Back

Joinpoint Regression to Determine the Impact of COVID-19 on Mortality in Europe: A Longitudinal Analysis From 2000 to 2020 in 27 Countries

Rovetta, A.

2022-01-21 epidemiology
10.1101/2022.01.19.22269576 medRxiv
Show abstract

The novel coronavirus disease 2019 (COVID-19) represented the most extensive health emergency in human history. However, to date, there is still a lot of uncertainty about the exact death toll the pandemic has claimed. In particular, the number of official deaths could be vastly underestimated. Despite this, many conspirationists speculate that COVID-19 is not a dangerous disease. Therefore, in this manuscript, we use joinpoint regression analysis to estimate the impact of COVID-19 in 27 European countries by comparing annual mortality trends from 2000 to 2020. Furthermore, we provide accessible evidence even for a non-expert audience. Siegel (A1) and Holm-Bonferroni (A2) approaches were employed to assess the significance of the results separately. In conclusion, these results estimate that COVID-19 increased the overall mortality in Europe by 10% (A1: P < .001, A2: Adjusted P = .001). In 16 out of 27 countries (59.3%), the excess mortality ranged from 7.4% to 18.5% (A1: P < .003, A2: Adjusted P < .040). Comparison of the excess mortalities distribution to the null counterfactual showed that the mortality increase was highly significant across Europe (Adjusted P < .001).

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.