Evaluating the impact of mobility on COVID-19 pandemic with machine learning hybrid predictions.

ABSTRACT: COVID-19 pandemic had expanded to the US since early 2020 and has caused nationwide economic loss and public health crisis. Until now, although the US has the most confirmed cases in the world and are still experiencing an increasing pandemic, several states insisted to re-open business activities and colleges while announced strict control measures. To provide a quantitative reference for official strategies, predicting the near future trend based on finer spatial resolution data and presumed scenarios are urgently needed. In this study, the first attempted COVID-19 case predicting model based on county-level demographic, environmental, and mobility data was constructed with multiple machine learning techniques and a hybrid framework. Different scenarios were also applied to selected metr

SUBMITTER: Kuo CP 

PROVIDER: S-EPMC7837279 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature