Reopening Georgia: What the data (doesn’t) show

This post should be short.  Instead of trying to figure out what the crappy data indicates, it should be “the data says X so we should do Y.”  While there are a couple of brighter spots, the overall COVID-19 testing, data collection, and reporting in this country continue to be nothing less than a MAJOR EMBARRASSMENT.  Red states, Blues states, forget the tribal poo-flinging.  Perhaps one party is worse than the other, but it’s the difference in degree, not in outcome: both parties have failed. So instead of having good information to make decisions with, we spend lots of time arguing over the “data.”  And if everyone wants to be intellectually honest, based on the “data” we have, you could in fact argue for a range of options from maintaining strict mitigation measures all the way to “why bother, back to normal.”  Which suits the political leadership just fine: if the data were clear, which policies would work best might be clear and they might have to agree on something, rather presenting stark contrasts which keep you angry and divided.

Let’s look at Georgia, since it was the first to “reopen”, and selfishly because I live here.  So instead of having good information on which to base the reopening decision, and thence if the reopening decision was sound, we have to read entrails and cast runes to try to figure things out.  But what it shows isn’t very comforting.  Right now I’m focusing on the reported number of hospitalizations.  Georgia’s data utterly inconsistent.  They are reporting 15 new COVIDI19 hospitalizations yesterday.  But the *total* number of hospitalizations went up by 129.  Factor of 10 discrepancy.  Which is right?  Probably neither one.  So let’s get another thing clear: reporting delays on top of the way the virus progresses through the population, means that trying to figure out the consequences of decisions made two weeks ago is frustrating at best, and potentially a less a waste of time.  But … let’s give it a shot anyway.

Here is a plot of the changes in reported hospitalizations sorted by day of week.  The “X” axis is weeks since March 19th (which were all zeros). The “Y” axis is the change in the total hospitalizations.  Why by day of week?  Because for a variety of reasons of both behavior and reporting, there is a very clear bias in reporting between the days of the week.  So you can’t compare Tuesday to Monday, much less a weekday like Monday to Sunday.  So here I’m just comparing Sundays to previous Sundays, Mondays to previous Mondays, etc.  In theory, if the reopening is causing a spike in dangerous infections (those requiring significant medical care resulting in hospitalization), it should show up in this data.

What we are seeing isn’t comforting.  We have three straight days of relative increases.  And 4 of the last 5 days saw above normal increases (Friday was a draw).  Conclusions?  The trends don’t look good, but again this is very noisy data, so we will have to continue to watch carefully.

What does it mean to you?  If you are re-engaging in everyday life, please be careful.  Maintain your distance where possible, wear a mask when you cant (for others more than yourself).  If you feel any symptoms stay home.  Good hand hygiene is absolutely essential. Minimize contacts with surfaces.   If you go out shopping, please please please DON’T PICK UP EVERY ITEM IN THE BIN!  I’m looking at you, idiot who picked up and examined every bag of mixed veggies at Publix last week!

One thought on “Reopening Georgia: What the data (doesn’t) show

  1. Yes I am disappointed by the publics lack of social distancing, wearing masks, etc. Georgia is blowing the reopening. Soon we will have overflowing hospitals and morgues. Georgia’s rate of hospitalizations changed by almost 150% over the last week

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