Early Phase of the COVID-19 Outbreak in Hungary and Post-Lockdown Scenarios
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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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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 Sentences Resources 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]). ggplot2suggested: (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 …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 Sentences Resources 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]). ggplot2suggested: (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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