Revere at Effect Measure is not very happy about the publicity surrounding a paper published in Nature on the mathematical modelling of pandemic influenza, or, even with the decision of the scientists who decided to publish in Nature or the editorial board of Nature which accepted it for publication:
I’m a supporter of mathematical modeling as another way to get a handle on what might happen in an influenza pandemic. But a recent paper by the group at London’s Imperial College, published in Nature, shows what can happen when modelers allow their work to bear more weight than it can sustain. When a prestigious scientific journal, Nature, publishes such a paper, it also gets attention it wouldn’t get if published in a more appropriate place — meaning a place where its scientific contribution could be judged in the usual way, not under the glare of global publicity. I’m not blaming the wire services. The reporting on this paper is pretty high quality. I am blaming the scientists and the journal.
Revere goes on to describe the problems he has with the paper, its conclusions and the attendant publicity:
This kind of paper and the attendant publicity doesn’t help anyone. Michael Osterholm, Director of the Center for Infectious Disease Research and Policy (CIDRAP) is right to say it is unhelpful for planners, or worse, confusing. There is a sense in which this kind of modeling could even be said to be irresponsible, although I won’t go quite that far. It isn’t the modeling effort itself. It is the promotion of the work that I object to and Ferguson, like many scientists, is promoting his work. Nature also deserves blame here. Nature is probably the most prestigious scientific journal in the world and I hold it in high regard. But they shouldn’t have given any of their precious print real-estate to this paper. They did it because they know it makes news. Nature, like the scientists, was promoting itself. This is a paper that would have been better published in a specialty journal, not in a high profile journal. It does not make a significant and urgent contribution to the scientific literature. It’s just another modeling effort, another data point in that literature.
He also give a two line summary of criticism for the benefit of one of his commentors:
The way it was promoted, overprecise predictions, over interpreted. Less information for planers than implied.
Take a look!
