Enhancing long-term forecasting: Learning from COVID-19 models.

ABSTRACT: While much effort has gone into building predictive models of the COVID-19 pandemic, some have argued that early exponential growth combined with the stochastic nature of epidemics make the long-term prediction of contagion trajectories impossible. We conduct two complementary studies to assess model features supporting better long-term predictions. First, we leverage the diverse models contributing to the CDC repository of COVID-19 USA death projections to identify factors associated with prediction accuracy across different projection horizons. We find that better long-term predictions correlate with: (1) capturing the physics of transmission (instead of using black-box models); (2) projecting human behavioral reactions to an evolving pandemic; and (3) resetting state variables to accoun

SUBMITTER: Rahmandad H 

PROVIDER: S-EPMC9119494 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature