I did a search but couldn’t find another thread on this, apologies if I’m rehashing.
IANAS, obviously, but I’m fairly good with math. Every morning I check the numbers for Ontario to see how many new cases have been detected the previous day. For two weeks now Ontario has been under 200 new cases a day. During our third wave earlier this year, we were in the thousands; at one point in April our 7-day average was 4,341 new cases. So obviously things are much better, as we enter the second week of the third stage (of the seventh son…) of reopening.
But it took me a long time to figure out that the positivity rate was just not getting as much attention. As we were climbing down from those awful heights, there’d be an occasional spike again, but as I looked at the daily positivity rate, it was steady and getting lower. The news always mentions how many tests were conducted the previous day. I feel like a doofus for not noticing it earlier, but I finally noticed that some of the spikes were on days when there had also been a sudden jump for whatever reason in the number of tests carried out. Yet a big chunk of provincial planning around re-opening was based partly on the number of shots in arms, but also the daily cases. Which now felt to me like they were missing the point. One day the testing goes up 70% and the day’s case number goes up only 20%…that’s a good thing, despite the hyperbolic “we had a jump in case numbers.”
This feels like a Rant of the Obvious. But I guess this is my question to those better-versed in epidemiology than I: should the media be focusing more on positivity rates than actual new cases? Would that give a more accurate indication of the current spread of the virus in the province? Is it media laziness (duh) that a solid number is an easier sell than a percentage of an ever-changing sample size for a news story?