EuroMOMO euromomo.eu/graphs-and-maps Excess Deaths from 2020 Week 8 now match reported COVID Deaths @JHUSystems perfectly (better than 2%). In earlier weeks the reported deaths were lower. Not sure why? It allows me to do this in depth analysis & comparison with EuroMOMO influenza.
Analysis of Europe's Excess Deaths is hard: EuroMOMO provides beautiful plots; data requires hand-recorded mouse-overs. COVID19 2020, Weeks 08-19 & flu 2018, Weeks 01-16 is relatively easy for all age ranges (totals 153,006 & 111,226). Getting Dec. 2017 flu peak is very tricky.
Should be easy as mouse over gives two values a week: Actual death count & Baseline value. Tests on COVID19 peak gave total of 127,062 deaths & not 153,006. Plotting table & superimposing real plot showed why. Wrong Baseline values are actually 'Substantial increase' values!!
Requiring two COVID19 death counts to match means reducing Baseline value by 23,774/12=1,981. Mouse-over 2017 weeks 46 to 52 gave table below. Negative excess death meant 2017 flu began Week 49 not 46. We tried to get Age Range data for 2017 but table just use 2018 flu data.
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As someone who broke the news to Israeli leaders on Sweden’s handling of COVID-19 in Mar. 2020, I am so distressed to be reading this now m.ynet.co.il/articles/hj30k…
When will Homo Sapiens realize that we can never stop a tiny virus & re-engineer human biology by force not smarts?
Please note that the two translation are automatic. I give independent results from Microsoft and Google. The original is in Hebrew.
Taking this opportunity to rejoice in machine translation. It it so worthwhile to get used to its quirks.
Fortunately age-adjusted excess death in Israel for the 75 weeks from 1-Jan-20 to 6-Jun-21 is almost as small as that in Sweden (<2% of natural death in 75 weeks)
Economic, social, medical & educational cost to Israel likely higher than to Sweden.
2/8 Rather than make plots of one measure against another, we get the correlation coefficient of all pairs of measures.
Correlation coefficient, CC, of A to B is same as CC of B to A so table is symmetric. Correlation coefficient of A to A is always 1; it is whited out here.
1/7 Excess death (E) in any period is the difference between the actual all-cause deaths and those that are expected. Expected deaths in the current year, c, can be calculated in many ways. Easiest is to use the data from a few recent years as a reference (we use, 2017 to 2019).
2/7 Data can be used in 3 ways to calculate expected deaths. (1) as average death in the reference years. (2) as average corrected for the change in total population. (3) as average for each age band corrected for its population, what we call age-adjusted.
We use 5 age bands.
3/7 (1) If D(i) is death in reference years i, then expected death in year c is E(c)=average[D(i)]. (2) If P(i) is population; E(c)=P(c)*average[D(i)/P(i)]. (3) If (P(i,j) is population of age band j in year i, D(i,j) the corresponding death; E(c,j)=P(c,j)*average[D(i,j)/P(i,j)]