Four data points, La Niña, and the flu

Columbia's Jerry Shaman* and Harvard's Marc Lipsitch have a new paper out in PNAS that argues that La Niña events may be driving the pandemic flu cycle by changing the pattern of bird migration:
We find that the four most recent human influenza pandemics (1918, 1957, 1968, and 2009), all of which were first identified in boreal spring or summer, were preceded by La Niña conditions in the equatorial Pacific. Changes in the phase of the El Niño–Southern Oscillation have been shown to alter the migration, stopover time, fitness, and interspecies mixing of migratory birds, and consequently, likely affect their mixing with domestic animals. We hypothesize that La Niña conditions bring divergent influenza subtypes together in some parts of the world and favor the reassortment of influenza through simultaneous multiple infection of individual hosts and the generation of novel pandemic strains. We propose approaches to test this hypothesis using influenza population genetics, virus prevalence in various host species, and avian migration patterns.
Here is a BBC article summarizing the paper. Aside from the fact that this paper is, to my eye, a great argument for robust interdisciplinary training (climate + public health + microbiology), it's also a good example of a fundamental statistical truism: just because the data are sparse doesn't mean you can't say something meaningful. There have been only four pandemic influenzas in the past century, but the likelihood that they would all start at the same point in the ENSO cycle is low (Shaman and Lipsitch estimate it at P=0.069). That on its own wouldn't necessarily be meaningful, but when combined with the fairly credible potential mechanism the authors outline one ends up with a pretty plausible hypothesis. Whether it holds remains to be seen (hence the apposition in the title) but it's a lovely first paper on what might end up being a very important phenomenon.

* Jerry Shaman presented a version of this paper at the session Sol coorganized at AGU (video here).

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