Infectious disease science communcation
Today we have two examples of the important issue of communicating scientific knowledge about infectious disease epidemics.
The first is the WHO, which is doing an excellent job of describing the limited information about the new H7N9 influenza outbreak in China. Their media release is here, and they’ve had someone answering questions on Twitter as well as more traditional venues. There’s currently evidence of a small amount of human-to-human transmission, but not enough to sustain a pandemic. On the other hand, the virus does appear to have mutated to live more successfully in people, and this could continue. They don’t advise actually doing anything specific at the moment.
The second is the UK measles epidemic, where The Independent, has as its top front-page headline “MMR scare doctor: this outbreak proves I was right”. Of course, it does nothing of the sort, as the story admits later . He’s claiming that the MMR vaccine should have been replaced by three single vaccines, and even if you believe that anti-vaccination campaigners would then suddenly have stopped their misrepresentations, having three single vaccinations is actually more dangerous than one combined one.
The Independent is maintaining that its story is accurate if you read the whole thing. Even if that were so, it’s still hard to imagine why the opinion of a discredited researcher and struck-off former doctor is the single most important piece of information they have about epidemic and the world today. And, as Martin Robins writes in New Statesman
It would be a great example of the false balance inherent in ‘he-said, she-said’ reporting, except that it isn’t even balanced – Laurance provides a generous abundance of space for Wakefield to get his claims and conspiracy theories across, and appends a brief response from a real scientist at the end.
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »