Reciprocal association between voting and the epidemic spread of COVID-19: observational and dynamic modeling study

  1. Jean-David Zeitoun
  2. Matthieu Faron
  3. Sylvain Manternach
  4. Jérôme Fourquet
  5. Marc Lavielle
  6. Jérémie H Lefèvre

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Abstract

Background

Whether voting is a risk factor for epidemic spread is unknown. Reciprocally, whether an epidemic can deter citizens from voting has not been often studied. We aimed to investigate such relationships for France during the coronavirus disease 19 (COVID-19) epidemic.

Methods

We performed an observational study and dynamic modelling using a sigmoidal mixed effects model. All hospitals with COVID-19 patients were included (18 March 2020–17 April 2020). Abstention rate of a concomitant national election was collected.

Results

Mean abstention rate in 2020 among departments was 52.5% ± 6.4% and had increased by a mean of 18.8% as compared with the 2014 election. There was a high degree of similarity of abstention between the two elections among the departments (P < 0.001). Among departments with a high outbreak intensity, those with a higher participation were not affected by significantly higher COVID-19 admissions after the elections. The sigmoidal model fitted the data from the different departments with a high degree of consistency. The covariate analysis showed that a significant association between participation and number of admitted patients was observed for both elections (2020: β = –5.36, P < 1e−9 and 2014: β = –3.15, P < 1e−6) contradicting a direct specific causation of the 2020 election. Participation was not associated with the position of the inflexion point suggesting no effect in the speed of spread.

Conclusions

Our results suggest that the surrounding intensity of the COVID-19 epidemic in France did not have any local impact on participation to a national election. The level of participation had no impact on the spread of the pandemic.

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  1. Version published to 10.1093/eurpub/ckab140
  2. ScreenIT

    SciScore for 10.1101/2020.05.14.20090100: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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: We detected the following sentences addressing limitations in the study:
    Our report has a main limitation, namely its ecological design. We could not access individual data. We cannot exclude the possibility that our results might be confounded by factors that were not measured and cannot establish (or exclude) definitive causality. In conclusion, we did not find any local effect of the intensity of the COVID-19 epidemic in France on participation to a national election for mayor designation. While there had been a concern that participation could accelerate virus transmission, we did not measure any statistical association between participation at a local level and subsequent evolution of the epidemic. Our results do not support the election as an interfering factor for outbreak outcome.

    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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  3. Version published to 10.1101/2020.05.14.20090100v1 on medRxiv