There has been some press coverage of an article that appeared in the October 4, 2013, issue of Science called “Social Factors in Epidemiology” by Chris Bauch and Alison Galvani. The article highlights how social factors and social responses are intertwined in biological systems. For example, a perception that vaccines are harmful can cause a drop in vaccination coverage. The point that the authors are making is that mathematical modelers are now creating models that are tailored to include social behaviors into their systems to better predict things like the spread of a disease. Hence, getting clues from social media sources like Fackbook and Twitter is useful. (To read the article you need access to Science but a note about the article is available in Science Daily.)
While it seems nice to again (as the MPE2013 initiative likes to do) point out the usefulness of mathematics I was struck by how little mathematics was actually in the article. The authors did make a strong case that social factors are important in an anecdotal sort of way and it did appear that the mathematical models were network type models, but there seemed to be little of any mathematical substance.
Reading the article I was reminded of the work done by Martina Morris using random network models and the success of those models in predicting HIV spread. Two former blogs, from June 6th and the July 2nd, showcase the exciting work done by her and other mathematicians using random graph models. There have been several other blogs on this site devoted to modeling disease spread. I found all of these more interesting than the Science article. I also wondered how beneficial the work of Morris and others would be for the epidemiology questions asked by Bauch and Galvani. I would speculate quite a bit. I am curious how aware the different researchers are about these and other developments and ironically, if somehow, social behavior of a different sort is at play here.