we are inundated with statements about COVID deaths, but how often have you seen charts showing COVID deaths in context of all deaths? Not very often, if ever.

I've done one for Ontario (where I live). Population 14.8 MM.
2/ All-causes death rates are ~2100. Total COVID deaths to date ~2500. Here is diagram showing COVID deaths (black) stacked with (estimate of) all other deaths.
3/ in Ontario (as with CDC), all-cause death data is appalling delayed. Thus, reported 2020 all-cause values substantially under-state eventual results. Data is updated monthly (latest Nov 26). Deaths trend up with increasing population; recent "decline" is reporting artifact
4/ because of abysmally delayed reporting of All Causes deaths, number of still unreported All-Cause deaths from April on is, for most weeks, greater, even much greater, than COVID deaths. So there's uncertainty in my figure.
5/ the table below shows estimation problem. In Oct and Nov releases by Statistics Canada, tota; increments to weeks in July were over 500 deaths per week and about 200 in April-May. These are more, much more than weekly COVID deaths.
6/ I don't understand why public health agencies are so slow in reporting All Cause deaths. These bureaucratic delays seem very unfair to policy makers, who ought to be provided accurate and timely All Cause death estimates up to the current month at least.
7/ UK has very timely All Cause death information. Its spring COVID spike was very dramatic and yielded corresponding All Cause spike. So YMMV.
8/ I just located a Statistics Canada dset which estimates "excess deaths" in 2020 by province to Sep 5 (so far). During summer, Ontario had lower than usual death rates. To Sep 5 YTD, we had ~700 "excess" deaths, about 1/3 number of COVID deaths.
9/ incidence of COVID in Ontario (pop 14.8MM) has (luckily) been much less than comparable US states (NY,PA,IL,MI), so one can't extrapolate from our experience to other jurisdictions.
10/ in Ontario, it seems plausible hypothesis that COVID "competes" with "ordinary" pneumonias as Grim Reaper for very old people. Most deaths in Ontario have been of people over 80 and over 90.
11/ I'm reminded of a saying from my youth about pneumonia being the "old person's friend". Phrase attributed to Sir William Osler, a famous Canadian physician and a co-founder of Johns Hopkins Medical School.
12/ to be clear, I repeat that I'm all in favor of getting rid of COVID, but, in respect to lockdown policy, the relevant damage to be assessed seems to me to be excess deaths and excess hospitalizations - not casedemic.
13/ more progress on representing Ontario data.
StatsCan 2020 estimates to Sep 5 (www150.statcan.gc.ca/t1/tbl1/en/tv.…) combined with 2010-2019 reported (www150.statcan.gc.ca/t1/tbl1/en/tv.…). Shows anomalously LOW weekly deaths in summer. (Caveat: all-cause reporting very slow and estimate uncertain)

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More from @ClimateAudit

29 Nov
@kylenabecker @Barnes_Law here's one pushback. You say "Yet, Biden leads in Michigan, Pennsylvania, and Wisconsin because of an apparent avalanche of black votes in Detroit, Philadelphia, and Milwaukee."

Trump won more votes than Clinton in Philadelphia. Avalanche was in (white) suburbs.
@kylenabecker @Barnes_Law 2/ while there was obviously little enthusiasm for Biden - not enough to bother going to physically vote - there may have been enough enthusiasm to fill out a mail-in ballot when Dem collector came to harvest.
@kylenabecker @Barnes_Law 3/ to be precise, there was an avalanche for Biden in Philadelphia, but there was bigger avalanche for Clinton. So nothing anomalous about Philadelphia avalanche. Swing to Biden occurred b/c he did better than Clinton in liberal suburbs.
Read 4 tweets
28 Nov
many people have observed the disconnect between resurgent and exacerbated COVID cases this fall without commensurate death increases. Here is plot of detailed Toronto information (pop 3 MM) color coded by age subgroup, paneled to Young, Middle and Old.
2/ nearly all of the present surge in cases is among 20-60 year olds, but this component of surge has had negligible impact on hospitalizations and even less on deaths (almost non-existent in this cohort)
3/ main factor in reduced hospitalizations and deaths in present surge appears to be lower COVID case rates among over-80s thus far as compared to spring.
Read 8 tweets
28 Nov
tho ughtful comment on Georgia filing from knowledgeable Oregon Dem. It's hard to believe that a purportedly democratic nation could make such a mess of electoral procedures.
abandonment of/failure to carry out verifiable election processes in battleground states has left US courts in an absurd situation: it's impossible for them to have any founded confidence either that election wasn't stolen or that it was stolen.
in a local election, solution would be easy: a do-over run-off election in which rules obeyed. But this doesn't appear possible given mandated electoral college date cutoffs. What a mess.
Read 4 tweets
26 Nov
before accepting calculations from anonymous (or even non-anymous) sources, insist on a citation to original data so that it can be checked. I'm told (but haven't seen reference by Werise) that this comes from NYT json data static01.nyt.com/elections-asse…. I'll comment on this data.
2/ first, I extracted the data into a csv format using the R package jsonlite. I hadn't used this program before but it worked easily first try.
3/ A first and important problem with this dataset: it does NOT give actual vote counts in integers. It gives total votes and Trump and Biden share only to 3 digits. As a result, candidate counts are accurate only to nearest ~3000. Calculated increments can be off up to ~6000.
Read 14 tweets
12 Nov
I'm re-examining MI Oakland County from first principles, since I agree that similarity of 2016 and 2020 doesn't preclude manipulation in both elections, tho I think that it counts against it.
2/ Technically, Shiva's comparison of total margins to straight ticket margins is (at best) "exploratory" - a term of art in statistics. We don't know anything about the properties of this statistic. So Shiva's claim to have PROVED manipulation is unjustified armwaving.
3/ Having said that, merely showing (as I did last night) that there were similar patterns in 2016 Oakland Co doesn't end the discussion, as commenters rightly observed, since we still don't really understand the result.
Read 16 tweets
12 Nov
there's been considerable publicity about Dr Shiva's characterization of the plot shown at right for Oakland County MI 2020 results. However, Oakland MI 2016 plot in same format yields nearly identical results. So, unfortunately, his plot proves nothing.
2/ Dr Shiva said that the downward slope PROVED use of an algorithm to tamper with data. It doesn't. Slope has something to do with straight ticket vs all vote results; and is not due to malicious algorithm.
here's my understanding of phenomenon. Straight Ticket Republicans obviously voted for Trump. So difference arises from balance between "Paul Ryan" non-Trump Reps and "50 Cent" pro-Trump Dems. Presumably pct of Paul Ryans vs 50 Cents increases in strongly R precincts.
Read 5 tweets

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