ArticleEpidemiology and infection2014
Spectral analysis based on fast Fourier transformation (FFT) of surveillance data: the case of scarlet fever in China.
Article in Epidemiology and infection, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Patterns in the Incidence of Scarlet Fever Among Children Aged 0-9 Years - China, 2010-2019.China CDC weekly · 2023Article
- Multivariate time series analysis on the dynamic relationship between Class B notifiable diseases and gross domestic product (GDP) in China.Scientific reports · 2016Article
- The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models.International journal of environmental research and public health · 2016Article
- Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005-2014.International journal of environmental research and public health · 2016Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many infectious diseases exhibit repetitive or regular behaviour over time. Time-domain approaches, such as the seasonal autoregressive integrated moving average model, are often utilized to examine the cyclical behaviour of such diseases. The limitations for time-domain approaches include over-differencing and over-fitting; furthermore, the use of these approaches is inappropriate when the assumption of linearity may not hold. In this study, we implemented a simple and efficient procedure based on the fast Fourier transformation (FFT) approach to evaluate the epidemic dynamic of scarlet fever incidence (2004-2010) in China. This method demonstrated good internal and external validities and overcame some shortcomings of time-domain approaches. The procedure also elucidated the cycling behaviour in terms of environmental factors. We concluded that, under appropriate circumstances of data structure, spectral analysis based on the FFT approach may be applicable for the study of oscillating diseases.
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