The Institutional and Cultural Context of Cross-National Variation in COVID-19 Outbreaks
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Abstract
The COVID-19 pandemic poses an unprecedented and cascading threat to the health and economic prosperity of the world’s population.
Objectives
To understand whether the institutional and cultural context influences the COVID-19 outbreak.
Methods
At the ecological level, regression coefficients are examined to figure out contextual variables influencing the pandemic’s exponential growth rate across 96 countries.
Results
While a strong institutional context is negatively associated with the outbreak (B = −0.55 … −0.64, p < 0.001), the pandemic’s growth rate is steeper in countries with a quality education system (B = 0.33, p < 0.001). Countries with an older population are more affected (B = 0.46, p < 0.001). Societies with individualistic (rather than collectivistic) values experience a flatter rate of pathogen proliferation (B = −0.31, p < 0.001), similarly for higher levels of power distance (B = −0.32, p < 0.001). Hedonistic values, that is seeking indulgence and not enduring restraints, are positively related to the outbreak (B = 0.23, p = 0.001).
Conclusions
The results emphasize the need for public policy makers to pay close attention to the institutional and cultural context in their respective countries when instigating measures aimed at constricting the pandemic’s growth.
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SciScore for 10.1101/2020.03.30.20047589: (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 Multiple R2 indicates that 85.09% of the variation in growth can be predicted by the context variables; estimated power to predict multiple R2 is at the maximum of 1.000, as calculated with G*Power 3.1. G*Powersuggested: (G*Power, RRID:SCR_013726)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.Res…
SciScore for 10.1101/2020.03.30.20047589: (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 Multiple R2 indicates that 85.09% of the variation in growth can be predicted by the context variables; estimated power to predict multiple R2 is at the maximum of 1.000, as calculated with G*Power 3.1. G*Powersuggested: (G*Power, RRID:SCR_013726)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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