Frontiers in Public Health (Nov 2015)

Seasonal Influenza Epidemics and El Ninos

  • Olusegun Steven Ayodele Oluwole

DOI
https://doi.org/10.3389/fpubh.2015.00250
Journal volume & issue
Vol. 3

Abstract

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Seasonal influenza epidemics occur annually during the winter in the north and south hemispheres, but timing of peaks and severity vary seasonally. Low humidity, which enhances survival and transmission of influenza virus, is the major risk factor. Both El Nino and La Nina phases of El Nino-southern oscillation (ENSO), which determine inter-annual variation of precipitation, are putative risk factors. This study was done to determine if seasonality, timing of peak, and severity of influenza epidemics are coupled to phases of ENSO. Monthly time series of positive specimens for influenza viruses and of multivariate El Nino-Southern Oscillation Index from January 2000 to August 2015 were analyzed. Seasonality, wavelet spectra, and cross wavelet spectra analyses were performed. Of 31 countries in the dataset, 21 were in north hemisphere and 10 in south hemisphere. Highest number of influenza occurred in January in the north hemisphere, but in July in the south hemisphere, p < 0.0001. Seasonal influenza epidemic was coupled to El Nino, while low occurrence was coupled to La Nina. The moderate La Nina of 2010–2011 was followed by weak seasonal influenza epidemic. The influenza pandemic of 2009–2010 followed the moderate El Nino of 2009–2010, which had three peaks. Spectrograms showed time varying periodicities of 6–48 months for ENSO, 6–24 months for north hemisphere influenza, and 6–12 months for south hemisphere influenza. Cross spectrograms showed time varying periodicities at 6–36 months for ENSO and influenza in both hemispheres, p < 0.0001. Phase plots showed that influenza time series lagged ENSO in both hemispheres. Severity of seasonal influenza increases during El Nino, but decreases during La Nina. Coupling of seasonality, timing, and severity of influenza epidemics to the strength and waveform of ENSO indicate that forecast models of El Nino should be integrated into surveillance programmes for influenza epidemics.

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