Do you have the stats for the % that tested positive vs. other days? Just curious if it is related to any increased testing numbers or if the % of positive tests have increased as well.
I don't. Closest thing to that in the dataset I'm using would be the total tested trends by day vs growth in case counts.
Here's the dataset I'm using.
You can put total tested right next to number of cases per day, but obviously the Y-axis is a different scale as they're trying to capture trends. From the analysis I've done, which is crude and not very granular, there's obviously a correlation between total tested and the growth in case counts (as one would expect), but it's not clear how well that correlation maps overall to the growth in cases.
I suspect that our initial peaks around April 8th - April 13th reflect a number of backlogged cases as testing was really just starting to ramp up and scale. I base this conclusion on the fact that testing growth rate was nearly flat between April 8 - April 12th while cases started peaking out. Although not proven, that seems to indicate to me that the case count peaks were more a reflection of a backlog of pending tests being cleared than a growth in testing. Otherwise, you'd have to assume an excessively high positive test rate which I don't think is supported by the data. I presume the % positive test rate was rather high during the time, however, as testing wasn't growing that quickly, and those initially tested were more likely to have the virus as the screening criteria in place (because of testing scarcity) was more stringent.
So, I would tend to agree that part of why we're seeing a new peak in cases is because of recent growth in test capacity. However, if you look at the slope of the trend for both tests completed and % cases, you'll see a fairly consistent slope for case counts whereas tests completed is much less consistent and has plateaus/sharp increases.
My ultimate conclusion is that we weren't testing enough previously and were probably underestimating case counts, and now we're about to see a more realistic view of positive cases because testing capacity has grown enough that the heavy rationing that was in place is no longer necessary.
It also shows why developing ACCURATE antibody tests (obviously this test type isn't currently reflected in the dataset I'm using) that have much better sensitivity and specificity are necessary. Improving the antibody tests is necessary to achieve lower rates of false positives and negatives otherwise they're just not trustworthy enough to use to guide decision-making. Actually, even the PCR tests still have problems with false negatives/positives.
Bottom line: we are not where we need to be yet as it pertains to testing. We're making good progress on overall testing growth and availability, but we also need to simultaneously increase the accuracy of both the PCR and antibody tests to be able to have a clear understanding of how the virus is spreading throughout the community. We'll get there -- but improving accuracy requires time and experience and definitely involves some trial and error as we've seen.
Ultimately, I don't know that we can conclude that the recent peak is an ominous sign or an aberration until we see several more days of data (or even a week). Which is why I mentioned that as a caveat in my original post about the new peak we experienced yesterday. There's a lot of variables involved, so there's a number of things that could explain the increase. Until more data is available, I'm not at all confident any conclusion can be made other than we need to watch the data closely in the coming days to see if case counts continue to rise compared to the previous average per day, and how that correlates with total tests completed.