Time dynamics of COVID-19.
Sci Rep
; 10(1): 21040, 2020 12 03.
Article
in English
| MEDLINE | ID: covidwho-1493184
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pandemics
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Sci Rep
Year:
2020
Document Type:
Article
Affiliation country:
S41598-020-77709-4
Similar
MEDLINE
...
LILACS
LIS