Exponential distribution of large excess death rates in Europe during the COVID-19 outbreak in the spring of 2020
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Abstract
Excess death rates E during the spring of 2020 are computed in N = 540 level 3 European territorial units for statistics —NUTS3 in Belgium (40), France (96), Italy (110), Netherlands (44), Spain (50), Sweden(21) and United Kingdom (179)— from 2020 provisional week deaths, the population numbers for 2020, and observations in previous years (reference or baseline), all of them obtained from Eurostat web page.
Excess death rates are classified in three tiers. Largest 27 excess death rates (tier 1, E > 1721 × 10 −6 ) were distributed exponentially with empirical complementary cumulative distribution function (empirical survival function) S following S ∝ 2 − E/ε with ε 1 = 958(42) × 10 −6 . Tier 2 (the next 52 largest excess death rates, E < 1142 × 10 −6 also distributed exponentially with ε 2 = 379.5(89) × 10 −6 . Tier 3 (smallest 460 excess death rates) were distributed normally.
The results suggests that when, within some regions, the outbreak is above a threshold, interaction with neighbouring region become less relevant and the outcomes —excess death rates— become exponentially distributed as it happens with independent events.
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SciScore for 10.1101/2020.09.20.20198283: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2020.09.20.20198283: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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