Not very long ago, if you raised any questions about the rising number of new COVID cases during the Omicron surge, you could be banned from Twitter for posting “dangerous misinformation.” The doom and gloom about records being set for new cases was a regular feature on most cable news outlets, despite the fact that hospitalizations and deaths didn’t seem to be tracking anywhere near the levels being discussed. Now, however, even the mainstream media seems to be coming around to the idea that simply measuring “new cases” each day is not only misleading, but the numbers being posted are almost certainly wrong. (The word “unreliable” is apparently preferred.) With that in mind, some news outlets, including the Associated Press, are issuing new marching orders as to what data should be reported and how it needs to be framed.

The number of case counts soared over the holidays, an expected development given the emergence of a variant more transmissible than its predecessors.

Yet these counts only reflect what is reported by health authorities. They do not include most people who test themselves at home, or are infected without even knowing about it. Holidays and weekends also lead to lags in reported cases.

If you could add all those numbers up — and you can’t — case counts would likely be substantially higher.

For that reason, The Associated Press has recently told its editors and reporters to avoid emphasizing case counts in stories about the disease. That means, for example, no more stories focused solely on a particular country or state setting a one-day record for number of cases, because that claim has become unreliable.

It’s hard to tell if the media outlets being cited in this report are more concerned about the numbers they are displaying being wrong or the poor reception this coverage is meeting with the public. As far as the inaccuracy of the new case numbers goes, that’s been obvious for a while now and many of us have been attempting to point this out. Particularly with Omicron, a shocking number of people have already contracted the disease and recovered from it without ever being tested or even realizing they were ill. People conducting home tests (assuming you can find a test kit) who test positive aren’t reporting their results to anyone but their local doctors. And a lot of positive results are showing up among people who were being treated for something else entirely.

So what is the media doing to adjust to this new reality? The AP has altered its guidelines, telling reporters and editors to “avoid emphasizing case counts in stories about the disease” because that data has become “unreliable.” In one report on Saturday covering the Omicron “explosion,” the Associated Press didn’t even mention new case count metrics. They instead reported on the number of new hospitalizations and the rate of employees calling in sick.

Other news networks are still reporting case counts, but handling them differently. NBC has switched to showing seven-day averages. On Tuesday, CNN was displaying two-week averages. MSNBC (predictably) was the outlier, using a scattershot approach of different averages, with some as low as three days.

None of this, however, addresses the underlying problem with all of these statistics. It’s not just that the numbers are wrong and, frankly, unknowable. It’s that the new case count numbers are meaningless if the vast majority of those testing positive are simply recovering on their own. A more appropriate number to study would be the new hospitalizations and deaths, but as we’ve discussed here previously, even the hospitalization numbers are suspect. They still include huge numbers of “incidental” positive tests, where the patient is being treated for something else entirely but just happens to test positive for COVID as well.

It’s hard to ignore a growing sense of public annoyance and lack of satisfaction with this coverage. The “fear porn” that everyone seems to be waking up to is very real and it’s a strategy that most cable news networks have been employing regularly. But the public has long since started burning out on this subject and the doom and gloom aren’t selling very well anymore. If you can’t figure out a way to collect accurate data on how many people are either dying or requiring intensive care treatment in hospitals specifically for COVID, then perhaps you should give all of this a pass.