Analyses of academician cohorts generate biased pandemic excess death estimates

ABSTRACT Objective Death data from cohorts of academicians have been used to estimate pandemic excess deaths. We aimed to evaluate the validity of this approach. Study design and setting Data were analyzed from living and deceased member lists from Mainland China, UK and Greece academies; and Nobel laureates (and US subset thereof). Samples of early elected academicians were probed for unrecorded deaths; datasets overtly missing deaths were excluded from further analyses. Actuarial risks were compared against the general population in the same country in respective age strata. Relative incidence risk increases in death in active pandemic periods were compared to population-wide pandemic excess death estimates for the same country. Results Royal Society and Academy of Athens datasets overtly missed deaths. Pre-pandemic death rates were 4-12-fold lower in the Chinese Academy of Engineering (CAE) versus respective age strata of the Mainland China population. A +158% relative increase in death risk was seen in CAE data during the first 12-months of wide viral spread. Both increases (+34% in British Academy) and decreases (-27% in US Nobel laureates) in death rates occurred in pandemic (2020-22) versus pre-pandemic (2017-2019) years; point estimates were far from known excess deaths in the respective countries (+6% and +14%, respectively). Published excess death estimates for urban-dwelling Mainland China selectively analyzed CAE, but not another Chinese academy (Chinese Academy of Sciences) with half the pandemic death rates. Conclusion Missingness, lack of representativeness, large uncertainty, and selective analysis reporting make data from academy rosters unreliable for estimating general population excess deaths.