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Creators/Authors contains: "Dubey, Paromita"

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  1. ; ; (, The Annals of Statistics)
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  2. ; (, Journal of the American Statistical Association)
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  3. ; ; ; ; ; (, NeuroImage)
    null (Ed.)
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  4. ; ; ; ; ; ; ; ; (, Scientific Reports)
    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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