tetano
Editor, Senior Moderator
Front Public Health. 2017 Nov 23;5:301. doi: 10.3389/fpubh.2017.00301. eCollection 2017.
[h=1]Dynamic Regimes of El Ni?o Southern Oscillation and Influenza Pandemic Timing.[/h] Oluwole OSA[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] El Ni?o southern oscillation (ENSO) dynamics has been shown to drive seasonal influenza dynamics. Severe seasonal influenza epidemics and the 2009-2010 pandemic were coincident with chaotic regime of ENSO dynamics. ENSO dynamics from 1876 to 2016 were characterized to determine if influenza pandemics are coupled to chaotic regimes. Time-varying spectra of southern oscillation index (SOI) and sea surface temperature (SST) were compared. SOI and SST were decomposed to components using the algorithm of noise-assisted multivariate empirical mode decomposition. The components were Hilbert transformed to generate instantaneous amplitudes and phases. The trajectories and attractors of components were characterized in polar coordinates and state space. Influenza pandemics were mapped to dynamic regimes of SOI and SST joint recurrence of annual components. State space geometry of El Ni?os lagged by influenza pandemics were characterized and compared with other El Ni?os. Timescales of SOI and SST components ranged from sub-annual to multidecadal. The trajectories of SOI and SST components and the joint recurrence of annual components were dissipative toward chaotic attractors. Periodic, quasi-periodic, and chaotic regimes were present in the recurrence of trajectories, but chaos-chaos transitions dominated. Influenza pandemics occurred during chaotic regimes of significantly low transitivity dimension (p < 0.0001). El Ni?os lagged by influenza pandemics had distinct state space geometry (p < 0.0001). Chaotic dynamics explains the aperiodic timing, and varying duration and strength of El Ni?os. Coupling of all influenza pandemics of the past 140 years to chaotic regimes of low transitivity indicate that ENSO dynamics drives influenza pandemic dynamics. Forecasts models from ENSO dynamics should compliment surveillance for novel influenza viruses.
[h=4]KEYWORDS:[/h] El Ni?o; chaos; determinism; dynamics; fractal; influenza; nonlinear; pandemic
PMID: 29218303 PMCID: PMC5703710 DOI: 10.3389/fpubh.2017.00301
[h=1]Dynamic Regimes of El Ni?o Southern Oscillation and Influenza Pandemic Timing.[/h] Oluwole OSA[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] El Ni?o southern oscillation (ENSO) dynamics has been shown to drive seasonal influenza dynamics. Severe seasonal influenza epidemics and the 2009-2010 pandemic were coincident with chaotic regime of ENSO dynamics. ENSO dynamics from 1876 to 2016 were characterized to determine if influenza pandemics are coupled to chaotic regimes. Time-varying spectra of southern oscillation index (SOI) and sea surface temperature (SST) were compared. SOI and SST were decomposed to components using the algorithm of noise-assisted multivariate empirical mode decomposition. The components were Hilbert transformed to generate instantaneous amplitudes and phases. The trajectories and attractors of components were characterized in polar coordinates and state space. Influenza pandemics were mapped to dynamic regimes of SOI and SST joint recurrence of annual components. State space geometry of El Ni?os lagged by influenza pandemics were characterized and compared with other El Ni?os. Timescales of SOI and SST components ranged from sub-annual to multidecadal. The trajectories of SOI and SST components and the joint recurrence of annual components were dissipative toward chaotic attractors. Periodic, quasi-periodic, and chaotic regimes were present in the recurrence of trajectories, but chaos-chaos transitions dominated. Influenza pandemics occurred during chaotic regimes of significantly low transitivity dimension (p < 0.0001). El Ni?os lagged by influenza pandemics had distinct state space geometry (p < 0.0001). Chaotic dynamics explains the aperiodic timing, and varying duration and strength of El Ni?os. Coupling of all influenza pandemics of the past 140 years to chaotic regimes of low transitivity indicate that ENSO dynamics drives influenza pandemic dynamics. Forecasts models from ENSO dynamics should compliment surveillance for novel influenza viruses.
[h=4]KEYWORDS:[/h] El Ni?o; chaos; determinism; dynamics; fractal; influenza; nonlinear; pandemic
PMID: 29218303 PMCID: PMC5703710 DOI: 10.3389/fpubh.2017.00301