Time dynamics of COVID-19
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Abstract
We apply tools from functional data analysis to model cumulative trajectories of COVID-19 cases across countries, establishing a framework for quantifying and comparing cases and deaths across countries longitudinally. It emerges that a country’s trajectory during an initial first month “priming period” largely determines how the situation unfolds subsequently. We also propose a method for forecasting case counts, which takes advantage of the common, latent information in the entire sample of curves, instead of just the history of a single country. Our framework facilitates to quantify the effects of demographic covariates and social mobility on doubling rates and case fatality rates through a time-varying regression model. Decreased workplace mobility is associated with lower doubling rates with a roughly 2 week delay, and case fatality rates exhibit a positive feedback pattern.
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SciScore for 10.1101/2020.05.21.20109405: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The advantages afforded by a functionally-minded approach are not immune to limitations imposed by data quality, however. The bias in COVID-19 case count is difficult to control for, as the causes of under-reporting are several and complex (e.g., the delay between infection and confirmation, confounds in testing availability, prevalence of asymptomatic carriers, etc.). Findings regarding individual countries must be evaluated in light …
SciScore for 10.1101/2020.05.21.20109405: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The advantages afforded by a functionally-minded approach are not immune to limitations imposed by data quality, however. The bias in COVID-19 case count is difficult to control for, as the causes of under-reporting are several and complex (e.g., the delay between infection and confirmation, confounds in testing availability, prevalence of asymptomatic carriers, etc.). Findings regarding individual countries must be evaluated in light of the their unique set of biases. Indeed, this issue does not yet have a clear solution and warrants continued attention. A feature of our analysis that is favorable is that while absolute case counts may be subject to reporting error, the trends in time-dynamics on which we focus here are more robust, in the sense that biases for a given country may affect the entire trajectory, although to a different degree over time as for example testing is ramped up. Applying functional PCA led to the discovery of four main patterns of disease progression since initial exposure and to identify the countries which follow them. A complementary analysis of percentlle rank dynamics allows for comparison of relative performance of countries at different points in time. In terms of predictive modeling, we introduce a dynamic FPCA approach for forecasting country-specific case counts, illustrated with 10-day forecasts. These forecasts, when compared to the eventually observed curves, can illustrate whether a country over- or under-performs during a given shorter...
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: Please consider improving the rainbow (“jet”) colormap(s) used on page 10. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
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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