Contextual factors and the COVID ‐19 outbreak rate across U.S. counties in its initial phase
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Abstract
Background
This study examines the association of contextual factors with the COVID‐19 outbreak rate across U.S. counties in its initial phase.
Methods
Contextual factors are simultaneously tested at the county‐ and state‐level with a multilevel linear model using full maximum likelihood.
Results
The variation between states is substantial and significant (ICC = 0.532, u 0 = 8.20E−04, P < .001). At the state level, the cultural value of collectivism and the contextual factor of government spending are positively associated with the outbreak rate. At the county level, the racial and ethnic composition contributes to outbreak differences, disproportionally affecting black/African, native, Asian, and Hispanic Americans as well as native Hawaiians. Counties with a higher median age and a higher household income have a stronger outbreak. Better education and personal health are generally associated with a lower outbreak. Obesity and smoking are negatively related to the outbreak, in agreement with the value expectancy concepts of the health belief model. Air pollution is another significant contributor to the outbreak.
Conclusions
Because of a high variation in contextual factors, policy makers need to target pandemic responses to the smallest subdivision possible, so that countermeasures can be implemented effectively.
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SciScore for 10.1101/2020.05.13.20101030: (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: 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…
SciScore for 10.1101/2020.05.13.20101030: (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: 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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