Even if the data was misreported, which is a possibility, censoring or deleting it in some way is the worst option. Lets say Florid's growth for that month was 30%. But because of bad reporting it thought it had a growth rate of 15%, until the end of the month when all of the missed cases were reported. That spike will not be accurate, but just deleting it would make it look like Florida still had a 15% growth rate. Reviewing the full months data to correct those issues would give the clearest report, but reporting the raw data is more honest than just deleting the anomaly.

The trade off is between measurement bias and selection bias. Typically you want to be dealing with measurement bias and not selection bias, since the latter is often impossible to account for.

You are correct that it is preferable to report the raw data, but it is more than just "honest"! Even with that data `incorrectly` on the wrong day, when binned as a full month the growth rate will be correct. That is, the data is now more correct than if the late reported deaths were not included.

I believe this is effectively the same as Intention to Treat Analysis (https://en.wikipedia.org/wiki/Intention-to-treat_analysis).

> "it does not seem plausible that people were spinning deaths reported May 5 as being due to the May 4 reopening."

You've got to be kidding. Here on Hacker News people were buying the very same sort of spin from an article about the 1918 flu epidemic and San Francisco (I think that was the city). I've seen lots of people on either "side" of this issue buy into absolutely outrageous claims that are clearly just spin.

For example, weeks ago somebody on the "open up now" side graphed the data from the CDC showing that deaths around the country weren't increasing, but in fact plummeting. The page with the data is explicit in multiple places that the data is incomplete for many weeks into the past. Then, weeks later I heard that the official death toll from Covid-19 had been cut by 50%. When I asked for a source, it was that same page with data that lags by up to 8 weeks.

Another example: somebody on the "panic now" side reported (in the news, IIRC) that Michigan's positive test ratio was skyrocketing and had reached 47%. The only table that contained positive vs negative test results clearly had not been reporting the negative tests at all. They should have just gone ahead and claimed that 100% of the tests in MI were positive, since that was what the table showed for the previous 5 days.

The fake news around Covid-19 has been driving me absolutely crazy on both sides.

Framing two sides as "open up now" and "panic now" does not help your case.

I think putting both viewpoints down basically implied he was impartial and and talking of those who had an agenda.

It helps reduce verbiage.

Calling “stay in lockdown” a panicked response seems like picking a side to me.

But I didn’t call it that. I called lying about what was happening in MI in order to make people think things were way worse than they really are, the “panic now” side.

Do you not agree that such lies are bad? Perhaps you think the end justifies the means, but in that case, you might want to consider what telling lies does to the public’s perception of your trustworthiness when you tell them it’s necessary to stay in lockdown.

And then there’s all the real reasons not to panic. Because hoarding is bad for everybody. Because failing to seek necessary medical care for your ruptured appendix because you’re afraid of getting Covid-19 as a 28-year old would be pretty bad. And on and on.

What possible good do the lies I described above accomplish?

You make a good point. I'll revise my statement:

It does not seem plausible that reasonable people would suggest suppressing data just because some people tried to spin deaths reported May 5 as being due to the May 4 reopening.

If information sources in either of the examples you gave were later suppressed due to the extreme spin put on them, please let me know.

For the curious: Michigan's positive test rate on 19May2020 was: 435 new cases/12726 tests = 0.034, or 3.4%. Which is pretty good and means they are finding most cases within the section of the community they are testing.

For comparison, Australian testing rates (some of the best in the world) are around 0.5% to 1% in the week after the peak of cases.

Why does everything in the US always have to be about two strictly opposing sides?

First there is the assumption that you have to "pick a team", and that every voiced opinion also has done so.

Then there is the assumption that the voices from the far extremes of these sides are the ones worth listening to.

The fact that most people agree (or did at some point) about how we should respond to Covid-19 has no bearing on my comment that I can figure out.

Using date-of-death based statistics does indeed cause a misleading drop-off in the last few days - there's no perfect way of reporting uncertain information like this in real time - and I should probably have noted that, yeah, but the decline was longer term than that. Though in any case, it looks like my guess was wrong and the problem with Florida stats was even more embarrassing than that. Like, I'd assume if the supposed data manipulation had to do with drumming up support for reopening it'd have some relevance to what was happening now...