Evaluation of hydrologic and meteorological impacts on dengue fever incidences in southern Taiwan using time-frequency analysis methods

Tsai, Christina W.; Yeh, Ting-Gu; Hsiao, You-Ren

doi:10.1016/j.ecoinf.2018.05.002

Cited by 7 publications

(2 citation statements)

References 52 publications

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“…Another approach that is appropriate for non-stationary and/or nonlinear time series data is time-frequency analysis. Various approaches to time frequency analysis include Fourier transform (FT), Wigner distribution function, short time Fourier transform (STFT), Hilbert-Huang Transform (HHT), and continuous wavelet transform (WT) [7]. Tsai et al [7] compared the most two well-known types of time frequency analysis, HHT and WT in order to investigate the relationship between DF incidence and hydrologic and climatic factors.…”

Section: Methodsmentioning

confidence: 99%

“…Various approaches to time frequency analysis include Fourier transform (FT), Wigner distribution function, short time Fourier transform (STFT), Hilbert-Huang Transform (HHT), and continuous wavelet transform (WT) [7]. Tsai et al [7] compared the most two well-known types of time frequency analysis, HHT and WT in order to investigate the relationship between DF incidence and hydrologic and climatic factors. The WT is an effective approach for analyzing the time series frequency distribution of non-stationary data, but it struggles to capture the nonlinear features, while HHT can capture the non-linear features.…”

Section: Methodsmentioning

confidence: 99%

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Temporal Modeling of Dengue Fever: A Comprehensive Literature Review

Aswi

Cramb

White

et al. 2019

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Dengue fever has become a major public health problem in several countries. This paper aims to review and compare a number of temporal modeling approaches that have been proposed for predicting or forecasting the occurrence of dengue fever. This review also examines influential covariates considered in these studies. A comprehensive literature search was undertaken in September 2018, using Medline (via Ebscohost), ProQuest, Scopus, and Web of Science electronic databases. The search was confined to articles in English, published in refereed journals between January 2000 and September 2018. The most popular approach to temporal modeling of dengue was found to be an autoregressive integrated moving average (ARIMA) model. A limited number of studies applied Bayesian hierarchical dynamic generalized linear models. Climatic variables were most commonly associated with dengue incidence for temporal modeling.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%