For any individual study you can validly say that you think the estimate is too low, or indeed, too high, and give reasons for that. For instance, you might say that your sample was mainly young people who tend to be healthier than the general public, or maybe that the diagnostic tools are known to miss some true cases.
But when we look at reporting as a whole, it almost always says the condition is likely to be much more common than the estimate.
For example, have a look at the results of this Google search:
"the true number may be higher" 20,300 hits
"the true number may be lower" 3 hits
I often tell folks that the key to understanding behavior is to understand incentives. The media as institutions have incentives to sensationalize and scare (it sells papers) and as individual reporters have incentives to magnify the importance of whatever story he or she is working on.
But what I found really interesting was how the Observer effect comes into play here. Wikipedia has this brief definition of the observer effect:
In physics, the term observer effect refers to changes that the act of observation will make on the phenomenon being observed. This is often the result of instruments that, by necessity, alter the state of what they measure in some manner.
Click on the Google hit numbers above. I get 42,700 and 5,360 respectively, the increase presumably due in part to this article and links to it. Its impossible to report on patterns in Google searches without the very fact of such reporting affecting what is being measured.