An effect size is a difference between means which has been adjusted into units of standard deviations, so that entirely different data sets can be compared to one another without violating statistical principles.
A standard deviation is just a measure of how spread out the data are, and roughly represents an average distance of data from the mean.
When 33 nations reported their excess death rates for an acute respiratory disease (influenza), the excess death rates in the age 65 to 74 bracket spanned a range that was 15-fold (highest elderly flu death rate was 15 times higher than the lowest).
But examining the top 16 and bottom 16 as if they were two groups (two samples), revealed an upper limit on the expected differences in excess deaths by natural causes.
For deaths by natural causes, such as deaths by infectious diseases, an upper limit on the expected difference of mean excess death rates is a difference of means which amounts to 2.3 standard deviations of difference.
Alarmingly, the actual excess death rates of the top 16 nations in 2021 were much higher than the excess death rates of the bottom 16 nations — indicating that excess deaths in the top 16 nations are not due to natural causes (which are expected to vary, from sample to sample, by up to 2.3 standard deviations of difference).
Further research will be required in order to understand the excess deaths in the top 16 nations, because evidence suggests that they are not due to an infectious disease (i.e., a natural cause).
Reference
[Effect size of difference of mean flu excess death rates (age 65-74 bracket) for top 16 nations versus mean of bottom 16 nations, after Hedges Correction, was 2.3] — Iuliano AD, Roguski KM, Chang HH, Muscatello DJ, Palekar R, Tempia S, Cohen C, Gran JM, Schanzer D, Cowling BJ, Wu P, Kyncl J, Ang LW, Park M, Redlberger-Fritz M, Yu H, Espenhain L, Krishnan A, Emukule G, van Asten L, Pereira da Silva S, Aungkulanon S, Buchholz U, Widdowson MA, Bresee JS; Global Seasonal Influenza-associated Mortality Collaborator Network. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. Lancet. 2018 Mar 31;391(10127):1285-1300. doi: 10.1016/S0140-6736(17)33293-2. Epub 2017 Dec 14. Erratum in: Lancet. 2018 Jan 19;: PMID: 29248255; PMCID: PMC5935243. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935243/
Pull-quote:
“EMR[excess mortality rate]-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from ... 2·9 to 44·0 per 100 000 individuals for people aged between 65 and 74 years ... . We estimated that 291 243–645 832 seasonal influenza-associated respiratory deaths (4·0–8·8 per 100 000 individuals) occur annually.”