spearman correlation analysis were employ… Show more

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Cited by 42 publications
(33 citation statements)
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“…The cross-wavelet analysis of the same study also reveals that the correlation between malaria incidence and rainfall is stronger only during certain years whereas that of temperature is evident through all the years. In addition, similar associations have been documented for India [40] and China [41], among others. As Cazelles et al [23] reported, dengue epidemics in Thailand are highly related to rainfall and temperature.…”
Section: Cross Wavelet Spectrumssupporting
confidence: 79%
“…The cross-wavelet analysis of the same study also reveals that the correlation between malaria incidence and rainfall is stronger only during certain years whereas that of temperature is evident through all the years. In addition, similar associations have been documented for India [40] and China [41], among others. As Cazelles et al [23] reported, dengue epidemics in Thailand are highly related to rainfall and temperature.…”
Section: Cross Wavelet Spectrumssupporting
confidence: 79%
“…In the next step, Pearson correlation coefficient matrix was calculated for the explanatory variables. Highly correlated (r > |0.7|) explanatory variables were not included in the same regression model simultaneously to avoid multicollinearity effects [33] in the model. A Poisson generalized additive model (GAM) was used to examine temporal associations between remotely sensed environmental variables and monthly dengue fever cases accounting for its over dispersion [11,15,34].…”
Section: Discussionmentioning
confidence: 99%
“…Statistical methods were used by several researchers to investigate the association of climatic factors and malaria incidents which included the multiple polynomial regression to model malaria incidents in India [14], semi-parametric Poisson distribution methods to model the influence of temperature and rainfall on malaria incidence in Zambia [15], distributed non-linear lag model to associate malaria to meteorological factors in China [16], hierarchical Bayesian framework to model effects of weather and climate on malaria distributions in West Africa [17] and the time series regression models [18,19]. All the models have shown reasonable skills over the respective regions.…”
Section: Influence Of Climate On Malariamentioning
confidence: 99%