Cov19 analysis for State of RI. RI was hit hard in the Spring like other nearby states. Are we setting up for round 2 or is something else happening? Read on. 1/x
First we look at testing. RI breaks out new tests and repeat tests. Note testing is up huge since Spring, but 75% of the tests are now retests. We can see the jump in retests coinciding with colleges and schools starting up. Presumably most of these retests are mandated screening
We are going to ignore “cases” as a metric because anyone paying attention knows that cases alone is useless. Test positivity rate though can be useful. Here we see that first time test positivity is up steeply while repeat test positivity is effectively nil.
Interestingly, 1st time test positivity tracks hosp admissions very closely. Chicken? Egg? Is everyone in the hospital getting a positive test? Or is that why they are admitted? Note that RI counts any + test in a hosp as a C19 hospitalization. So are they hosp with or from?
Now we look at the familiar hospital and icu census along with deaths. Here we start see that something is different now. Deaths have barely budged even tho hosp started ramping 7 weeks ago. In Spring, deaths lagged hosp by 2 weeks. This is good news. Icu also looks better.
Might there be some new reasons for rapidly growing hosp census that are not due to severity of illness? Note the remdesivir approval date. Treatment requires hosp of 3-10 days and we see an apparent inflection there.
Also, a recent article indicates hosps are having difficulty discharging elderly and psych patients. LTC resisting, and patients need 2 neg tests. Psych care is full (wonder why). wpri.com/target-12/dive…
So how bad is the current hosp census versus average? We know hosp goes up this time of year every year. We also know there has been near 0 flu. Brand new analysis from @Rational_Ground crew indicates we are about 100 patients or 7% above average in hosp census. Not bad.
Another important metric is the growth rate of hosp, icu, and deaths. The initial slope determines the ultimate severity of these curves and slopes are way down vs Spring:
Hosp 3.7/day vs 8.2/d
ICU 0.5/d vs 2/d
Deaths 0.1/d vs 0.7/d
So icu growing 4xslower and deaths 7xslower.
Hopefully these trends indicate that severity is much reduced vs the Spring, and we will not see much in the way of excess fatalities. The Spring curve was a classic Gompertz epi curve. What we are seeing now is imo a seasonal flare from a now endemic virus.
Also, repeat surveillance testing seems to be accomplishing little other than wasting time and funds and creating a percentage point of likely false positives. Also note that any of these metrics are likely juiced by overly sensitive tests.
Finally, in those states (e.g., ND) that do separate hosps “from” C19 vs hosps “with” C19, about 1/3 are “with.” So we may well be 1/3 lower than reported as far as folks in the hosp *because* they have c19. /end
2 more graphs to add. First we have ICU census as a percentage of hospitalizations. No significant uptick yet.
Finally (again) a few folks wanted to see case counts. Caveats: cases are not infections, they are not sick people. They may be, but they may also be an artifact. In any case we can clearly see that ICU and especially deaths have completely detached from cases and hosps vs Spring
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Home with family and friends for the Holidays? Not if Task “Force” member Dr Birx has her way. Welcome to the “It’s time for Dr Birx to go” magnum opus.
“home with neighbors and friends may not be a safe place in specific communities.”
That’s one of the key messages of Dr Birx’s talk in Boston Friday. Birx has now officially gone completely “off the reservation” as she tours colleges and spreads a special kind of COVID crazy.
It will be clear when reading the low-lites of her talk that Birx has never left April.
Birx is a non-elected appointee who now feels she has the right to tell you to shun and be suspicious of friends and neighbors. You know what’s coming next: “stay away from your family.”
A new way to look at lockdown severity and its effects. We have all heard of the Oxford lockdown stringency index described here bsg.ox.ac.uk/research/resea… which uses 17 indicators to come up with a lockdown stringency score. What if we looked at cumulative stringency? 1/8
By cumulative stringency I mean the area under the stringency curve. I decided to look at the period from Feb 15 to June 30 2020 and sum the daily stringency scores. The max score for this 137 day period would be 13700 = 137 days * 100 max score. 2/8
As with my prior studies I looked at Western Europe. First the cumulative stringency scores, where Sweden is lowest. No surprise, but note Finland Iceland and even Norway score low. 3/8
Imagine if our “leaders”, “experts” and a majority of the population were this rational. Written by a fund manager whom I will not cite unless he requests. 1/8
“Honestly, the policy response is not hard once you accept that (1) this is mitigation not suppression, (2) we have a clear understanding of who is vulnerable and who is not, and (3) 30-40% of the population will be infected (with disease break point at 15-20%)” 2/8
“...regardless of what we do.
If you are vulnerable (old, diabetes, obese, etc.) – take every precaution. Test frequently. Have pulse oximeters to detect if 02 levels are falling. Do all you can to minimize person-to-person contact – and to keep fit and healthy.” 3/8
More plots for your consideration, focusing on W. Europe. The first looks at Oxford lockdown stringency. Did it affect the maximum daily deaths/million? The maximum stringency certainly did not for these 18 countries. In fact there is a weak correlation in the wrong direction. 1/
Meaning that the countries with harshest lockdowns had higher max daily deaths/M. Digging further, let’s look at the first day each country saw significant fatal infections. I lagged reported deaths (7d ma) by 25 days to approx day of infection. Then... 2/
I plotted the first day of 2020 where infections lead to 0.5 deaths/M. Note that the earlier the pandemic began ramping up in a country, the worse the max daily deaths/M. Not a bad R^2. 3/
Sweden: the undeserved battle ground of the pandemic mess. Thankfully we do have at least one country that did things differently to help us learn what really matters in our policy responses. Folks love to cherry-pick pairwise comparisons to support their views. Maybe tho ... 1/
... policy actions don’t matter much at all as far as the virus’ trajectory. Which if true would mean we ruined economies, mental health and so much more for little if any benefit. So I decided to do some analysis using OWID and Oxford Lockdown Stingency data to look at this 2/
I plotted daily Cov19 deaths per Million using a 7 day ma on a log scale to show growth rate. And then I shifted this curve 25 days earlier to approximate deaths by day of infection. I also plotted lockdown stringency to look for any correlation to virus trajectory. 3/