Early Phase of the COVID-19 Outbreak in Hungary and Post-Lockdown Scenarios

  1. Gergely Röst
  2. Ferenc A. Bartha
  3. Norbert Bogya
  4. Péter Boldog
  5. Attila Dénes
  6. Tamás Ferenci
  7. Krisztina J. Horváth
  8. Attila Juhász
  9. Csilla Nagy
  10. Tamás Tekeli
  11. Zsolt Vizi
  12. Beatrix Oroszi

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Abstract

COVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a considerable reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

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  1. Version published to 10.3390/v12070708
  2. ScreenIT

    SciScore for 10.1101/2020.06.02.20119313: (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

    Software and Algorithms
    SentencesResources
    All methods were implemented under the R statistical environment version 4.0.0 [20] using packages ggplot2 version 3.3.0 [21] for visualization, data.table version 1.12.8 [22] for data manipulation and shiny version 1.4.0.2 [23] for creating an interactive dashboard to carry out epidemiological analyses online (available in Hungarian [24]).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your code.

    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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  3. Version published to 10.1101/2020.06.02.20119313v1 on medRxiv