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. 2014 Jun 3:4:5157.
doi: 10.1038/srep05157.

Effect of non-stationary climate on infectious gastroenteritis transmission in Japan

Daisuke Onozuka  1
Affiliations

Effect of non-stationary climate on infectious gastroenteritis transmission in Japan

Daisuke Onozuka. Sci Rep. .

Abstract

Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Infectious gastroenteritis cases were non-stationary and significantly associated with the IOD and ENSO (Multivariate ENSO Index [MEI], Niño 1 + 2, Niño 3, Niño 4, and Niño 3.4) for a period of approximately 1 to 2 years. This association was non-stationary and appeared to have a major influence on the synchrony of infectious gastroenteritis transmission. Our results suggest that non-stationary patterns of association between global climate factors and incidence of infectious gastroenteritis should be considered when developing early warning systems for epidemics of infectious gastroenteritis.

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Figures

Figure 1
Figure 1. Monthly time series data in Fukuoka, Japan (2000–2012).
(a) Infectious gastroenteritis cases; (b) Temperature; (c) Relative humidity; (d) Rainfall.
Figure 2
Figure 2. Monthly time series data for global climatic indices (2000–2012).
(a) DMI (dipole mode index); (b) MEI (multivariate ENSO index); (c) Niño 1 + 2 (ENSO index); (d) Niño 3 (ENSO index); (e) Niño 4 (ENSO index); (f) Niño 3.4 (ENSO index).
Figure 3
Figure 3. Cross-wavelet coherency and phase of the infectious gastroenteritis time series with global climatic indices.
(a) DMI (dipole mode index); (b) MEI (multivariate ENSO index); (c) Niño 1 + 2 (ENSO index); (d) Niño 3 (ENSO index); (e) Niño 4 (ENSO index); (f) Niño 3.4 (ENSO index). Red regions in the upper part of the plots indicate frequencies and times for which the two series share variability. Cone of influence (within which results are not influenced by the edges of the data) and significant coherent time-frequency regions (p < 0.05) are indicated by solid lines. In cross-wavelet phase plots, colors correspond to different lags between the variability in the two series for a given time and frequency, measured in angles from −PI to PI. A value of PI corresponds to a lag of 16 months.
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