Systematic analysis of the effectiveness of adding human mobility data to covid-19 case prediction linear models
<|reference_start|>Systematic analysis of the effectiveness of adding human mobility data to covid-19 case prediction linear models: Human mobility data has been extensively used in covid-19 case prediction models. Nevertheless, related work has questioned whether mobility data really helps that much. We present a systematic analysis across mobility datasets and prediction lookaheads and reveal that adding mobility data to predictive models improves model performance only for about two months at the onset of the testing period, and that performance improvements -- measured as predicted vs. actual correlation improvement over non-mobility baselines -- are at most 0.3.<|reference_end|>
@article{abrar2024systematic,
    title={Systematic analysis of the effectiveness of adding human mobility data
  to covid-19 case prediction linear models},
    author={Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak and Vanessa
  Frias-Martinez},
    journal={arXiv preprint arXiv:2407.10304},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.10304},
    primaryClass={cs.CY cs.SI}
}